Comparison of the studies that varied the OLR by changing the substrate concentration.
\r\n\tThe application of these complex statistical models provides a greater understanding of the complex processes and mechanisms. Complex statistical models are a powerful tool that enables researchers in the health and medical sciences to increase their knowledge and understanding of complex systems and thus advance knowledge.
\r\n\r\n\tThis book is devoted to applying complex models to health and medical sciences, both the classical and Bayesian approaches, and this book contain documentation of the contributions with the codes or script of the data analysis, that is relevant because it will help readers apply the models to new contexts.
",isbn:"978-1-80356-078-6",printIsbn:"978-1-80356-077-9",pdfIsbn:"978-1-80356-079-3",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!1,isSalesforceBook:!1,isNomenclature:!1,hash:"c5034363e1754265689dea0988fd89f8",bookSignature:"Prof. Cruz Vargas-De-León",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/10678.jpg",keywords:"Generalized Estimating Equation, Longitudinal Model, Path Analysis, Structural Equation Models, Modelling Recurrent Events, Multiple Survival Outcomes, Spatial Models, Temporal Models, Meta-Regressions, Clinical Trials, Structural Equation Modelling, Bayesian Statistics",numberOfDownloads:84,numberOfWosCitations:0,numberOfCrossrefCitations:0,numberOfDimensionsCitations:0,numberOfTotalCitations:0,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"December 3rd 2021",dateEndSecondStepPublish:"December 24th 2021",dateEndThirdStepPublish:"March 1st 2022",dateEndFourthStepPublish:"May 20th 2022",dateEndFifthStepPublish:"July 19th 2022",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"8 months",secondStepPassed:!0,areRegistrationsClosed:!0,currentStepOfPublishingProcess:5,editedByType:null,kuFlag:!1,biosketch:'Cruz Vargas-De-León received a certificate for highly cited research in "Mathematical Biosciences". He has been biographed by Marquis Who\'s Who in the World. Two of his articles have been awarded "Excellent papers" by National Program for Research Evaluation in Italy.',coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"421022",title:"Prof.",name:"Cruz",middleName:null,surname:"Vargas-De-León",slug:"cruz-vargas-de-leon",fullName:"Cruz Vargas-De-León",profilePictureURL:"https://mts.intechopen.com/storage/users/421022/images/system/421022.png",biography:'Cruz Vargas-De-León is a Professor of Biostatistics and Applied Mathematics. He has a bachelor\'s degree in mathematics (Statistics), a master\'s degree in health sciences, a master\'s degree in complexity sciences, and is currently a Student Ph.D. in Health Sciences. He is interested in Biostatistical and Biomathematical Modelling for Health. He has published more than 50 scientific articles, 35 of them in high-impact journals and indexed in JCR. He is also an Academic Editor of “International Journal of Hypertension”. \nHe has participated in the validation of surveys, randomized controlled trials, systematic reviews and meta-analyses, the construction of indices in medicine, and the identification of immunological biomarkers in cancer and epidemiological studies (Syphilis, Dengue, SARS-CoV-2, among others), and estimation of parameters of differential equation models.\nHe has received a certificate for the highly cited research in "Mathematical Biosciences" (2016, Elsevier), and the Guerrero State Award for Merit in Science and Technology "Guillermo Soberón" (2016). He has been biographed by Marquis Who\'s Who in the World in Issue 30 (2013). Two of his articles have been awarded "Excellent papers" by National Program for Research Evaluation (2011-2014) in Italy. Since 2015 he is a member of the National System of Researchers (SNI, in Spanish) from the National Council of Science and Technology (CONACYT, in Spanish).',institutionString:"Universidad Autónoma de Guerrero",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"0",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"Universidad Autónoma de Guerrero",institutionURL:null,country:{name:"Mexico"}}}],coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"15",title:"Mathematics",slug:"mathematics"}],chapters:[{id:"83034",title:"Optimal N-of-1 Clinical Trials for Individualized Patient Care and Aggregated N-of-1 Designs",slug:"optimal-n-of-1-clinical-trials-for-individualized-patient-care-and-aggregated-n-of-1-designs",totalDownloads:2,totalCrossrefCites:0,authors:[null]},{id:"81784",title:"Practical and Optimal Crossover Designs for Clinical Trials",slug:"practical-and-optimal-crossover-designs-for-clinical-trials",totalDownloads:4,totalCrossrefCites:0,authors:[null]},{id:"82499",title:"Modelling Agitation-Sedation (A-S) in ICU: An Empirical Transition and Time to Event Analysis of Poor and Good Tracking between Nurses Scores and Automated A-S Measures",slug:"modelling-agitation-sedation-a-s-in-icu-an-empirical-transition-and-time-to-event-analysis-of-poor-a",totalDownloads:17,totalCrossrefCites:0,authors:[{id:"39457",title:"Prof.",name:"Irene",surname:"Hudson",slug:"irene-hudson",fullName:"Irene Hudson"}]},{id:"82011",title:"Spatial Statistics in Vector-Borne Diseases",slug:"spatial-statistics-in-vector-borne-diseases",totalDownloads:14,totalCrossrefCites:0,authors:[null]},{id:"81944",title:"The Basics of Structural Equations in Medicine and Health Sciences",slug:"the-basics-of-structural-equations-in-medicine-and-health-sciences",totalDownloads:20,totalCrossrefCites:0,authors:[null]},{id:"81710",title:"Spatial Modeling in Epidemiology",slug:"spatial-modeling-in-epidemiology",totalDownloads:27,totalCrossrefCites:0,authors:[null]}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"444315",firstName:"Karla",lastName:"Skuliber",middleName:null,title:"Mrs.",imageUrl:"https://mts.intechopen.com/storage/users/444315/images/20013_n.jpg",email:"karla@intechopen.com",biography:"As an Author Service Manager, my responsibilities include monitoring and facilitating all publishing activities for authors and editors. From chapter submission and review to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. 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\nAccording to Reddy et al. [3], one of the major drawbacks of using organic wastes is that only 30–40% of the substrate is used to H2 production and 60–70% is converted to several other metabolites. However, some metabolites are commercially attractive, such as acetic acid, butyric acid, propionic acid, lactic acid, succinic acid, 1,3-propanediol, ethanol, methanol, etc. [4, 5].
\nH2 production has been carried out with a variety of organic wastes, in which the source of carbonaceous organic material is based on glucose, sucrose, starch, xylose, cheese-processing wastewater, tapioca-processing wastewater, and sugarcane vinasse [6–9].
\nThe fermentation process for the production of H2 in anaerobic reactors is greatly influenced by several factors, such as the type of wastewater, the inoculum, the type of reactor, the nutritional requirements, the temperature, and the pH [10–12].
\nFor practical engineering, industrial H2 production requires continuous or semicontinuous production processes. Several types of reactors have been studied to effectively generate H2. Reactors for continuous H2 production include suspended biomass reactors, e.g., continuous stirred tank reactors (CSTRs) [13–15] and anaerobic sequencing bed reactors (ASBRs) [16], and biofilm reactors such as anaerobic packed bed reactors (APBRs) [17] and anaerobic fluidized bed reactors (AFBRs) [6–9, 18]. The advantages and disadvantages of different reactor types vary. Biofilm reactors can overcome the drawbacks of suspended biomass reactors by decoupling the biomass retention time from HRT, thus increasing the biomass concentration in the reactor. The hydraulic mixing regime is usually more turbulent in AFBRs than in APBRs, which improves mass transfer and treatment efficiencies because bed fluidization favors contact between the biofilm and substrate [19–21].
\nHydrogen production is a microbial-mediated process dependent on several parameters that can affect the performance. Some of these are the inoculum source, pH, substrate concentration, accessible nutrients, HRT, and temperature [11, 21]. Their control in appropriate range can enrich the microbial community with hydrogen producers, eliminate hydrogen consumers, shift the metabolism to favor hydrogen production, increase substrate conversion efficiency, and increase the overall process potential [1, 10, 11, 21]. The organic loading rate (OLR; influent substrate concentration/HRT) is a parameter that evaluates the simultaneous effects of influent substrate concentrations and HRTs when synthetic or real wastewaters are used to produce H2 in anaerobic reactors [13–18, 22–26]. Previous studies in our research group observed hydrogen production with glucose concentrations of 2000 mg L−1 [27–29], 4000 mg L−1 [6, 30] and 5000 mg L−1 [31]. Increasing glucose concentration to 10 g L−1 and 25 g L−1 can determine the range where hydrogen-producing acidogenesis shifts to solventogenesis. Therefore, the present study examines the effect of both OLR and alkalinity supplementation on H2 production in AFBRs with influent glucose concentrations of 10 g L−1 (OLRs of 30–240 kg COD m−3 day−1) and 25 g L−1 (OLRs of 75–600 kg COD m−3 day−1).
A schematic diagram of the two identical jacketed AFBRs used in this study is presented in Figure 1. The reactors were constructed with a transparent acrylic tube, within 5.3 cm of internal diameter and 190 cm of height, and filled with expanded clay (diameter = 2.8–3.3 mm, density = 1.5 g cm−3). Each AFBR was equipped with a water jacket that recirculated heated water from a thermostatic bath to maintain the temperature at 30°C. The AFBRs were fed with synthetic wastewater containing glucose (10 and 25 g L−1) as the main carbon source supplemented with the following nutrients: SeO2, 0.07 mg L−1; CoCl2·2H2O, 0.08 mg L−1; FeCl3·6H2O, 0.5 mg L−1; NiSO4·6H2O, 1 mg L−1; FeSO4·7H2O, 5 mg L−1; K2 HPO4, 21.7 mg L−1; Na2HPO4·2H2O, 33.4 mg L−1: CaCl2·6H2O, 47 mg L−1; KH2PO4, 85 mg L−1; and CO(NH2)2N2O, 125 mg L−1. In order to control the pH of the reactors at 5.0–5.5, hydrochloric acid (10 M) and sodium bicarbonate (1 g L−1) were also used [6].
Schematic description of the AFBR.
The AFBRs were inoculated with sludge from an upflow anaerobic sludge blanket (UASB) reactor treating swine wastewater effluent. The sludge was heat treated for 10 min at 90°C according to the methodology of Kim et al. [25] in order to eliminate hydrogen consumers and select for endospore producers. The reactors were inoculated at a rate of 10% of the sludge feed volume.
\nThe total liquid flow rate into the AFBRs was maintained at 128 L h−1 (expansion = 30%). This flow rate produced a superficial velocity 1.30 times greater than the minimum fluidization velocity. At first, in order to activate the H2-producing biomass, the two AFBRs were operated in batch mode for 48 h while periodically recording the substrate consumption by microorganisms. When the activation period was over, the reactors were operated in continuous mode with an HRT of 8 h, which was then decreased stepwise to 6 h, 4 h, 2 h, and 1 h. The composition of the gaseous products (H2 and CO2) and soluble metabolites (volatile organic acids and alcohols) produced during fermentative H2 production was monitored as a function of time.
\nTo facilitate discussion of the results and to identify the reactors, each reactor was named according to the influent glucose concentration: the reactor operated with 10 g L−1 glucose was named “R10,” and the reactor operated with 25 g L−1 glucose was named “R25.”
The GOD-PAP enzymatic method [32] was used to determine the glucose concentrations. Total solids (TS), volatile suspended solids (VSS), total volatile solids (TVS), and chemical oxygen demand (COD) analyses were performed according to Standard Methods for the Examination of Water and Wastewater [33].
\nA gas chromatograph (GC-2010, Shimadzu, Tokyo, Japan) equipped with a thermal conductivity detector (TCD) was used to determine the biogas composition. Argon was used as the carrier gas with a Carboxen 1010 PLOT column (30 m long × 0.53 mm internal diameter). A gas chromatograph (GC-2010, Shimadzu, Tokyo, Japan) equipped with a flame ionization detector (FID) was used to determine volatile organic acids and alcohols. The GC used a COMBI-PAL headspace sample introduction system (AOC 5000 model) and HP-INNOWAX column (30 m long × 0.25 mm internal diameter × 0.25 mm film thickness) [32].
\nA gas meter (type TG1; Ritter Inc., Germany) was used to measure the amount of H2 generated.
Figure 2 presents the variation in pH effluent as a function of OLR for the two AFBRs used in this study. The pH remained stable throughout the system operation within the operating range of acidogenic anaerobic systems, i.e., between 3.7 in Barros et al. [6], 3.4 and 3.6 in R10, and 3.3 and 3.5 in R25. The influent pH remained between 5.2 and 5.9 in Barros et al. [6], 4.8 and 5.6 in R10, and 5.5 and 5.9 in R25 (Figure 2).
pH effluent as a function of the OLR for the AFBRs.
Figure 3 presents the variation in glucose conversion as a function of OLR for the AFBRs used in this study. To estimate glucose consumption during fermentation, glucose levels were measured in the fermentation medium (Figure 3). Glucose consumption by microorganisms was recorded at all OLR intervals in both AFBRs. The data indicate that glucose conversion decreased with the increase of OLR at all concentrations. For reactor R10, when OLR was increased from 30–120 kg COD m−3 day−1, glucose conversion decreased from 57 to 36%, but when OLR increased to 240 kg COD m−3 day−1, glucose conversion increased to 41%. For reactor R25, when OLR increased from 75 to 600 kg COD m−3 day−1, glucose conversion decreased from 36 to 20%.
Glucose conversion as a function of the OLR for the AFBRs.
Figure 4 presents the variation in the hydrogen production rate (HPR) as a function of OLR for the two AFBRs used in this study. Similar to the results of Barros et al. [6] for an AFBR with expanded clay as the support material, an influent glucose concentration of 4 g L−1, and alkalinity supplementation (values presented in Figure 2), the HPR values for R10 increased linearly from 0.12 to 1.58 L h−1 L−1 when OLR increased from 30 to 240 kg COD m−3. By contrast, a linear relationship between HPR and OLR was not observed in R25 for OLR ranging from 75 to 600 kg COD m−3. The maximum HPR values were 1.58 and 0.84 L h−1 L−1 for reactors R10 and R25, respectively.
HPR as a function of the OLR for the AFBRs.
Figure 5 presents the variation in HY as a function of OLR for the two AFBRs used in this study. The HY values increased with increasing OLR in both reactors. For reactor R10, when OLR was increased from 30 to 120 kg COD m−3 day−1, HY increased significantly from 0.48 to 1.32 mol H2 mol−1 glucose, but when OLR increased to 240 kg COD m−3 day−1, HY decreased to 1.04 mol H2 mol−1 glucose. For reactor R25, when OLR increased from 75 to 300 kg COD m−3 day−1, the increase in HY was less significant, i.e., from 0.44 to 0.63 mol H2 mol−1 glucose, but when OLR increased to 600 kg COD m−3 day−1, the yield decreased to 0.56 mol H2 mol−1 glucose.
HY as a function of the OLR for the AFBRs.
Figure 6 presents the variation in H2 content as a function of OLR for the two AFBRs used in this study. In reactors R10 and R25, the behavior of the H2 content also varied according to changes in OLR. The hydrogen content of the biogas increased with increasing OLR in both reactors, with a higher H2 content for HRT 1 h (240 and 600 kg COD m−3 day−1, respectively). The H2 content ranged from 8 to 58% for R10 and 10 to 57% for R25.
H2 content as a function of the OLR for the AFBRs.
The glucose conversion, HPR, HY, and H2 content of the reactors are consistent with the results of several studies conducted using AFBRs [6, 18, 27, 28, 30–32, 34, 35].
\nTable 1 compares studies that evaluated OLR and HY. Studies that observed a decrease in HY with increasing OLR used an OLR range of 6–833.3 kg COD m−3 day−1 and reported HYs of 4.26–0.81 mol H2.mol−1 substrate. By contrast, studies that observed an increase in HY with increasing OLR worked with an OLR range of 13.5–480 kg COD m−3 day−1 and reported HYs of 0.94–2.49 mol H2 mol−1 substrate.
Study | Substrate | OLR (kg m−3 d−1) | HY (mol H2 mol−1 substrate) | ||
---|---|---|---|---|---|
Low | High | Low OLR | High OLR | ||
Lower OLR improves H2 production | |||||
Yu et al. [36] | Rice winery | 168 | 432 | 1.89 | 1.79 |
Van Ginkel and Logan [24] | Glucose | 25.6 | 76.8 | 2.20 | 2.00 |
Van Ginkel and Logan [37] | Glucose | 6 | 24 | 2.80 | 2.20 |
Kyazze et al. [15] | Sucrose | 22.4 | 112.2 | 1.65 | 0.81 |
Lin et al. [38] | Sucrose | 34.7 | 833.3 | 4.26 | 2.31 |
Davila-Vasquez et al. [39] | Cheese whey | 54 | 138.6 | 2.4 | 1.0 |
Higher OLR improves H2 production | |||||
Lin et al. [18] | Sucrose | 13.5 | 107.9 | 1.69 | 2.49 |
Sucrose | 20 | 160 | 1.34 | 2.17 | |
Zhang et al. [35] | Glucose | 60 | 480 | 0.94 | 1.19 |
Shida et al. [27] | Glucose | 6 | 48 | 1.84 | 2.29 |
Perna et al. [17] | Cheese whey | 22 | 37 | 0.5 | 0.67 |
Comparison of the studies that varied the OLR by changing the substrate concentration.
Adapted from Kraemer and Bagley [26].
According to Kraemer and Bagley [26], the reason for the variations of H2 yield at lower or higher OLRs is unknown. High OLR values may reduce the production of H2 by (1) increasing inhibition by volatile fatty acids (VFAs) with increasing OLR, (2) decreasing thermodynamic regulation due to lower dissolved H2 concentrations at lower OLRs, (3) affecting acetogenic activity, and (4) increase CO2 inhibition by increasing the concentration of dissolved CO2.
\nInhibition by VFAs at high OLR values appears to be a valid explanation. The ability of added external VFA to reduce or inhibit the production of H2 in mixed-culture and continuous-flow systems has been studied, and there is consensus that butyrate increases higher inhibition than the acetate [18, 24, 40].
\nH2 production was also assessed with or without the addition of sodium bicarbonate as an alkalizing agent. The effect of the alkalizing agent on pH was important for controlling the hydrogen content and CO2 in the system. The high HY in the absence of a buffering agent can be attributed to the pH range of the reactor and the CO2 concentrations produced at steady bicarbonate concentrations [41–44].
Table 2 presents the distribution of soluble microbial products (SMPs) with increasing glucose concentration and increasing OLRs in the AFBRs. The molar fractions of acetic and butyric acid were the largest by percentage. Barros et al. [6] for an AFBR with expanded clay as the support material, an influent glucose concentration of 4 g L−1, and alkalinity supplementation (values presented in Table 2) observed a descending order of products of acetate (32.99–46.81%), butyrate (37.30–41.49%), ethanol (10.18–22.95%), and propionate (1.26–4.90%). In our reactor R10, the products in descending order were ethanol (45.54–71.54%), acetate (27.11–50.63%), butyrate (2.91–31.03%) and methanol (0.00–14.41%). In reactor R25, the products in descending order were ethanol (48.00–71.54%), acetate (12.05–37.43%), butyrate (01.02–29.09%), and methanol (0.00–14.41%) (Table 2).
Reactor | OLR (kg COD m−3 day−1) | HAc (mM) | HBu (mM) | HPr (mM) | EtOH (mM) | MetOH (mM) | TVFA (mM) | TSolv (mM) | HAc/HBu |
---|---|---|---|---|---|---|---|---|---|
Barros et al. [6] | 12 | 6.25 | 7.67 | 0.68 | 4.35 | 0 | 14.60 | 4.35 | 0.81 |
16 | 10.00 | 11.08 | 0.34 | 5.43 | 0 | 21.42 | 5.43 | 0.90 | |
24 | 12.50 | 11.08 | 0.41 | 2.72 | 0 | 23.98 | 2.72 | 1.13 | |
48 | 12.83 | 10.63 | 0.68 | 4.35 | 0 | 24.13 | 4.35 | 1.21 | |
96 | 9.06 | 8.35 | 1.01 | 2.28 | 0 | 18.42 | 2.28 | 1.08 | |
R10 | 30 | 10.73 | 0.62 | 0.00 | 9.35 | 0.49 | 11.34 | 9.84 | 17.42 |
40 | 7.23 | 1.57 | 0.00 | 10.62 | 1.44 | 8.80 | 12.06 | 4.62 | |
60 | 9.66 | 3.53 | 0.00 | 12.70 | 9.58 | 13.20 | 22.28 | 2.74 | |
120 | 6.37 | 5.75 | 0.00 | 10.70 | 0.00 | 12.11 | 10.7 | 1.11 | |
240 | 6.65 | 7.61 | 0.00 | 10.27 | 0.00 | 14.27 | 10.27 | 0.87 | |
R25 | 75 | 9.04 | 2.60 | 0.13 | 11.59 | 0.78 | 11.77 | 12.37 | 3.47 |
100 | 17.39 | 2.70 | 1.20 | 21.24 | 4.10 | 21.30 | 25.34 | 6.43 | |
150 | 6.64 | 1.11 | 0.00 | 39.42 | 7.94 | 11.70 | 47.36 | 6.01 | |
300 | 5.92 | 3.53 | 0.00 | 10.65 | 2.01 | 9.45 | 12.66 | 1.68 | |
600 | 4.88 | 6.18 | 0.00 | 10.18 | 0.00 | 11.06 | 10.18 | 0.79 |
Effect of glucose concentration and OLR on the SMP distribution in the AFBRs.
HAc acetate, HBu butyrate, HPr propionate, EtOH ethanol, MetOH methanol, TVFA total volatile fatty acids, TVFA HAc + HBu + HPr, SMP TVFA + EtOH + MetOH, HAc/SMP molar acetate-to-SMP ratio, HBu/SMP molar butyrate-to-SMP ratio, HPr/SMP molar propionate-to-SMP ratio, EtOH/SMP molar ethanol-to-SMP ratio, MetOH/SMP molar methanol-to-SMP ratio, HAc/HBu molar acetate-to-butyrate ratio
Previous studies employing conditions similar to those used in the present study observed the production of similar metabolites, although differences in the distributions of the metabolites were observed [6, 18, 27, 28, 30–32, 34, 35].
\nThe reactors R10 and R25 produced higher amounts of solvents, such as MetOH and EtOH in the R25 reactor. The higher EtOH concentrations observed in R10 and R25 are similar to the results of Wu et al. [34]. However, our recent studies [6, 27, 29] that used the same medium composition, inoculum, and support material have significantly different results. Barros et al. [6] with an influent glucose concentration of 4 g L−1, and alkalinity supplementation, observed ethanol percentages lower than 22.95% at the beginning of the operation and subsequently decreased and stabilized to 11%. EtOH production is considered unfavorable for hydrogen metabolite production because no H2 is consumed or produced (Eq. (1)):
\nPropionate was only detected during the operation of the reactor containing 25 g L−1, with maximum concentration of 1.20 mM in the OLR of 100 kg COD m−3 day−1. Propionic acid production was not observed in AFBRs with influent glucose concentration of 2 g L−1 [27, 29]. Zhang et al. [35] suggested that the absence of propionic acid may be due to inhibition of the activity of the bacteria that form this acid under low pH conditions; these bacteria may be sensitive to both low HRTs and high OLRs. Moreover, the absence of propionic acid production ensures greater production of hydrogen due to the lower consumption of H2 for forming propionate (Eq. (2)):
\nBoth HAc and HBu are soluble metabolites favoring H2 production because these products are generated during H2 production (Eqs. (3) and (4)):
\nPrevious studies have observed that H2 production increases with the molar ratio of HAc/HBu [45, 46]. Table 2 presents the variation of the HAc/HBu ratio in R10 and R25. Barros et al. [6] for an influent glucose concentration of 4 g L−1, and alkalinity supplementation, observed the best proportion of soluble metabolites and therefore a higher yield of hydrogen, with molar ratios of HAc/HBu ranging from 0.81 to 1.21 for OLRs varied 12–96 kg COD m−3 day−1, respectively, but decreasing to 1.08 for an OLR of 96 kg COD m−3 day−1. In our R25, similar behavior of Barros et al. [6] were obtained, but in R10 HAc/HBu ratio decreased from 17.42 to 0.87 when the OLRs increased from 30 to 240 kg COD m−3 day−1.
\nAccording to Hafez et al. [45], when OLR increased from 6.5 to 103 g COD L−1 day−1, acetate and butyrate were the main liquid products, with trace concentrations of ethanol and no detectable lactate, whereas in the OLR range of 154–206 g COD L−1 day−1, the concentrations of propionate, isovalerate, valerate, and ethanol increased markedly. The steady-state average molar ratios of acetate/butyrate were 2.3, 2.3, 2.0, and 2.2 for OLRs of 6.5, 25.7, 51.4, and 103 g COD L−1 day−1, respectively, but decreased to 1.1 for OLRs of 154 and 206 g COD L−1 day−1.
\nAccording to Prakasham et al. [47], at lower substrate conditions with the limitation of substrate concentration, increasing glucose concentration progressively increases H2 production because of effective metabolism and further H2 production process. However, higher concentrations can also negatively impact H2 production. When the H2 yield observed value reduced because the glucose concentration was above the optimum value, a limited glucose utilization occurred, or a shift in the metabolic pathway from the acidogenic phase to a solventogenic phase took place.
\nHydrogen and CO2 were the only gaseous metabolites during all stages of the experiment. NO CH4 was detected in the biogas from either reactor. The combination of heat treatment of the inoculum and operation under acidogenic pH conditions inhibited the methanogenic activity responsible for the consumption of hydrogen in the system. Furthermore, the results in the literature suggest that manipulating some operational parameters such as the HRT contributes to the elimination of methanogenic archaea in the reactors.
\nAccording to Chen et al. [48], these microorganisms fail to thrive in part because the maximum specific growth rate of methanogenic archaea (μmaximum = 0.0167 h−1) is significantly lower than that of acidogenic microorganisms (μmaximum = 0.083 h−1). Thus, methanogenic microorganisms are unable to reproduce or remain in equilibrium under these conditions, resulting in their removal from the reactor.
The carbon balance in the reactors can be calculated by Eq. (5) according to Gavala et al. [49].The comparison between measured and calculated COD concentrations for each steady state is also presented. The COD calculations were performed as the following: the products (CODproducts) and the glucose (CODglucose) COD concentrations were calculated according to Eqs. (5) and (6), respectively. The CODresidual was calculated after subtraction of the sum of the CODproducts and CODglucose from the CODmeasured (Eq. (3)).The CODothers corresponds to the non-identified metabolic products during glucose fermentation:
\nwhere a, b, c, d, and e are the measured concentrations of the acetic acid, butyric acid, propionic acid, methanol, and ethanol, respectively.
\nwhere f is the measured concentration of glucose.
\nThe difference between CODmeasured and COD based on SMP may be attributed to the presence of other soluble metabolites that were not detected, e.g., lactic acid and formic acid, because the chromatographic method of headspace extraction used in this study only detects alcohols and volatile acids.
\nThis difference was calculated based on Eq. (7):
\nTable 3 presents influent and effluent COD values and standard deviations as well as efficiencies for all reactors. Influent COD represents glucose added to the wastewater and carbonaceous matter present in urea. Effluent COD corresponds to the carbonaceous matter in the effluent that was oxidized. Carbonaceous matter present in the effluent consists of non-consumed glucose; soluble metabolites, e.g., organic acids, solvents, and other intermediary compounds; and biomass detached from the support medium.
OLR (kg COD m−3 day−1) | Influent COD (mg L−1) | Effluent COD (mg L−1) | COD removal (%) | |
---|---|---|---|---|
Barros et al. [6] | 12 | 4216 ± 210 | 3788 ± 153 | 10 ± 6 |
16 | 4140 ± 206 | 3349 ± 146 | 19 ± 9 | |
24 | 4139 ± 270 | 3718 ± 165 | 10 ± 4 | |
48 | 4487 ± 220 | 3805 ± 191 | 15 ± 2 | |
96 | 4312 ± 226 | 3680 ± 136 | 15 ± 4 | |
R10 | 30 | 11,298 ± 954 | 8617 ± 457 | 24 ± 5 |
40 | 10,439 ± 843 | 9056 ± 419 | 13 ± 6 | |
60 | 10,693 ± 977 | 8639 ± 433 | 19 ± 3 | |
120 | 10,175 ± 799 | 8589 ± 447 | 16 ± 2 | |
240 | 10,969 ± 901 | 8705 ± 512 | 21 ± 2 | |
R25 | 75 | 26,126 ± 1024 | 20,202 ± 978 | 23 ± 3 |
100 | 26,447 ± 1201 | 22,352 ± 883 | 15 ± 2 | |
150 | 27,285 ± 1392 | 22,207 ± 791 | 19 ± 2 | |
300 | 26,116 ± 1273 | 23,502 ± 943 | 10 ± 1 | |
600 | 28,216 ± 1321 | 25,242 ± 967 | 11 ± 2 |
Influent COD, effluent COD, and COD removal in AFBRs.
The theoretical effluent COD was calculated based on stoichiometric relationships for oxidation of glucose, acetic acid, butyric acid, propionic acid, biomass, ethanol, and methanol to estimate the carbon balance. Theoretical COD values for the remaining glucose, soluble metabolites, and biomass as well as the difference between the theoretical total COD and the COD measured for all reactors are presented in Table 4.
Reactor | OLR (kg COD m−3 day−1) | HRT (h) | CODt, glucose (mg L−1) | CODt, acetate (mg L−1) | CODt, butyrate (mg L−1) | CODt propionate (mg L−1) | CODt, biomass (mg L−1) | CODt, ethanol (mg L−1) | CODt, methanol (mg L−1) | CODt total (mg L−1) | COD measured (mg L−1) | COD others (mg L−1) |
---|---|---|---|---|---|---|---|---|---|---|---|---|
Barros et al. [6] | 12 | 8 | 946 | 245 | 1382 | 0 | 192 | 90 | 24 | 3405 | 3788 | 39 |
16 | 6 | 475 | 192 | 1000 | 0 | 157 | 203 | 105 | 3157 | 3349 | 32 | |
24 | 4 | 901 | 320 | 1563 | 0 | 161 | 215 | 0 | 3432 | 3719 | 12 | |
48 | 2 | 666 | 320 | 1763 | 0 | 155 | 629 | 0 | 3455 | 3805 | 350 | |
96 | 1 | 1394 | 235 | 964 | 0 | 181 | 573 | 0 | 3556 | 3680 | 124 | |
R10 | 30 | 8 | 4514 | 757 | 645 | 0 | 148 | 1540 | 940 | 8545 | 8617 | 159 |
40 | 6 | 5807 | 438 | 705 | 0 | 157 | 457 | 564 | 8129 | 9056 | 104 | |
60 | 4 | 6935 | 291 | 551 | 0 | 140 | 631 | 0 | 8548 | 8639 | 91 | |
120 | 2 | 6659 | 364 | 858 | 0 | 134 | 585 | 0 | 8600 | 8589 | 254 | |
240 | 1 | 6639 | 294 | 699 | 0 | 168 | 959 | 104 | 8862 | 8705 | 301 | |
R25 | 75 | 8 | 17,177 | 1210 | 271 | 47 | 148 | 2178 | 144 | 21,174 | 20,202 | 1026 |
100 | 6 | 16,590 | 769 | 330 | 0 | 145 | 4825 | 760 | 23,419 | 22,352 | 486 | |
150 | 4 | 19,454 | 452 | 425 | 0 | 141 | 1692 | 275 | 22,439 | 22,207 | 107 | |
300 | 2 | 21,122 | 373 | 636 | 0 | 134 | 1360 | 96 | 23,722 | 23,502 | 17 | |
600 | 1 | 22,996 | 269 | 751 | 0 | 168 | 1023 | 0 | 25,206 | 25,242 | 35 |
Theoretical COD values of soluble metabolites, biomass COD, and effluent COD measured in AFBRs.
In the reactor operated by Barros et al. [6], this difference varied between 12 and 350 mg L−1, which corresponded to a variation of 0.34 and 9.19%. The reactor R10 showed a difference ranging from 91 to 301 mg L−1 (variation of 1.05 and 3.28%), whereas in the reactor R25, the difference varied between 17 and 1026 mg L−1 (variation of 0.07 and 4.62%).Those differences may be accredited to the presence of other metabolites such as lactic acid and formic acid that were not detected, probably due to the chromatographic method performed (headspace extraction), considering that this method can only detect volatile acids and alcohols.
\nThe largest variation between COD measured in the effluent and the theoretical COD (corresponding to glucose, soluble metabolites, and biomass in the effluent) was 9.19% based on the results obtained from the carbon balance. However, according to Standard Methods [33], the determination of metabolites and COD produces errors of close to 10%. For that reason, this variation may be attributed to the margin of error of the determination methods used.
Satisfactory performance for H2 production was observed in the anaerobic fluidized bed reactor containing 10 g L−1 glucose. However, in the reactor containing 25 g L−1 glucose, the yield was limited.
\nThe HPR had a linear increase with OLR, with the exception of reactor operated with 25 g L−1 glucose. The maximum HPR was 1.58 L h−1 L−1 obtained in the reactor with 10 g L−1 glucose for OLR of 240 kg COD m−3 day−1 (HRT = 1 h). The maximum HY was 1.32 mol H2 mol−1 glucose obtained in the reactor with 10 g L−1 glucose for HRT 2 h (OLR = 240 kg COD m−3 day−1).
\nThe H2 production with addition of sodium bicarbonate was important to control the pH and CO2 system. The reactors operated at high glucose concentrations (10 and 25 g L−1) showed higher proportions of solvents.
Today, there is no controversy about considering acute and chronic pain based on a foundation of neurobiology influenced by and interacting with biological, psychological, and social/contextual factors [1, 2, 3]. Hence, modern clinical practice applies a biopsychosocial (BPS) framework in assessments and treatments [4, 5]. This approach is the result of developments that have occurred over the past 70 years.
Units dedicated to treat pain were developed in the USA based on physicians’ experiences with chronic pain in soldiers during and after World War Two. During this period, surgeons and anaesthesiologists attempted to alleviate both chronic and acute pain mainly using blockades and local anaesthesia [6]. Later, this type of unit expanded into Europe and Sweden. The first multidisciplinary pain clinic opened in the 1960s as a development of the pain clinic founded by John Bonica in the 1950s at the University of Washington in Seattle (USA) [7]. Bonica realised that patients with complex pain problems were not helped by single specialties, and during the 1950s he brought neurosurgeons, psychiatrists, and anaesthesiologists to his clinic. In 1959, Wilbert Fordyce, a psychologist hired by the Department of Physical Medicine and Rehabilitation at the same hospital, became interested in applying behavioural strategies in the assessments and treatments of chronic pain. Their collaboration led to the incorporation of psychologists in pain clinics and later other health care providers trained in different but related areas [6]. Bonica also led an international initiative that resulted in the formation of an association of researchers and clinicians dedicated to the understanding and treatment of pain (International Association for the Study of Pain, IASP).
In 1982, Fordyce’s psychological program and Bonica’s pain clinic merged under the direction of John Loeser [6]. Under this new arrangement, patients were evaluated and treated by teams, and the BPS model started to be used in pain programs. These early programs had to deal with medication problems and addiction, so inpatient treatment became the standard. During the 1970s, the number of multidisciplinary pain clinics following the example of Seattle’s clinic grew in the USA and later in Australia, New Zealand, and Europe. During the 1980s, psychologists began to add cognitive treatment strategies to the programs, which opened up treatment to a broader mix of patients. By 1990, cognitive-behavioural pain management programs were widespread and became the golden standard of care. During the 1980s and the 1990s, many studies focused on interdisciplinary pain programs (IPRPs), and new theories were launched [6, 8, 9].
The positive development in the USA slowed down at the beginning of 2000, and most units offering IPRPs closed their operations in the following decade, except for units in the Department of Veterans Affairs (VA). The Commission for the Accreditation of Rehabilitation Facilities (CARF) offers a specific set of standards that emphasise the interdisciplinary setting and the BPS model for the treatment of chronic pain. As the CARF standards remained focused on the BPS framework, the number of accredited programs illustrates the development in the USA. In 1998, there were 205 accredited chronic pain programs in the USA. By 2004, the number decreased to 125, 11 of which were VA programs [6]. These programs, excluding the VA IPRPs, decreased to 63 in 2010, 53 in 2015, and 32 in 2020 (Carolan Terrence, CARF, personal communication). However, outside the USA, the development has gone in the opposite direction. By the end of 1990 outside the USA, fewer than five tertiary pain units with CARF accredited pain programs were in operation; however, by 2021, this number had increased to 140 (CARF, personal communication). According to many reports, the decline in the USA was due to opioid use as a medication for chronic pain, but this approach, as the result of the opioid pandemic, is currently being replaced by initiatives to re-start IPRP.
Both evidence and clinical practice guided the development of how to face the problem of chronic pain—from viewing chronic pain as a symptom of underlying causes to viewing chronic pain as a dysfunction (i.e., from a biomedical approach to a biopsychosocial approach). Therefore, treatments have evolved from monodisciplinary to multidisciplinary treatments and from multidisciplinary treatments to interdisciplinary programs.
During the 1970s and 1980s, the novel approaches to chronic pain developed slowly in Sweden. As new methods and treatments were developed, national guidelines for chronic pain treatment were warranted. In 1994, an expert group formed by the Swedish National Board of Health and Welfare summarised the recommendations for treatment of chronic pain based on the International Association for the Study of Pain (IASP) guidelines and available evidence at the time. In 2006 and 2010, two compilations of evidence for chronic pain treatments, commissioned by the Swedish Agency for Health Technology Assessment and Assessment of Social Services (SBU; see below), confirmed the conclusions of the 1994 report about appropriate methods and lack of evidence for methods still being used. In the 2006 and 2010 reports, one method was singled out as an evidence-based approach, the IPRP. These reports contributed to a governmental decision to financially support the development of IPRPs throughout Sweden. During this period, a registry for pain rehabilitation was formed through an initiative of the professions with the aim to analyse outcomes of pain rehabilitation. The registry with the support of the affiliated units and the national organisation of county councils (SKL) developed into a national quality registry that included all tertiary pain rehabilitation units as well as units operating at the primary care level.
In clinical practise, patients with complex chronic pain conditions with difficulties coping with their condition in daily life are referred to an IPRP. These patients’ ability to cope with their pain can be compromised by co-morbidities and/or their work situation. Often, these patients have tried monodisciplinary interventions and/or pharmacological treatments without marked improvements. The Swedish guidelines regarding indications for IPRP, which have been approved by several authorities and professional organisations, recommend that IPRP be offered to chronic pain patients with complex clinical presentations and when monodisciplinary interventions have not been effective [10].
In 2011, the IASP stated in the Declaration Montreal that ‘access to pain management is a fundamental human right’ [11]. This humanitarian approach is important; however, availability to IPRP is scarce, as mentioned above, in several parts of the world, and chronic pain is common in the general population—approximately 20% of the European and North American population has a significant chronic pain condition [12, 13]. In addition, as many patients with chronic pain rarely seek health care services, these patients seem to have adapted to their pain condition to lead lives with minor consequences to their function and well-being. This needs to be considered as IPRP is costly interventions in the short run and patients need to be fully invested in the process and very possibly have a sense of urgency to benefit from treatment and be motivated to engage in behavioural and cognitive change. The motivation to behavioural and cognitive change is fundamental as an indication for IPRP. For IPRP to be used with an ethical and humanitarian perspective, it needs to prioritise individuals who suffer from substantial consequences of their chronic pain condition regarding function, social, and/or psychological well-being.
The idea of treating chronic diseases with a broader approach than the biomedical approach was first launched by Engel in a biopsychosocial (BPS) model for the treatment of diseases, especially chronic diseases [14]. The model emphasises the mutual interactions between biological, psychological, and experiential or social factors that impact people’s perceptions of their overall health. This model lies at the core of the multidisciplinary and interdisciplinary approaches to the treatment of chronic pain. Similarities and differences between these approaches are described in detail elsewhere [7]. Although both rely on the BPS model, they differ regarding whether the goals of the professionals are integrated, whether professionals work collaboratively in teams, and whether their treatments are provided simultaneously or sequentially [9, 15]. The interdisciplinary treatment, which is based on the BPS approach [1], is the standard treatment used in IPRPs. According to IASP, interdisciplinary treatment is a:
The programs usually include experts working in an integrated manner with physical, social, psychological, and medical aspects to diminish the consequences of chronic pain in these or other areas [7, 16]. The principal components of IPRP are as follows:
a team assessment of the chronic pain problem and its consequences;
the establishment of a treatment plan, including interventions by different professions with goals to be achieved during the program;
communication between team members and between the team, the patient, and significant others;
deliveries of the different synchronised interventions of IPRP;
evaluation of the interventions;
documentation; and
a discharge process, including interaction with other stakeholders.
Other researchers have also identified the same content [17]. Although the areas covered by the interdisciplinary programs are well described elsewhere, there are very few descriptions of the interventions used in clinical practice in IPRPs, usually describing the interventions used in specific centres, such as Mayo Clinic or Chicago University Hospital [16]. In Sweden, it is possible to gather information on the interventions used in clinical practice from most of the IPRPs affiliated with the Swedish National Registry. Of the 39 affiliated units, 31 were included [18]. The usual contents of IPRP described by Swedish units are as follows:
dialogue and education (e.g., education, training in wellness and healthy living habits, meetings with families, video feedback, and couples therapy) and self-training (e.g., home lessons, activity diary, physical self-training, reflection time, and self-analysis);
activity training (activity training, graded activity training, and exposure training);
meetings (conferences with patients, rehabilitation team, vocational guidance, rehabilitation coordinator, goal-setting meetings, and meetings to check goal achievement);
cognitive behavioural therapy, other psychological treatments (e.g., supervised group therapy, pain or a stress coping course, psychological and social aspects, post-traumatic stress disorder (PTSD) treatment, and psychodynamic methods) and Acceptance and Commitment Therapy (ACT) (e.g., goal compass, training in ACT principles, and mindfulness);
relaxation techniques; and
physical exercise.
Only 14 of 31 programs reported using interventions in the workplace. All programs reported having follow-ups (1-year follow-up by mail or at the unit for completing the registry’s questionnaires). Usually, extra follow-up meetings were scheduled two to three months after discharge from rehabilitation (21 of 31 units).
The optimal composition of IPRP with respect to length, contacts with therapists, and intensity are insufficiently known according to a systematic review (SR) [19] and a meta-analysis (MA) [20]. The former concluded that because dose variables were not investigated separately in the RCTs, the reviewers could not disentangle the interrelationships between dose, content, and effects of IPRP on disability, work, and quality of life. Similarly, a longitudinal study of IPRP dosage (i.e., duration) could not establish an optimal dosage [21].
Generally, IPRP goals include improving important outcomes (4,5). There are several simultaneous general goals to be considered—decreased pain intensity and increased mental health; increased participation in work/studies and social life; and increased health and quality of life. These general goals are combined with the specific goals of the individual with chronic pain. Thus, goals should ideally be set at the level of the individual, the rehabilitation teams, and the socio-economic constraints. The latter is essential since IRRPs historically have been financial failures. For IRRP to prosper and receive funding, the considerable socio-economic costs of chronic pain need to be considered. Goals, such as return to work/studies and decrease in medication use, health care use, and surgery, will in the long run also benefit the individual move towards an active, independent lifestyle.
As chronic pain is a complex experience with possible adverse effects on function and social and psychological well-being, goal setting should include several aspects and involve a BPS perspective. The general goals for IPRPs are mentioned above. In addition to these goals, there is an increasing emphasis on cognitive areas that could mediate positive changes, such as catastrophizing, acceptance of the pain condition, avoidance of activity due to unrealistic concerns about harm, and expectations of pain treatment [22].
Researchers have debated whether pain intensity aspects should be amongst the main outcomes of pain treatments included in IPRP [23, 24, 25, 26]. Many patients consider reducing pain to be the most important aspect of treatments with respect to regaining a normal lifestyle; however, changing this view is considered an intrinsic component of IPRP. Many chronic pain patients eligible for IPRP have experienced how short-sighted attempts to control only pain intensity can lead to vicious cycles of increased physical and psychological disability and reduced quality of life. Thus, many IPRPs have largely adopted the idea of introducing acceptance as a cornerstone of the psychological component of IPRP (i.e., the willingness to experience pain as it is) and encouraging patients to set up activity-related rehabilitation goals and to risk initial pain flare-ups. This means that patients are advised against establishing pain reduction as the only or the most important goal. Paradoxically, in the long run, pain reduction is one of the more robust results of IPRP [27]. Nevertheless, in traditional CBT, a cornerstone and mainstream in IRPs, an array of strategies is presented, strategies that target the consequences of pain with non-pharmaceutical techniques for pain control.
The process of goal setting is vital and fundamental both for the individual and the team as goal setting has been shown to promote greater behavioural change across a wide range of behaviours [28]. At the individual level, a thorough assessment that is communicated to the patient and a collaborative goal-setting process will increase engagement and adherence to treatment. In addition, the rehabilitation team will benefit from formulating common goals for treatment, reviewing results, and improving plans to stay engaged and to be flexible. The latter should constitute an important goal for the team as role models for patients. Often, the goal is to attain goals that are SMART—i.e., Specified, Measurable, Attractive, Realistic, and Time-limited [29, 30]. However, possibly the most important quality for goals is to be personalised and agreed upon by the patient. The team should strive for a collaborative approach but must always bear in mind that the patient is in a more vulnerable position and might easily give in to goals that might, for example, not feel relevant or feel too demanding. Motivational Interviewing (MI) can be used to discover a patient’s motivation for a specific goal when a patient finds it difficult to specify goals. Patients are often more focused on avoiding unpleasant experiences and frequently the main wish of the patient is to be free of pain. As such, the goal-setting can constitute an acceptance of intervention as it models how to focus on the attainable and let go of the difficult to achieve a goal—i.e., pain relief.
Nevertheless, the SMART model for goal setting has lately been challenged by Acceptance and Commitment Therapy (ACT), the third wave CBT. ACT, which has increasingly been introduced in IRRP, emphasises identifying important values and not primarily setting specified, time-limited goals. However, the SMART model can be used as a step towards identifying important values.
The variety of interventions used at most IPRPs in a single country [18] is in itself a challenge when it comes to measuring the outcomes of IPRPs delivered in clinical settings. Nevertheless, the areas addressed correspond to the areas proposed by the BPS model. In addition to the variety of interventions within IPRPs, many tools have been used both by researchers and clinicians to assess patients and to measure IPRP outcomes. Two well-known initiatives to bring consensus into the areas of evaluating clinical trials, including IPRP are the Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials (IMMPACT) [4, 31] and the validation and application of a patient-relevant core set of outcome domains to assess multimodal PAIN therapy (VAPAIN) initiatives (Table 1) [32].
IMMPACT’s domains | VAPAIN’s domains |
---|---|
Pain | Pain intensity and frequency |
Emotional function | Emotional well-being |
Physical function | Physical activity |
Productivity | |
Satisfaction with social roles and activities | |
Self-evaluation on overall improvement and satisfaction with the intervention | Patient’s perception of achieved treatments goals |
Symptom and side-effects of intervention | |
Participant disposition (including participation and discontinuation of participation) | Reasons for discontinuation of treatment |
Domains of IMMPACT and VAPAIN.
IMMPACT identifies relevant outcome domains for clinical studies and proposes reliable measurement tools for the study of treatments of chronic pain, including all possible modalities and approaches. IMMPACT has resulted in several studies evaluating clinical treatments. VAPAIN specifically targets IPRPs. These initiatives have some overlapping domains that are included in clinical trials (Table 1). VAPAINs focused on IPRPs led to the addition of two domains considered critical when the treatment is interdisciplinary—productivity and patient satisfaction with social roles and activities. VAPAIN renamed certain domains and extended their scope (e.g., the more inclusive ‘emotional well-being’ rather than ‘emotional function’).
A different approach taken by a Canadian research group focuses on the variables of interest for health care providers and the variables of interest for patients, according to lists of parameters from the Patient-Reported Outcomes Measurement Information System (PROMIS), the International Classification of Functioning, Disability and Health (ICF), and current guidelines [33]. Here, the initiative was to identify the set of variables that are important to both providers and patients. They triangulated the ICF and the PROMIS frameworks with the perspectives (both the patients’ and clinicians’ perspectives) and found a common list of ten variables—pain interference, pain intensity, physical function, sleep disturbance, anxiety, depression, ability to participate in social roles and activities, fatigue, sleep-related impairments, and self-efficacy. The authors conclude that these variables mirror the BPS model covering the physical, psychological, and social consequences of chronic pain on an individual’s life both from the perspective of people with chronic pain and the perspective of health care providers.
There is a need to develop clinically applicable, standardised, and accepted ways to evaluate IPRP. IPRP is a complex intervention with several general goals (see above) and is delivered by an interdisciplinary team of professionals in close collaboration with the patient and considering the patient’s specific goals. This is entirely different from a pharmacological intervention, which aims to alter a biochemical process to decrease pain intensity (Figure 1). In fact, an IPRP tries to influence several levels, including the behaviours of the patient with chronic pain. Hence, in clinical practice, there are several outcomes and to make things, even more, complicated the important goals for the individual patients may differ. Due to these circumstances, the concept of one or two primary outcomes and a few secondary outcomes applied in pharmacological randomised controlled trials (RCTs) do not reflect the complexity of IPRP. In a systematic review (SR) by SBU, the included RCTs on average had nine outcome variables and the variables were seldom divided into primary and secondary outcomes [23].
The complexity of IPRP versus a pharmacological intervention.
The evaluation of complex interventions, such as IPRP is not clear-cut [34]. Clinically applicable, standardised, and accepted ways to evaluate the multiple outcomes of IPRP in individual patients clinically and in trials, SRs/meta-analysis (MAs) and observational studies are lacking. If the changes in outcomes are intercorrelated (they often are, see below), it may be problematic to evaluate the outcome measures separately as sometimes is done [35]. In contrast, SBU defined a positive outcome of an RCT when the
Because evaluations of several outcomes often raise an issue of multiple comparisons, Bonferroni corrections may be recommended [42, 43]. This is a conservative approach when the number of tests increases and can reduce the chances to detect real treatment effects [42, 44, 45]. Moreover, such corrections are intended for corrections of
The available SRs and MAs indicate that IPRP is an evidence-based intervention. Table 2 lists and briefly describes the results of available SRs and MAs based on only RCTs according to Dragioti et al.’s [47] search strategy.
First author, year, and reference | Type | Patients | No. of RCTs* | Main results and comments |
---|---|---|---|---|
Nielson 2001 [48] | SR | CP with separate analysis for CLBP, FM, and other | 21 |
|
Guzman 2002 [49] | SR+MA | CLBP | 10 |
|
SBU 2006 [23] | SR | CP with separate analysis for FM | 46 |
|
van Geen 2007 [50] | SR | CLBP | 10 |
|
Scascighini 2008 [37] | SR | CP with separate analyses for CBLP and FM | 36 |
|
Norlund 2009 [51] | SR+MA | CLBP | 7 |
|
Häuser 2009 [52] | SR+MA | FM | 9 |
|
SBU 2010 [36] | SR | CP with separate analyses for CLBP and FM | Partial update of 2006 SBU**
| |
van Middelkoop 2011 [53] | SR+MA | CLBP | 83 |
|
Kamper 2014 [35] | SR+MA | CBLP | 41 |
|
Gianola 2018 [54] | SR+MA | CBLP | 22 | Partial reanalyses of Kamper et al.’s review [35] using minimal important differences units (MIDs). Using this approach, they concluded that IPRP led to improvements in an appreciable number of patients in the short- and medium-term after IPRP. In the long term, IPRP probably had little or no benefit for most patients. |
Casey 2020 [55] | SR+MA | CP | 27 |
|
Martinez-Calderon 2020 [56] | SR+MA | CP | 60 | Investigates the outcome pain self-efficacy.
|
Martinez-Calderon 2020 [57] | SR | CLBP | 61 | Investigates outcomes of fear.
|
Martinez-Calderon 2021 [58] | SR | FM | 12 | Investigates the outcome of pain-related fear.
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Brief conclusions from Systematic Reviews (SR) and Meta-Analyses (MA) of IPRP identified using Dragioti et al.’s search strategy [47].
Not all RCTs may be used for the analyses of IPRP outcomes.
Note that GRADE was used in the 2010 SBU report but not in the 2006 SBU report.
SR = Systematic Review with narrative synthesis of data; MA = Meta-Analysis; RCT = Randomised Controlled Trial; IPRP = Interdisciplinary Pain Rehabilitation; CLBP = chronic low back pain; FM = fibromyalgia; CP = non-specific chronic pain conditions; TAU = treatment as usual; and WLC = waiting list controls.
SRs and MAs using several simultaneous outcomes report positive outcomes for IPRP for chronic pain conditions [23, 35, 36, 37, 48, 49, 52, 53, 55]. Studies using overall assessments of outcomes and therefore considering that IPRP is a complex intervention agree that IPRP has positive outcomes with moderate to strong evidence [23, 36, 37]. There is no consensus regarding the duration of the effects after IPRP (follow-up time) [23, 35, 36, 37, 48, 52, 53, 54, 55]. When outcome variables are evaluated independently, the outcomes associated with positive effects differ across studies [50, 53, 56, 57, 58]. Articles reporting results for fibromyalgia separately reported positive outcomes for IPRP. However, both evidence levels and follow-up periods (short, medium, or long term) differed [23, 36, 37, 52, 58]. The conclusions regarding the effects of IPRP on vocational variables, such as return to work (RTW) and sick leave were heterogenous according to these reviews [23, 35, 36, 48, 49, 50, 51].
The authors of these reviews identify several problems and limitations. Most SRs report that there is heterogeneity in study settings, interventions, and control groups. It is difficult to compare the patient groups included in the identified RCTs since there is no internationally accepted way to describe the patient groups. In addition, the number of comorbidities and duration of sick leave can differ, and external factors, such as the social security situation can differ considerably across studies from different countries and years. Some of the variables suggested by IMMPACT and VAPAIN can be useful for the development of a standardised set of variables that can be used to describe chronic pain patient cohorts [4, 31, 32]. Moreover, because there is no internationally accepted definition of IPRP, authors of SRs and MAs must create their own operational definitions to identify the relevant RCTs. In the quality assessments of RCTs, the issue of blinding might be problematic, and IPRP studies may be classified with lower quality since it is impossible to blind IPRP for patients. Different results in the reviews might also depend on the specific criteria for inclusion and the fact that parts of reviews are based on judgements of researchers.
The results from RCTs, SRs, and MAs must be confirmed in real-life consecutive flow of patients in clinical settings. Direct clinical application of the results from RCTs is not suitable in all situations as these studies might be associated with bias and the patients investigated in RCTs might not represent real-world patients (i.e., insufficient external validity) [59]. Hence, the results from RCTs and SRs must be confirmed in real-life settings, for example, using registry data. This methodology is labelled
Most real-world observational evaluations of IPRP are based on within-group analyses over time. However, such observational studies are often associated with bias. Creating an objection-free control group in clinical practice in association with registries of IPRP is ethically, economically, and practically impossible. To date, attempts using other types of registries for creating a control group have not been successful [61]. Fortunately, methods have been developed that emulate randomisations based on observational data, which allows comparisons between interventions [62]. Target trial emulations are increasingly applied (e.g., in clinical pharmacology, oncology, cardiovascular diseases, critical care, and rheumatology) and can under appropriate circumstances give valid effect estimations compared to RCTs [63, 64]. When target trial emulations can be adequately performed, they generally yield stronger evidence than other types of observational research designs [63]. However, these are not simple methods or without limitations and biases [65, 66, 67]. Although criticised, a first attempt has been made that focuses on sick leave associated with IPRP using data from the SQRP (see below) [68]. If further research and refinements of registries covering IPRP conclude that this methodology is applicable, it would be a great advantage. It would further increase the importance of registries for improving the clinical results of IPRP and other complex interventions for patients with serious chronic pain conditions.
There are usually two approaches to building a registry, and both influence the architecture and content of the registry. Registries are either built to answer research questions or to provide clinical evaluations to providers at each site. SQRP was built primarily around the second approach. The initiative to start SQRP was taken within the professionals’ network, the decision made by the leadership of the units delivering IPRP around 1997. Since its inception, in 1998, the registry has addressed the description of what was being offered at the clinical settings, the overall situation of the patients being admitted, and the changes reported in the included instruments at discharge and 1-year follow-up. Therefore, the SQRP has always worked very closely with the clinicians providing treatment as they are a source of knowledge to be used in the assessment of patients and the evaluation of their progress in the programs as well as describe data at the organization’s level. The general goals are given in Table 3.
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General goals of SQRP.
The registry aims to highlight data on structure, processes, and outcomes. Outcomes are retrieved at the individual, group, unit, and national levels (Table 4).
Type of intervention | |||
Number of registrations | |||
Time | |||
Reasons for discharge | |||
Level of the individual (patient profile and reports) | |||
Level of the unit (group reports) | |||
Level of the country (yearly reports) | |||
R 1 | |||
R 2 | |||
R 3 | |||
R 4 |
Clinical evaluations (levels of analysis).
R = Report.
Every year SQRP follows how the registry is used at the clinical level and promotes plans for improvements. Examples of improvement work, using measures of the registry (according to answers to the 2019 survey) are presented in Table 5.
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Examples of improvement work using measures of the registry.
An overview of the variables and instruments included in the registry (2021) is presented in Table 6. Hence, SQRP is mainly a patient-reported registry, including mostly patient-related outcome measures (PROM data) as well as patient-related evaluation measures (PREM data). The PREM variables concern satisfaction with reception/encounter, the site information, degree of participation in the rehabilitation plan, teamwork, and family participation in the program.
Type | Variables and instruments |
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Self-report and background information | |
Socio-demographic data | |
Work | |
Sick leave | |
Pain duration Pain extent | |
Attitude towards the future | |
Self-report, Instruments, and variables | |
Numeric Rating Pain Scale (NRPS) | |
The Hospital Anxiety and Depression Scale (HAD) | |
Multidimensional Pain Inventory (MPI) | |
Health-related life quality (RAND-36) | |
Perceived health (the EuroQol Group) (EQ-5D) | |
Chronic Pain Acceptance Questionnaire (CPAQ 8) | |
Insomnia Severity Index (ISI) | |
Perceived work ability index (WAI) | |
Kinesiophobia (TAMPA) | |
Perceived physical activity (3 items) | |
Changes in pain experience (retrospective items) | |
Changes in ability to handle life situations (retrospective items) | |
Patient satisfaction (six items) | |
Professional-evaluated variables | |
Diagnosis | |
Pain mechanisms | |
Expected future financial-support form | |
Swedish language ability | |
Rehabilitation plan |
Variables of SQRP.
The registry also includes self-reported background information. There are some variables that are evaluated by the professionals in the program (Table 6).
Some other Swedish quality registries were built to answer research questions and are now working to adapt the output of information to the needs of clinicians at the sites where healthcare is provided. On the other hand, SQRP has been working to improve its operations to allow for research questions to be explored by improving the validity of its information, reducing dropouts, and enhancing routines to avoid missing values and registration errors. In 2011, a national research network (SQRP research group) was formed through initiatives developed by the SQRP’s steering group. This group has developed different research programs focused on the registry, leading to grants from different research funds, dissertations, and many publications. In this way, SQRP is becoming a source of knowledge for researchers interested in finding answers to the complex interventions included and the heterogeneous group receiving treatment.
SQRP collects a large amount of self-reported mandatory data concerning pain aspects, psychological distress, interference, health aspects, etc. together with background data from patients referred to specialist pain care in Sweden. The information covering the BPS framework complements information included in the clinical assessments. To determine which variables are generally important in patients with chronic pain, one approach investigates variables important for health aspects.
Pain severity, pain interference, and pain intensity were the most important regressors of health (N > 37 000 patients at baseline) followed by two variables that focus on control of pain and coping with pain, and four variables (also significant) reflecting mood aspects according to a cross-sectional SQRP study (Figure 2) [69]. Extent and duration of pain, age, gender, and background variables were not significant regressors.
OPLS regression of health (EQ5D-index) using other self-reported variables at baseline as regressors. Only significant variables are shown. Data are from [
Another approach is to use PCA to identify variables associated with prominent variations—i.e., high scores. Pain aspects, such as intensity and interference, psychological distress, coping, and health aspects, are the most important and therefore carry the most information for the clinical presentation according to SQRP studies [70, 71].
It is a clinical experience that patients with the same diagnosis show considerable variations in their presentations and consequences. Therefore, in the context of improving outcomes of interventions, there is a great interest to identify relevant subgroups of chronic pain patients. Most studies have been hypothesis-driven with respect to the input variables for subgrouping. Based on some mandatory variables covering the BPS framework, two subgroups/clusters of patients have been identified from SQRP data (N = 37 100) [70]. The subgroup with the most intense pain intensity/severity had the worst situation regarding psychological distress, interference in daily life, and least life control [70]. Furthermore, according to variables not used as input variables, this subgroup had more pain extent (spreading of pain) and more people born outside Europe. Also, smaller SQRP studies report that the patient group is not homogenous and different subgroups have been identified [71, 72].
The Multidimensional Pain Inventory (MPI) classifies patients into subgroups [73, 74]. These subgroups—Adaptive Coper (AC), Dysfunctional (DYS), and Interpersonally Distressed (ID)—were identified in a large cohort from the SQRP (N = 34 513) and the validity of these subgroups of MPI was partially confirmed [75]. However, in contrast to results reported by Turk and Rudy, the subgroups differed in socio-demographic characteristics, pain duration, and pain extent [73]. Hence, factors other than psychosocial may be important for understanding MPI responses.
In an SQRP sample (N > 38 000), the presence of severe anxiety symptoms was detected in 39.5% and the corresponding outcome for depression was 35.2% according to established cut-offs for the Hospital Anxiety and Depression Scale (HAD) [70]. Although psychological distress was common, the strength of the intercorrelations between pain intensity and anxiety and depression scales of HAD were low. The explained variations (r2) were between 3 and 11%. Two SQRP studies from different times investigated the prevalence of clinical insomnia according to Insomnia Severity Index (ISI) and reported a prevalence between 65 and 66% [76, 77]. Hence, it is important to assess insomnia in patients with complex chronic pain. A network analysis (N = 2 241) reported that psychological variables, such as acceptance and depression mainly were associated with pain interference, whereas the associations with pain intensity and extent together with insomnia were weak [78]. These results taken together may be important for expectations about treatment results (i.e., improvements in psychological distress may not necessarily lead to important improvements in pain intensity).
The pain extent is registered using 36 predetermined anatomical regions in the SQRP, which were summarised and divided into four categories: 1–6 regions with pain (20.6% of patients), 7–12 regions (26.8%), 13–18 regions (22.0%), and 19–36 regions (30.6%) (N = 39 916) [79]. A higher extent of pain spreading was associated with a more severe clinical picture at baseline and longer pain duration with the strongest associations emerging in relation to health and pain aspects (pain intensity, pain interference, and pain duration) [79]; generally, there were at least medium effects sizes (ESs) when comparing the two extreme groups. A cross-sectional multivariate analysis found that pain spreading correlated strongest with general health, vitality, female gender, physical function, pain interference, pain intensity aspects, and pain duration [79].
Patients with chronic pain generally have a higher Body Mass Index (BMI) than healthy controls. Obese patients had a worse pain profile (e.g., pain intensity, pain extent, and pain duration) and more depressive and insomnia symptoms than normal-weight patients according to another SQRP study (N = 3 310) [80].
Most patients referred to the specialist departments in Sweden are women (about 70%). The reasons for this overrepresentation are unclear and are only partially explained by the higher chronic pain prevalence in the population [81, 82]. It is unclear whether sex/gender differences for pain severity exist [83, 84, 85]. According to SQRP data, there were generally small differences (generally insignificant ESs) in clinical presentation according to self-reported data between the two genders [86, 87]. Generally, patients born outside Europe had a more severe clinical picture than those born in Europe, for example, with respect to pain intensity and psychological distress (medium ESs) [87]. Patients with only an elementary school education generally reported a worse clinical situation than those with a university education (most variables small to medium ESs).
A cluster analysis using gender, country of birth (Europe vs. outside Europe), and education level (three categories) as input variables identified five subgroups—three subgroups of European women and different education levels, one subgroup of European men, and one subgroup of non-European men and women and different education levels [87]. Prominent differences in clinical presentations, such as pain intensity, psychological distress, interference, life control, and health aspects, were noted between European women with university education and the non-European subgroup (worst situation) (ESs generally medium to large). European women with only elementary school also displayed a worse situation than those with university education.
To summarise, patient groups referred to specialist pain care in Sweden are not homogenous with respect to clinical presentations as distinct subgroups are evident. The clinical presentations show clear associations with pain extent, BMI, and socio-demographic variables.
Not all patients assessed and registered at baseline in SQRP are selected or choose to participate in IPRP. Unfortunately, the registry does not contain data that can separate these two reasons and other possible reasons, nor does it collect detailed information about assessments, all interventions offered (including IPRP), the interventions’ contents and dosages, and patient-related preferences and choices. Assessments of patients, including establishing treatment plans, are clinically necessary and perceived as important by patients. The assessment including a treatment plan with follow-up in primary care per se appears to be associated with positive significant effects on several aspects of the clinical presentation [88]. However, the ESs were insignificant to small.
The Swedish guidelines recommend that IPRP at the specialist level is offered to chronic pain patients with complex clinical presentations, for example, with respect to comorbidities [10]. However, the subgroup with the most severe clinical situation was somewhat underrepresented [70, 89]. Similar results were found for the DYS subgroup of MPI, male gender, and the non-European subgroup [75, 87]. In agreement with this SQRP, data from two university hospital departments showed negative correlations between participation/selection and pain intensity but positive correlations with pain extent [90]. The reasons for these selections are currently unclear and further research is needed.
IPRP in clinical settings is associated with improvements on the group level with small to medium effect sizes for the majority of the mandatory self-reported outcome variables, for an overall score and retrospective items. Sick-leave data retrieved from the Swedish Social Insurance Agency database show important decreases after IPRP.
The outcomes of IPRP were investigated in a study of more than 14 000 patients (Table 7) [27]. Significant improvements were generally found except for one or two of the three scales of the second part of MPI (how husband/wife reacts when a patient has pain). Most outcomes showed small ESs and some outcomes were associated with moderate ESs (Table 2). For the pre vs. post-IPRP comparisons, three variables had moderate effects sizes—two pain intensity variables and vitality (Table 7). At the 12-month follow-up, the same pain intensity variables were associated with moderate effect sizes; this was also the case for pain interference and a health aspect (Table 6). The variables of the second part of MPI had insignificant ESs both post IPRP and at the 12-month follow-up.
Pre vs. post-IPRP | Pre vs. FU | |||||||||||
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Pre | Post IPRP | Pre | FU | |||||||||
Outcome variables | Mean | SD | Mean | SD | ES | Mean | SD | Mean | SD | P-value | ES | |
NRS-7days | 6.86 | 1.72 | 5.95 | 2.09 | <0.001 | 0.45 | 6.84 | 1.72 | 5.78 | 2.32 | <0.001 | 0.47 |
HADS-Anxiety | 9.00 | 4.76 | 7.78 | 4.55 | <0.001 | 0.32 | 8.73 | 4.69 | 7.38 | 4.70 | <0.001 | 0.33 |
HADS-Depression | 8.49 | 4.44 | 6.70 | 4.31 | <0.001 | 0.47 | 8.18 | 4.37 | 6.74 | 4.66 | <0.001 | 0.35 |
MPI-Pain-severity | 4.39 | 0.93 | 3.87 | 1.16 | <0.001 | 4.36 | 0.91 | 3.71 | 1.33 | <0.001 | ||
MPI-Pain-interference | 4.38 | 1.02 | 3.94 | 1.19 | <0.001 | 0.49 | 4.34 | 1.02 | 3.73 | 1.37 | <0.001 | |
MPI-Life Control | 2.72 | 1.10 | 3.30 | 1.18 | <0.001 | 0.47 | 2.77 | 1.10 | 3.28 | 1.27 | <0.001 | 0.40 |
MPI-Distress | 3.46 | 1.26 | 2.89 | 1.38 | <0.001 | 0.42 | 3.42 | 1.27 | 2.92 | 1.45 | <0.001 | 0.35 |
MPI-Social support | 4.16 | 1.34 | 3.95 | 1.35 | <0.001 | 0.21 | 4.17 | 1.33 | 3.77 | 1.42 | <0.001 | 0.35 |
MPI-punish | 1.74 | 1.36 | 1.72 | 1.33 | 0.037 | 0.02 | 1.69 | 1.34 | 1.69 | 1.35 | 0.676 | 0.01 |
MPI-protect | 2.98 | 1.40 | 2.85 | 1.38 | <0.001 | 0.12 | 2.96 | 1.39 | 2.78 | 1.40 | <0.001 | 0.16 |
MPI-distract | 2.54 | 1.19 | 2.56 | 1.17 | 0.043 | 0.02 | 2.52 | 1.17 | 2.45 | 1.17 | <0.001 | 0.06 |
MPI-General activity index | 2.44 | 0.84 | 2.63 | 0.82 | <0.001 | 0.26 | 2.47 | 0.83 | 2.64 | 0.86 | <0.001 | 0.20 |
EQ-5D-index | 0.26 | 0.31 | 0.39 | 0.33 | <0.001 | 0.40 | 0.27 | 0.31 | 0.44 | 0.34 | <0.001 | |
EQ-VAS | 41.22 | 19.09 | 50.99 | 21.38 | <0.001 | 0.44 | 41.90 | 19.29 | 52.96 | 22.87 | <0.001 | 0.46 |
sf36-pf | 52.76 | 20.58 | 57.67 | 21.17 | <0.001 | 0.30 | 53.07 | 20.30 | 59.73 | 22.57 | <0.001 | 0.36 |
sf36-rp | 12.53 | 24.40 | 22.46 | 33.12 | <0.001 | 0.30 | 13.07 | 24.91 | 27.74 | 36.32 | <0.001 | 0.39 |
sf36-bp | 24.36 | 14.49 | 32.96 | 17.41 | <0.001 | 24.60 | 14.11 | 35.41 | 20.05 | <0.001 | ||
sf36-gh | 41.70 | 20.22 | 46.69 | 21.88 | <0.001 | 0.29 | 42.59 | 20.49 | 47.35 | 23.52 | <0.001 | 0.25 |
sf36-vt | 23.95 | 18.48 | 35.67 | 22.76 | <0.001 | 24.96 | 18.79 | 34.41 | 23.85 | <0.001 | 0.41 | |
sf36-sf | 47.29 | 25.19 | 54.93 | 25.91 | <0.001 | 0.30 | 48.95 | 25.50 | 57.66 | 27.05 | <0.001 | 0.32 |
sf36-re | 42.77 | 42.92 | 51.15 | 43.48 | <0.001 | 0.18 | 44.69 | 43.17 | 55.60 | 43.53 | <0.001 | 0.22 |
sf36-mh | 55.03 | 21.35 | 62.55 | 21.55 | <0.001 | 0.38 | 56.34 | 21.15 | 62.70 | 22.53 | <0.001 | 0.30 |
Mandatory outcome variables at baseline (pre) and immediately after IPRP (post IPRP) (left part; N = 12 999–14 772) and at baseline and at 12-month follow-up (FU) (right part; N = 7 784–8 904). Statistical comparisons are presented with effects sizes (ES, i.e., Cohen’s d). Effect sizes in bold were moderate, i.e., Cohen’s d ≥ 0.50. These data have been reported in Ringqvist et al. [27].
The effect sizes >0.50 are given in bold. The significance (p-values) are reported in the columns to the left of the columns concerning effect sizes. NRS-7days = Pain intensity as measured by a numeric rating scale for the previous 7 days; HADS = Hospital Anxiety and Depression Scale; MPI = Multidimensional Pain Inventory; EQ-5D-index = The index of the European quality of life instrument; EQ-VAS = The European quality of life instrument thermometer-like scale; sf36 = The Short Form (36) Health Survey; subscales; pf = physical functioning; rp = role limitations due to pf physical functioning; bp = bodily pain; gh = general health; vt = vitality; sf = social functioning; re = role limitations due to emotional problems; and mh = mental health.
In 2008, the Swedish government introduced a rehabilitation guarantee to enhance, for example, the implementation of IPRP in primary care. The SQRP created a module to collect data from IPRP in primary care. A relatively small study (N = 397) of the clinical presentation of the patients treated at this care level found that patients presented a considerable complexity [91]. A small study (N = 234) evaluated the outcomes of IPRP in primary care 1 year after discharge for 10 of the 11 variables selected. Eleven outcomes reflecting a BPS approach were evaluated 1 year after IPRP and 10 of these showed significant improvements although ESs were small (0.20–0.49) [92]. A cost-utility analysis indicated that IPRP in primary care was cost-effective [93].
The intercorrelations of changes in the 22 mandatory outcome variables (cf. Table 7) were investigated using PCAs [27]. Two groups of variables (components), which were not correlated, were identified; the first showed significant intercorrelations between changes in 18 of the outcomes and the second mainly reflected the changes in the second part of MPI together with changes in social support of MPI. Using the score of the first component, a Multivariate Improvement Score (MIS) was defined reflecting changes in the 18 variables [27]. A cluster analysis of MIS was made, and three clusters were identified; retrospectively their baseline situation was analysed. Cluster 1—overall the worst situation pre IPRP—showed the most positive improvements in MIS. Cluster 3—no changes or deterioration in MIS—had the best situation at baseline. Cluster 2 was an intermediary group at baseline and was associated with overall slightly positive MIS improvements [27].
Both post-IPRP and at 12-month follow-up patients retrospectively estimate the degree of positive change in pain and in their ability to handle life situations in general (both rated on five-point Likert scales from markedly increased pain/markedly worsened life situation (score 0) to markedly decreased pain/markedly improved (score 4) [27]. At both time points, most patients reported that their pain situation (57% at both time points), as well as their ability to handle their life situation, had improved (84 and 77%); the two most positive alternatives were added [27].
All patients undergoing IPRP registered in SQRP between 2007 and 2011 (n=7 297) were linked to the Swedish Social Insurance Agency database and the development of sick leave was analysed [94]. Sick-leave benefits increased during the year before IPRP and decreased after IPRP (analysed up to 2 years after) (Figure 3). These reductions in benefits were significant for both men and women. It was concluded that IPRP could positively influence sick-leave benefits for these patients regardless of their sick-leave situation, sex/gender, or policy changes.
Level of sick leave at 90–0 days before (T1) IPRP, 320–410 days after (T2) IPRP, and 775–985 days after (T3) IPRP; N = 7 297 (Rivano Fischer et al. [
A larger study of sick absence for patients included in SQRP (N = 44 241) showed similar results—i.e., sick absence increased from 17% 5 years before to 48% at assessment at the specialist department and thereafter decreased to 38% [95]. Sickness absence history was the strongest predictor of future sickness. Decreases in pain intensity/severity and pain interference but not increases in life control and social support or reduced affective stress during IPRP were associated with decreased risk of being on full-time sick leave 1 year later according to another SQRP study (N = 1 468) from a university department [96]. The same authors reported from a cohort of 2 784 patients that the subgroup DYS of MPI decreased after IPRP [97]. Those belonging to AC or ID had less full-time sick leave 1 year later and therefore the DYS profile was associated with long-term sick leave.
Decreases in sick leave after IPRP were reported in a target trial emulation study using SQRP data (N = 25 613) [68], but the results were not significantly better than for the comparison group. The article was the first target trial emulation attempt using SQRP data (see above). This study has been criticised for its heterogenous comparator group and lack of data concerning other interventions and patient preferences [98]. In addition, this critique emphasised that very complex processes may exist after the assessment when preparing and establishing the rehabilitation/treatment plan. Hence, registries such as SQRP need to collect detailed data concerning assessments, all interventions offered (including contents and dosages), as well as patient-related preferences. More details about the clinical departments might also be beneficial [18]. Perhaps one might expect more prominent decreases of sick leave in IPRP than in the comparison group. According to Swedish guidelines, IPRP should be offered to the most complex chronic pain patients, but those participating in IPRP had gross sick leave days the year before IPRP, so that is necessarily not a correct expectation.
Long-term opioid therapy (LTOT) for chronic pain is unfortunately common in clinical practise despite lack of evidence and serious adverse consequences [99, 100, 101, 102, 103]. At a university hospital reporting to SQRP, 30% of the patients referred to a clinical department used opioids daily [104]. These patients had higher pain intensity, more pain interference, lower quality of life, lower activity engagement, and less satisfaction with life than the other patients referred (medium ESs) [104]. Svanberg et al. investigated the opioid prescriptions 2 years after chronic pain patients were assessed for IPRP [105]. Opioid prescriptions were prescribed for 55% of the cohort (N = 1334). The odds of receiving LTOT were similar for those participating and not participating in IPRP. Patient characteristics at baseline/assessment in both these groups could predict LTOT. In those participating in IPRP, dysfunctional pain coping was a predictor; however, in those not participating in IPRP, pain intensity and depressive symptoms were predictors. Taken together, these studies indicate that long-term pharmacological treatment is not optimal for patients who are eligible for IPRP.
Evidence is contradictory when it comes to clinical presentation pre-treatment. A recent meta-analysis on prognostic factors for IPRP outcome demonstrated that both higher levels of general emotional distress and pain-specific cognitive behavioural factors were related to worse long-term (>6 months) physical functioning post-treatment [106]. However, a similar pattern was not displayed in two large-scale SQRP cohort studies where patients reporting higher levels of perceived disability and suffering displayed slightly greater improvement [27, 70]. Hence, those with the most severe clinical presentations at baseline will display the largest improvements found in SQRP studies [70, 71, 75].
Pain distribution (i.e., spreading of pain) is another factor that needs consideration. Cross-sectional population studies have reported that spreading of pain is significantly associated with pain intensity, depressive disorders, and poor health [107, 108]. In a recent large-scale SQRP cohort study, spreading of pain was associated with poorer outcomes of treatment, but the effects were in the small range [79]. Thus, spreading of pain is important for understanding chronic pain as an indicator of severity, as previously described, and to some extent as a predictor of the poorer outcome of IPRPs.
Psychosocial coping profiles with three subgroups have been derived from the MPI and are commonly used to aid in the assessment of patients with chronic pain. Based on a BPS approach to chronic pain, MPI and its subscales are sensitive to changes in the severity of chronic pain and predict sick leave. The dysfunctional (DYS) subgroup reports high pain severity, marked interference in daily life, high affective distress, low perception of life control, and low levels of activity. The adaptive coper (AC) subgroup is characterised by less severe pain, less interference with activities, less affective distress, and positive perceptions of life control and activity level. The interpersonally distressed (ID) subgroup has been described as perceiving low social support and non-supporting behaviours from significant others [109, 110, 111]. Some reports suggest that the DYS and/or ID subgroups have better treatment outcomes than the AC group [109, 112, 113, 114, 115, 116], whereas other studies have found no significant differences in outcomes amongst subgroups [110, 111, 117, 118, 119, 120, 121]. These results are supported by a large-scale cohort study from the SQRP: DYS and ID subgroups that had the most severe clinical presentation at baseline showed the largest improvement following IPRP [75].
The existing literature regarding sex differences in outcomes of IPRP is conflicting—women benefit more [84, 122, 123], no sex differences [124, 125, 126], and men benefit more [127, 128]. The outcomes of IPRPs in a primary care study were better in women than in men [92]. A recent large-scale cohort study from SQRP found sex differences in outcomes—women had slightly better results than men [87]. The conflicting results in the literature may be due to different cohorts investigated as well as the choice of outcomes.
An important principle in healthcare is equity (i.e., prioritization of healthcare based on the need of the patient); however, social contexts are seldom considered in studies [129]. Several studies have reported that prevalence of chronic pain, the severity of pain, and disability are inversely related to the socio-economic position and low education, male sex, and/or non-European origin (in European studies), which appear to be associated with lower participation rates and worse IPRP results [129, 130, 131, 132].
One-fifth of the European adult population lives with at least
As described in previous passages, results from IPRP demonstrate low to moderate effect sizes on outcomes with conflicting results concerning effects on RTW. Possible gains for the individual and society might be accomplished with improvements of routines and contents of IPRP. It is thus problematic that IPRP is somewhat heterogenous as this can constitute problems establishing strategies for improvements. As a comparison,
The results obtained by the SQRP show that the subgroup of patients with a relatively better clinical picture before IPRP had worse IPRP results than those with a more severe clinical picture [70]. The patient group with the more difficult clinical picture is most improved by IPRP but not so much that they reach the subgroup with a better clinical picture. Both circumstances indicate a need for the development of IPRP so that IPRP better matches the clinical picture. For example, individual treatments, short interventions, small group activities with different content to be selected for individual patients, individual treatments with the team as a backup, and closer communication with primary care to ensure that recommendations can improve the lives of patients without going through extensive IPRPs, which might be more appropriate for the less severe subgroups [15]. In the long run, this could mean that different IPRPs are available in clinical settings. In addition, the activated, mainly unknown, neurobiological pain mechanisms might not be sufficiently targeted by the various interventions in IPRP.
Early interventions might also improve results. The association between prominent pain extent (i.e., widespread pain) and pain duration supports the concept of early intervention as clinically important and an opportunity to possibly change prognosis with conceivable gains for the individual and society. Early interventions with psychological risk factor screening combined with protocols for active collaboration between caregivers and key stakeholders have been demonstrated to positively impact return to work [136].
Poorer results of IPRP in socially more challenged populations might suggest that equal care is not delivered. For example, IPRP in Sweden may not meet the needs of patients outside Europe. It has been suggested that in particularly non-Western backgrounds might be associated with other attitudes towards self-management interventions, passive symptom-focused management strategies, as well as pharmacological treatments [137], which could influence IPRP outcomes. Selection to participation in IPRP and outcomes might also be disadvantaged by different biases of professionals towards non-European patients and/or insufficient knowledge about immigration and other cultures. Lower socio-economic groups may differ from health professionals in culture, beliefs, and communication style, resulting in disadvantages and possibly feelings of inferiority. Carr and Moffet provocatively suggest that CBT interventions designed by middle-class health professionals are more suitable for middle-class patients [130]. Also, a common goal of IPRP is increased physical functioning; however, exercise and sports activities are less likely to be adopted by people in lower socio-economic groups than by people in higher socio-economic groups [138, 139, 140].
This raises important questions concerning fairness and equality. The combination of sex, education, and country of birth needs to be considered in the assessment of chronic pain patients and is important to consider when optimising the content and delivery of IPRP in clinical practice. IPRPs need to be adapted and educational elements fitted to meet different learning styles using techniques to increase retention of new information as described in textbooks, such as ‘Explain pain supercharged’ [141]. In addition, Carr and Moffet suggest that a useful starting point when considering how to improve treatments is the knowledge that people in socially-deprived areas endure higher levels of stress and lower perceived control [130]. Techniques are suggested to reduce stress and learned helplessness and include involving patients in shared decision-making of treatment, increased social support, incorporating individual coaching where the individual can learn to take more control, and additional validation where IPRPs are supplemented by phone calls between sessions. When attendance is challenged, audio and video material could be provided for patients unable to attend.
The patient group with chronic/persistent pain conditions referred to specialist care in Sweden are heterogenous and different subgroups exist. The clinical presentations show clear associations with the extent of pain spreading, BMI, and socio-demographic variables. IPRP is an evidence-based intervention for chronic pain patients who suffer from substantial consequences of their chronic pain condition regarding function, social, and/or psychological well-being. The intervention is complex and is delivered by an interdisciplinary team of professionals in close collaboration with the patient. Observational analyses of IPRP in clinical settings agree with the evidence presented in SRs and MAs. However, results differ amongst subgroups and benefits are not present for all patients. Interestingly, those with the most severe clinical presentation, according to registry data, an assessment benefit most from IPRP. Also, socio-economic factors can influence results and need to be addressed to warrant more equal opportunities for improvement in IPRP.
Units offering IPRPs differ in their strategies, services, and resources, both in intensity and duration, as well as in the degree of individual interventions opposed to group treatment. This diversity should be addressed by researchers and incorporated in studies by looking into the impact of referral flow, traditions, and the heterogeneity of the patients assessed. Methods other than randomised studies, such as emulated trials, repeated measured for patients (patients as controls) should be refined to enhance the potential gaining of analysing real-life information in registries.
There is thus room for enhancement of IPRP possibly by a more structured use of registries. Furthermore, pain registries should expand to cover a variety of clinical efforts designed to meet the individual needs of people with chronic pain and to deliver information about the effectiveness of these measures.
The authors declare no conflict of interest.
"Open access contributes to scientific excellence and integrity. It opens up research results to wider analysis. It allows research results to be reused for new discoveries. And it enables the multi-disciplinary research that is needed to solve global 21st century problems. Open access connects science with society. It allows the public to engage with research. To go behind the headlines. And look at the scientific evidence. And it enables policy makers to draw on innovative solutions to societal challenges".
\n\nCarlos Moedas, the European Commissioner for Research Science and Innovation at the STM Annual Frankfurt Conference, October 2016.
",metaTitle:"About Open Access",metaDescription:"Open access contributes to scientific excellence and integrity. It opens up research results to wider analysis. It allows research results to be reused for new discoveries. And it enables the multi-disciplinary research that is needed to solve global 21st century problems. Open access connects science with society. It allows the public to engage with research. To go behind the headlines. And look at the scientific evidence. And it enables policy makers to draw on innovative solutions to societal challenges.\n\nCarlos Moedas, the European Commissioner for Research Science and Innovation at the STM Annual Frankfurt Conference, October 2016.",metaKeywords:null,canonicalURL:"about-open-access",contentRaw:'[{"type":"htmlEditorComponent","content":"The Open Access publishing movement started in the early 2000s when academic leaders from around the world participated in the formation of the Budapest Initiative. They developed recommendations for an Open Access publishing process, “which has worked for the past decade to provide the public with unrestricted, free access to scholarly research—much of which is publicly funded. Making the research publicly available to everyone—free of charge and without most copyright and licensing restrictions—will accelerate scientific research efforts and allow authors to reach a larger number of readers” (reference: http://www.budapestopenaccessinitiative.org)
\\n\\nIntechOpen’s co-founders, both scientists themselves, created the company while undertaking research in robotics at Vienna University. Their goal was to spread research freely “for scientists, by scientists’ to the rest of the world via the Open Access publishing model. The company soon became a signatory of the Budapest Initiative, which currently has more than 1000 supporting organizations worldwide, ranging from universities to funders.
\\n\\nAt IntechOpen today, we are still as committed to working with organizations and people who care about scientific discovery, to putting the academic needs of the scientific community first, and to providing an Open Access environment where scientists can maximize their contribution to scientific advancement. By opening up access to the world’s scientific research articles and book chapters, we aim to facilitate greater opportunity for collaboration, scientific discovery and progress. We subscribe wholeheartedly to the Open Access definition:
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The Open Access publishing movement started in the early 2000s when academic leaders from around the world participated in the formation of the Budapest Initiative. They developed recommendations for an Open Access publishing process, “which has worked for the past decade to provide the public with unrestricted, free access to scholarly research—much of which is publicly funded. Making the research publicly available to everyone—free of charge and without most copyright and licensing restrictions—will accelerate scientific research efforts and allow authors to reach a larger number of readers” (reference: http://www.budapestopenaccessinitiative.org)
\n\nIntechOpen’s co-founders, both scientists themselves, created the company while undertaking research in robotics at Vienna University. Their goal was to spread research freely “for scientists, by scientists’ to the rest of the world via the Open Access publishing model. The company soon became a signatory of the Budapest Initiative, which currently has more than 1000 supporting organizations worldwide, ranging from universities to funders.
\n\nAt IntechOpen today, we are still as committed to working with organizations and people who care about scientific discovery, to putting the academic needs of the scientific community first, and to providing an Open Access environment where scientists can maximize their contribution to scientific advancement. By opening up access to the world’s scientific research articles and book chapters, we aim to facilitate greater opportunity for collaboration, scientific discovery and progress. We subscribe wholeheartedly to the Open Access definition:
\n\n“By “open access” to [peer-reviewed research literature], we mean its free availability on the public internet, permitting any users to read, download, copy, distribute, print, search, or link to the full texts of these articles, crawl them for indexing, pass them as data to software, or use them for any other lawful purpose, without financial, legal, or technical barriers other than those inseparable from gaining access to the internet itself. The only constraint on reproduction and distribution, and the only role for copyright in this domain, should be to give authors control over the integrity of their work and the right to be properly acknowledged and cited” (reference: http://www.budapestopenaccessinitiative.org)
\n\nOAI-PMH
\n\nAs a firm believer in the wider dissemination of knowledge, IntechOpen supports the Open Access Initiative Protocol for Metadata Harvesting (OAI-PMH Version 2.0). Read more
\n\nLicense
\n\nBook chapters published in edited volumes are distributed under the Creative Commons Attribution 3.0 Unported License (CC BY 3.0). IntechOpen upholds a very flexible Copyright Policy. There is no copyright transfer to the publisher and Authors retain exclusive copyright to their work. All Monographs/Compacts are distributed under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0). Read more
\n\nPeer Review Policies
\n\nAll scientific works are Peer Reviewed prior to publishing. Read more
\n\nOA Publishing Fees
\n\nThe Open Access publishing model employed by IntechOpen eliminates subscription charges and pay-per-view fees, enabling readers to access research at no cost. In order to sustain operations and keep our publications freely accessible we levy an Open Access Publishing Fee for manuscripts, which helps us cover the costs of editorial work and the production of books. Read more
\n\nDigital Archiving Policy
\n\nIntechOpen is committed to ensuring the long-term preservation and the availability of all scholarly research we publish. We employ a variety of means to enable us to deliver on our commitments to the scientific community. Apart from preservation by the Croatian National Library (for publications prior to April 18, 2018) and the British Library (for publications after April 18, 2018), our entire catalogue is preserved in the CLOCKSS archive.
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\n\nWe aim at improving the quality and availability of scholarly communication by promoting and practicing:
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Other positions she has held at the university include Vice-Dean of Master Programs, Vice-Dean of the Degree in Biology and Vice-Dean for Mobility and Enterprise and Engagement at the Faculty of Science (University of Alicante). She received her Bachelor in Biology in 1998 (University of Alicante) and her PhD in 2003 (Biochemistry, University of Alicante). She undertook post-doctoral research at the University of East Anglia (Norwich, U.K. 2004-2005; 2007-2008).\nHer multidisciplinary research focuses on investigating archaea and their potential applications in biotechnology. She has an H-index of 21. She has authored one patent and has published more than 70 indexed papers and around 60 book chapters.\nShe has contributed to more than 150 national and international meetings during the last 15 years. Her research interests include archaea metabolism, enzymes purification and characterization, gene regulation, carotenoids and bioplastics production, antioxidant\ncompounds, waste water treatments, and brines bioremediation.\nRosa María’s other roles include editorial board member for several journals related\nto biochemistry, reviewer for more than 60 journals (biochemistry, molecular biology, biotechnology, chemistry and microbiology) and president of several organizing committees in international meetings related to the N-cycle or respiratory processes.",institutionString:null,institution:{name:"University of Alicante",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"15",title:"Chemical Biology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/15.jpg",isOpenForSubmission:!0,editor:{id:"441442",title:"Dr.",name:"Şükrü",middleName:null,surname:"Beydemir",slug:"sukru-beydemir",fullName:"Şükrü Beydemir",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003GsUoIQAV/Profile_Picture_1634557147521",biography:"Dr. Şükrü Beydemir obtained a BSc in Chemistry in 1995 from Yüzüncü Yıl University, MSc in Biochemistry in 1998, and PhD in Biochemistry in 2002 from Atatürk University, Turkey. He performed post-doctoral studies at Max-Planck Institute, Germany, and University of Florence, Italy in addition to making several scientific visits abroad. He currently works as a Full Professor of Biochemistry in the Faculty of Pharmacy, Anadolu University, Turkey. Dr. Beydemir has published over a hundred scientific papers spanning protein biochemistry, enzymology and medicinal chemistry, reviews, book chapters and presented several conferences to scientists worldwide. He has received numerous publication awards from various international scientific councils. He serves in the Editorial Board of several international journals. 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He is a member of the Turkish Biochemical Society, American Chemical Society, and German Genetics society. Dr. Ekinci published around ninety scientific papers, reviews and book chapters, and presented several conferences to scientists. He has received numerous publication awards from several scientific councils. 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He worked on the structure-function relationships of glycoconjugates and his main project was the investigations on the biological roles of the de-N-glycosylation enzymes (Endo-N-acetyl-β-D-glucosaminidase and peptide-N4-(N-acetyl-β-glucosaminyl) asparagine amidase). From 2002 he contributes to the understanding of the Blood-brain barrier functioning using proteomics approaches. He has published more than 70 papers. 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Since then, he has been working as an Adjunct Professor in the same Department at the University of Pavia. His research activity during the first years was primarily focused on the purification and structural characterization of enzymes from animal and plant sources. During this period, Prof. Iadarola familiarized himself with the conventional techniques used in column chromatography, spectrophotometry, manual Edman degradation, and electrophoresis). Since 1995, he has been working on: i) the determination in biological fluids (serum, urine, bronchoalveolar lavage, sputum) of proteolytic activities involved in the degradation processes of connective tissue matrix, and ii) on the identification of biological markers of lung diseases. In this context, he has developed and validated new methodologies (e.g., Capillary Electrophoresis coupled to Laser-Induced Fluorescence, CE-LIF) whose application enabled him to determine both the amounts of biochemical markers (Desmosines) in urine/serum of patients affected by Chronic Obstructive Pulmonary Disease (COPD) and the activity of proteolytic enzymes (Human Neutrophil Elastase, Cathepsin G, Pseudomonas aeruginosa elastase) in sputa of these patients. More recently, Prof. Iadarola was involved in developing techniques such as two-dimensional electrophoresis coupled to liquid chromatography/mass spectrometry (2DE-LC/MS) for the proteomic analysis of biological fluids aimed at the identification of potential biomarkers of different lung diseases. He is the author of about 150 publications (According to Scopus: H-Index: 23; Total citations: 1568- According to WOS: H-Index: 20; Total Citations: 1296) of peer-reviewed international journals. 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She gained considerable experience in developing and validating new methodologies whose applications allowed her to determine both the amount of biomarkers (Desmosine and Isodesmosine) in the urine of patients affected by COPD, and the activity of proteolytic enzymes (HNE, Cathepsin G, Pseudomonas aeruginosa elastase) in the sputa of these patients. Simona Viglio was also involved in research dealing with the supplementation of amino acids in patients with brain injury and chronic heart failure. She is presently engaged in the development of 2-DE and LC-MS techniques for the study of proteomics in biological fluids. The aim of this research is the identification of potential biomarkers of lung diseases. She is an author of about 90 publications (According to Scopus: H-Index: 23; According to WOS: H-Index: 20) on peer-reviewed journals, a member of the “Società Italiana di Biochimica e Biologia Molecolare,“ and a Consultant Reviewer for International Journal of Molecular Science, Journal of Chromatography A, COPD, Plos ONE and Nutritional Neuroscience.",institutionString:null,institution:{name:"University of Pavia",institutionURL:null,country:{name:"Italy"}}},editorThree:null}]},overviewPageOFChapters:{paginationCount:42,paginationItems:[{id:"82914",title:"Glance on the Critical Role of IL-23 Receptor Gene Variations in Inflammation-Induced Carcinogenesis",doi:"10.5772/intechopen.105049",signatures:"Mohammed El-Gedamy",slug:"glance-on-the-critical-role-of-il-23-receptor-gene-variations-in-inflammation-induced-carcinogenesis",totalDownloads:15,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Chemokines Updates",coverURL:"https://cdn.intechopen.com/books/images_new/11672.jpg",subseries:{id:"18",title:"Proteomics"}}},{id:"82875",title:"Lipidomics as a Tool in the Diagnosis and Clinical Therapy",doi:"10.5772/intechopen.105857",signatures:"María Elizbeth Alvarez Sánchez, Erick Nolasco Ontiveros, Rodrigo Arreola, Adriana Montserrat Espinosa González, Ana María García Bores, Roberto Eduardo López Urrutia, Ignacio Peñalosa Castro, María del Socorro Sánchez Correa and Edgar Antonio Estrella Parra",slug:"lipidomics-as-a-tool-in-the-diagnosis-and-clinical-therapy",totalDownloads:7,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Fatty Acids - Recent Advances",coverURL:"https://cdn.intechopen.com/books/images_new/11669.jpg",subseries:{id:"17",title:"Metabolism"}}},{id:"82440",title:"Lipid Metabolism and Associated Molecular Signaling Events in Autoimmune Disease",doi:"10.5772/intechopen.105746",signatures:"Mohan Vanditha, Sonu Das and Mathew John",slug:"lipid-metabolism-and-associated-molecular-signaling-events-in-autoimmune-disease",totalDownloads:17,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Fatty Acids - Recent Advances",coverURL:"https://cdn.intechopen.com/books/images_new/11669.jpg",subseries:{id:"17",title:"Metabolism"}}},{id:"82483",title:"Oxidative Stress in Cardiovascular Diseases",doi:"10.5772/intechopen.105891",signatures:"Laura Mourino-Alvarez, Tamara Sastre-Oliva, Nerea Corbacho-Alonso and Maria G. 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He has an excellent track record in the herpesvirus field, and his group is engaged in clinical research in the field of Epstein-Barr virus diseases. He is the editor of the online Encyclopedia of Environment and he coordinates the Universal Health Coverage education program for the BioHealth Computing Schools of the European Institute of Science.",institutionString:null,institution:{name:"Grenoble Alpes University",country:{name:"France"}}},{id:"131400",title:"Prof.",name:"Alfonso J.",middleName:null,surname:"Rodriguez-Morales",slug:"alfonso-j.-rodriguez-morales",fullName:"Alfonso J. Rodriguez-Morales",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/131400/images/system/131400.png",biography:"Dr. Rodriguez-Morales is an expert in tropical and emerging diseases, particularly zoonotic and vector-borne diseases (especially arboviral diseases). He is the president of the Travel Medicine Committee of the Pan-American Infectious Diseases Association (API), as well as the president of the Colombian Association of Infectious Diseases (ACIN). He is a member of the Committee on Tropical Medicine, Zoonoses, and Travel Medicine of ACIN. He is a vice-president of the Latin American Society for Travel Medicine (SLAMVI) and a Member of the Council of the International Society for Infectious Diseases (ISID). Since 2014, he has been recognized as a Senior Researcher, at the Ministry of Science of Colombia. He is a professor at the Faculty of Medicine of the Fundacion Universitaria Autonoma de las Americas, in Pereira, Risaralda, Colombia. He is an External Professor, Master in Research on Tropical Medicine and International Health, Universitat de Barcelona, Spain. He is also a professor at the Master in Clinical Epidemiology and Biostatistics, Universidad Científica del Sur, Lima, Peru. In 2021 he has been awarded the “Raul Isturiz Award” Medal of the API. Also, in 2021, he was awarded with the “Jose Felix Patiño” Asclepius Staff Medal of the Colombian Medical College, due to his scientific contributions to COVID-19 during the pandemic. He is currently the Editor in Chief of the journal Travel Medicine and Infectious Diseases. His Scopus H index is 47 (Google Scholar H index, 68).",institutionString:"Institución Universitaria Visión de las Américas, Colombia",institution:null},{id:"332819",title:"Dr.",name:"Chukwudi Michael",middleName:"Michael",surname:"Egbuche",slug:"chukwudi-michael-egbuche",fullName:"Chukwudi Michael Egbuche",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/332819/images/14624_n.jpg",biography:"I an Dr. Chukwudi Michael Egbuche. I am a Senior Lecturer in the Department of Parasitology and Entomology, Nnamdi Azikiwe University, Awka.",institutionString:null,institution:{name:"Nnamdi Azikiwe University",country:{name:"Nigeria"}}},{id:"284232",title:"Mr.",name:"Nikunj",middleName:"U",surname:"Tandel",slug:"nikunj-tandel",fullName:"Nikunj Tandel",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/284232/images/8275_n.jpg",biography:'Mr. Nikunj Tandel has completed his Master\'s degree in Biotechnology from VIT University, India in the year of 2012. He is having 8 years of research experience especially in the field of malaria epidemiology, immunology, and nanoparticle-based drug delivery system against the infectious diseases, autoimmune disorders and cancer. He has worked for the NIH funded-International Center of Excellence in Malaria Research project "Center for the study of complex malaria in India (CSCMi)" in collaboration with New York University. The preliminary objectives of the study are to understand and develop the evidence-based tools and interventions for the control and prevention of malaria in different sites of the INDIA. Alongside, with the help of next-generation genomics study, the team has studied the antimalarial drug resistance in India. Further, he has extended his research in the development of Humanized mice for the study of liver-stage malaria and identification of molecular marker(s) for the Artemisinin resistance. At present, his research focuses on understanding the role of B cells in the activation of CD8+ T cells in malaria. Received the CSIR-SRF (Senior Research Fellow) award-2018, FIMSA (Federation of Immunological Societies of Asia-Oceania) Travel Bursary award to attend the IUIS-IIS-FIMSA Immunology course-2019',institutionString:"Nirma University",institution:{name:"Nirma University",country:{name:"India"}}},{id:"334383",title:"Ph.D.",name:"Simone",middleName:"Ulrich",surname:"Ulrich Picoli",slug:"simone-ulrich-picoli",fullName:"Simone Ulrich Picoli",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/334383/images/15919_n.jpg",biography:"Graduated in Pharmacy from Universidade Luterana do Brasil (1999), Master in Agricultural and Environmental Microbiology from Federal University of Rio Grande do Sul (2002), Specialization in Clinical Microbiology from Universidade de São Paulo, USP (2007) and PhD in Sciences in Gastroenterology and Hepatology (2012). She is currently an Adjunct Professor at Feevale University in Medicine and Biomedicine courses and a permanent professor of the Academic Master\\'s Degree in Virology. She has experience in the field of Microbiology, with an emphasis on Bacteriology, working mainly on the following topics: bacteriophages, bacterial resistance, clinical microbiology and food microbiology.",institutionString:null,institution:{name:"Universidade Feevale",country:{name:"Brazil"}}},{id:"229220",title:"Dr.",name:"Amjad",middleName:"Islam",surname:"Aqib",slug:"amjad-aqib",fullName:"Amjad Aqib",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/229220/images/system/229220.png",biography:"Dr. Amjad Islam Aqib obtained a DVM and MSc (Hons) from University of Agriculture Faisalabad (UAF), Pakistan, and a PhD from the University of Veterinary and Animal Sciences Lahore, Pakistan. 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He received his medical degree from the Sousse Faculty of Medicine at Sousse, University of Sousse, Tunisia. He completed his surgical residency in General Surgery at the University Hospital Farhat Hached of Sousse and was a member of the Unit of Liver Transplantation in the University of Rennes, France. He then worked in the Department of Surgery at the Sahloul University Hospital in Sousse. Professor Derbel is presently working at the Clinique les Oliviers, Sousse, Tunisia. His hospital activities are mostly concerned with laparoscopic, colorectal, pancreatic, hepatobiliary, and gastric surgery. He is also very interested in hernia surgery and performs ventral hernia repairs and inguinal hernia repairs. He has been a member of the GREPA and Tunisian Hernia Society (THS). During his residency, he managed patients suffering from diabetic foot, and he was very interested in this pathology. For this reason, he decided to coordinate a book project dealing with the diabetic foot. Professor Derbel has published many articles in journals and collaborates intensively with IntechOpen Access Publisher as an editor.",institutionString:"Clinique les Oliviers",institution:null},{id:"300144",title:"Dr.",name:"Meriem",middleName:null,surname:"Braiki",slug:"meriem-braiki",fullName:"Meriem Braiki",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/300144/images/system/300144.jpg",biography:"Dr. Meriem Braiki is a specialist in pediatric surgeon from Tunisia. She was born in 1985. She received her medical degree from the University of Medicine at Sousse, Tunisia. She achieved her surgical residency training periods in Pediatric Surgery departments at University Hospitals in Monastir, Tunis and France.\r\nShe is currently working at the Pediatric surgery department, Sidi Bouzid Hospital, Tunisia. Her hospital activities are mostly concerned with laparoscopic, parietal, urological and digestive surgery. She has published several articles in diffrent journals.",institutionString:"Sidi Bouzid Regional Hospital",institution:null},{id:"229481",title:"Dr.",name:"Erika M.",middleName:"Martins",surname:"de Carvalho",slug:"erika-m.-de-carvalho",fullName:"Erika M. de Carvalho",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/229481/images/6397_n.jpg",biography:null,institutionString:null,institution:{name:"Oswaldo Cruz Foundation",country:{name:"Brazil"}}},{id:"186537",title:"Prof.",name:"Tonay",middleName:null,surname:"Inceboz",slug:"tonay-inceboz",fullName:"Tonay Inceboz",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/186537/images/system/186537.jfif",biography:"I was graduated from Ege University of Medical Faculty (Turkey) in 1988 and completed his Med. PhD degree in Medical Parasitology at the same university. I became an Associate Professor in 2008 and Professor in 2014. I am currently working as a Professor at the Department of Medical Parasitology at Dokuz Eylul University, Izmir, Turkey.\n\nI have given many lectures, presentations in different academic meetings. I have more than 60 articles in peer-reviewed journals, 18 book chapters, 1 book editorship.\n\nMy research interests are Echinococcus granulosus, Echinococcus multilocularis (diagnosis, life cycle, in vitro and in vivo cultivation), and Trichomonas vaginalis (diagnosis, PCR, and in vitro cultivation).",institutionString:"Dokuz Eylül University",institution:{name:"Dokuz Eylül University",country:{name:"Turkey"}}},{id:"71812",title:"Prof.",name:"Hanem Fathy",middleName:"Fathy",surname:"Khater",slug:"hanem-fathy-khater",fullName:"Hanem Fathy Khater",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/71812/images/1167_n.jpg",biography:"Prof. Khater is a Professor of Parasitology at Benha University, Egypt. She studied for her doctoral degree, at the Department of Entomology, College of Agriculture, Food and Natural Resources, University of Missouri, Columbia, USA. She has completed her Ph.D. degrees in Parasitology in Egypt, from where she got the award for “the best scientific Ph.D. dissertation”. She worked at the School of Biological Sciences, Bristol, England, the UK in controlling insects of medical and veterinary importance as a grant from Newton Mosharafa, the British Council. Her research is focused on searching of pesticides against mosquitoes, house flies, lice, green bottle fly, camel nasal botfly, soft and hard ticks, mites, and the diamondback moth as well as control of several parasites using safe and natural materials to avoid drug resistances and environmental contamination.",institutionString:null,institution:{name:"Banha University",country:{name:"Egypt"}}},{id:"99780",title:"Prof.",name:"Omolade",middleName:"Olayinka",surname:"Okwa",slug:"omolade-okwa",fullName:"Omolade Okwa",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/99780/images/system/99780.jpg",biography:"Omolade Olayinka Okwa is presently a Professor of Parasitology at Lagos State University, Nigeria. She has a PhD in Parasitology (1997), an MSc in Cellular Parasitology (1992), and a BSc (Hons) Zoology (1990) all from the University of Ibadan, Nigeria. She teaches parasitology at the undergraduate and postgraduate levels. She was a recipient of a Commonwealth fellowship supported by British Council tenable at the Centre for Entomology and Parasitology (CAEP), Keele University, United Kingdom between 2004 and 2005. She was awarded an Honorary Visiting Research Fellow at the same university from 2005 to 2007. \nShe has been an external examiner to the Department of Veterinary Microbiology and Parasitology, University of Ibadan, MSc programme between 2010 and 2012. She is a member of the Nigerian Society of Experimental Biology (NISEB), Parasitology and Public Health Society of Nigeria (PPSN), Science Association of Nigeria (SAN), Zoological Society of Nigeria (ZSN), and is Vice Chairperson of the Organisation of Women in Science (OWSG), LASU chapter. She served as Head of Department of Zoology and Environmental Biology, Lagos State University from 2007 to 2010 and 2014 to 2016. She is a reviewer for several local and international journals such as Unilag Journal of Science, Libyan Journal of Medicine, Journal of Medicine and Medical Sciences, and Annual Research and Review in Science. \nShe has authored 45 scientific research publications in local and international journals, 8 scientific reviews, 4 books, and 3 book chapters, which includes the books “Malaria Parasites” and “Malaria” which are IntechOpen access publications.",institutionString:"Lagos State University",institution:{name:"Lagos State University",country:{name:"Nigeria"}}},{id:"273100",title:"Dr.",name:"Vijay",middleName:null,surname:"Gayam",slug:"vijay-gayam",fullName:"Vijay Gayam",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/273100/images/system/273100.jpeg",biography:"Dr. Vijay Bhaskar Reddy Gayam is currently practicing as an internist at Interfaith Medical Center in Brooklyn, New York, USA. He is also a Clinical Assistant Professor at the SUNY Downstate University Hospital and Adjunct Professor of Medicine at the American University of Antigua. He is a holder of an M.B.B.S. degree bestowed to him by Osmania Medical College and received his M.D. at Interfaith Medical Center. His career goals thus far have heavily focused on direct patient care, medical education, and clinical research. He currently serves in two leadership capacities; Assistant Program Director of Medicine at Interfaith Medical Center and as a Councilor for the American\r\nFederation for Medical Research. As a true academician and researcher, he has more than 50 papers indexed in international peer-reviewed journals. He has also presented numerous papers in multiple national and international scientific conferences. His areas of research interest include general internal medicine, gastroenterology and hepatology. He serves as an editor, editorial board member and reviewer for multiple international journals. His research on Hepatitis C has been very successful and has led to multiple research awards, including the 'Equity in Prevention and Treatment Award” from the New York Department of Health Viral Hepatitis Symposium (2018) and the 'Presidential Poster Award” awarded to him by the American College of Gastroenterology (2018). He was also awarded 'Outstanding Clinician in General Medicine” by Venus International Foundation for his extensive research expertise and services, perform over and above the standard expected in the advancement of healthcare, patient safety and quality of care.",institutionString:"Interfaith Medical Center",institution:{name:"Interfaith Medical Center",country:{name:"United States of America"}}},{id:"93517",title:"Dr.",name:"Clement",middleName:"Adebajo",surname:"Meseko",slug:"clement-meseko",fullName:"Clement Meseko",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/93517/images/system/93517.jpg",biography:"Dr. Clement Meseko obtained DVM and PhD degree in Veterinary Medicine and Virology respectively. He has worked for over 20 years in both private and public sectors including the academia, contributing to knowledge and control of infectious disease. Through the application of epidemiological skill, classical and molecular virological skills, he investigates viruses of economic and public health importance for the mitigation of the negative impact on people, animal and the environment in the context of Onehealth. \r\nDr. Meseko’s field experience on animal and zoonotic diseases and pathogen dynamics at the human-animal interface over the years shaped his carrier in research and scientific inquiries. He has been part of the investigation of Highly Pathogenic Avian Influenza incursions in sub Saharan Africa and monitors swine Influenza (Pandemic influenza Virus) agro-ecology and potential for interspecies transmission. He has authored and reviewed a number of journal articles and book chapters.",institutionString:"National Veterinary Research Institute",institution:{name:"National Veterinary Research Institute",country:{name:"Nigeria"}}},{id:"158026",title:"Prof.",name:"Shailendra K.",middleName:null,surname:"Saxena",slug:"shailendra-k.-saxena",fullName:"Shailendra K. Saxena",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRET3QAO/Profile_Picture_2022-05-10T10:10:26.jpeg",biography:"Professor Dr. Shailendra K. Saxena is a vice dean and professor at King George's Medical University, Lucknow, India. His research interests involve understanding the molecular mechanisms of host defense during human viral infections and developing new predictive, preventive, and therapeutic strategies for them using Japanese encephalitis virus (JEV), HIV, and emerging viruses as a model via stem cell and cell culture technologies. His research work has been published in various high-impact factor journals (Science, PNAS, Nature Medicine) with a high number of citations. He has received many awards and honors in India and abroad including various Young Scientist Awards, BBSRC India Partnering Award, and Dr. JC Bose National Award of Department of Biotechnology, Min. of Science and Technology, Govt. of India. Dr. Saxena is a fellow of various international societies/academies including the Royal College of Pathologists, United Kingdom; Royal Society of Medicine, London; Royal Society of Biology, United Kingdom; Royal Society of Chemistry, London; and Academy of Translational Medicine Professionals, Austria. He was named a Global Leader in Science by The Scientist. He is also an international opinion leader/expert in vaccination for Japanese encephalitis by IPIC (UK).",institutionString:"King George's Medical University",institution:{name:"King George's Medical University",country:{name:"India"}}},{id:"94928",title:"Dr.",name:"Takuo",middleName:null,surname:"Mizukami",slug:"takuo-mizukami",fullName:"Takuo Mizukami",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/94928/images/6402_n.jpg",biography:null,institutionString:null,institution:{name:"National Institute of Infectious Diseases",country:{name:"Japan"}}},{id:"233433",title:"Dr.",name:"Yulia",middleName:null,surname:"Desheva",slug:"yulia-desheva",fullName:"Yulia Desheva",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/233433/images/system/233433.png",biography:"Dr. Yulia Desheva is a leading researcher at the Institute of Experimental Medicine, St. Petersburg, Russia. She is a professor in the Stomatology Faculty, St. Petersburg State University. She has expertise in the development and evaluation of a wide range of live mucosal vaccines against influenza and bacterial complications. Her research interests include immunity against influenza and COVID-19 and the development of immunization schemes for high-risk individuals.",institutionString:'Federal State Budgetary Scientific Institution "Institute of Experimental Medicine"',institution:null},{id:"238958",title:"Mr.",name:"Atamjit",middleName:null,surname:"Singh",slug:"atamjit-singh",fullName:"Atamjit Singh",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/238958/images/6575_n.jpg",biography:null,institutionString:null,institution:null},{id:"252058",title:"M.Sc.",name:"Juan",middleName:null,surname:"Sulca",slug:"juan-sulca",fullName:"Juan Sulca",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/252058/images/12834_n.jpg",biography:null,institutionString:null,institution:null},{id:"191392",title:"Dr.",name:"Marimuthu",middleName:null,surname:"Govindarajan",slug:"marimuthu-govindarajan",fullName:"Marimuthu Govindarajan",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/191392/images/5828_n.jpg",biography:"Dr. M. 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He serves as an editorial board member in various national and international scientific journals.",institutionString:null,institution:null},{id:"274660",title:"Dr.",name:"Damodar",middleName:null,surname:"Paudel",slug:"damodar-paudel",fullName:"Damodar Paudel",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/274660/images/8176_n.jpg",biography:"I am DrDamodar Paudel,currently working as consultant Physician in Nepal police Hospital.",institutionString:null,institution:null},{id:"241562",title:"Dr.",name:"Melvin",middleName:null,surname:"Sanicas",slug:"melvin-sanicas",fullName:"Melvin Sanicas",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241562/images/6699_n.jpg",biography:null,institutionString:null,institution:null},{id:"117248",title:"Dr.",name:"Andrew",middleName:null,surname:"Macnab",slug:"andrew-macnab",fullName:"Andrew Macnab",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of British Columbia",country:{name:"Canada"}}},{id:"322007",title:"Dr.",name:"Maria Elizbeth",middleName:null,surname:"Alvarez-Sánchez",slug:"maria-elizbeth-alvarez-sanchez",fullName:"Maria Elizbeth Alvarez-Sánchez",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Universidad Autónoma de la Ciudad de México",country:{name:"Mexico"}}},{id:"337443",title:"Dr.",name:"Juan",middleName:null,surname:"A. 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