Mann-Whitney U test for preoperative laboratory data.
\\n\\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\\n\\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\\n"}]',published:!0,mainMedia:{caption:"Highly Cited",originalUrl:"/media/original/117"}},components:[{type:"htmlEditorComponent",content:'IntechOpen is proud to announce that 191 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\nThroughout the years, the list has named a total of 261 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\nReleased this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\nWe wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
\n'}],latestNews:[{slug:"step-in-the-right-direction-intechopen-launches-a-portfolio-of-open-science-journals-20220414",title:"Step in the Right Direction: IntechOpen Launches a Portfolio of Open Science Journals"},{slug:"let-s-meet-at-london-book-fair-5-7-april-2022-olympia-london-20220321",title:"Let’s meet at London Book Fair, 5-7 April 2022, Olympia London"},{slug:"50-books-published-as-part-of-intechopen-and-knowledge-unlatched-ku-collaboration-20220316",title:"50 Books published as part of IntechOpen and Knowledge Unlatched (KU) Collaboration"},{slug:"intechopen-joins-the-united-nations-sustainable-development-goals-publishers-compact-20221702",title:"IntechOpen joins the United Nations Sustainable Development Goals Publishers Compact"},{slug:"intechopen-signs-exclusive-representation-agreement-with-lsr-libros-servicios-y-representaciones-s-a-de-c-v-20211123",title:"IntechOpen Signs Exclusive Representation Agreement with LSR Libros Servicios y Representaciones S.A. de C.V"},{slug:"intechopen-expands-partnership-with-research4life-20211110",title:"IntechOpen Expands Partnership with Research4Life"},{slug:"introducing-intechopen-book-series-a-new-publishing-format-for-oa-books-20210915",title:"Introducing IntechOpen Book Series - A New Publishing Format for OA Books"},{slug:"intechopen-identified-as-one-of-the-most-significant-contributor-to-oa-book-growth-in-doab-20210809",title:"IntechOpen Identified as One of the Most Significant Contributors to OA Book Growth in DOAB"}]},book:{item:{type:"book",id:"1611",leadTitle:null,fullTitle:"Nonlinear Optics",title:"Nonlinear Optics",subtitle:null,reviewType:"peer-reviewed",abstract:"Rapid development of optoelectronic devices and laser techniques poses an important task of creating and studying, from one side, the structures capable of effectively converting, modulating, and recording optical data in a wide range of radiation energy densities and frequencies, from another side, the new schemes and approaches capable to activate and simulate the modern features. It is well known that nonlinear optical phenomena and nonlinear optical materials have the promising place to resolve these complicated technical tasks. The advanced idea, approach, and information described in this book will be fruitful for the readers to find a sustainable solution in a fundamental study and in the industry approach. 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PhD. Natalia Vladimirovna Kamanina was born in Kaliningrad, Russian Federation, 1957. She graduated with an Honor Diploma from Leningrad Polytechnical Institute (1981), St. Petersburg, Russia, and received a PhD (Physics & Mathematics) at Vavilov State Optical Institute, St.-Petersburg, Russia (1995), as well as a Dr. Sci. (Physics & Mathematics) at the same institution (2001). She is currently a Head of the Lab for “Photophysics of media with nanoobjects” at Vavilov State Optical Institute St.-Petersburg, Russia and has been involved in collaboration research with many researchers and scientists all over the world since 1995, publishing about 200 technical papers. Her pioneer ideas and experienced contributions were applied in technique and were certificated by 13 Russian Patents. Dr.Sci. N.V. Kamanina has current interest in the areas of investigations on organic conjugated materials, liquid crystals, inorganic soft materials of the UV and IR range, laser-matter interaction, fullerenes and biological objects. She has an experience in nanoparticles doping process of organics, in recording of amplitude-phase thin gratings in thin films as well as in developing of LC cells and spatial light modulators; she has an experience in optical limiting effect of laser radiation over visible and infrared spectral ranges, in medical applications of LC structures to orient human blood cell. 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Also, drug-loaded ligand anchored liposomes are used to induce selective apoptosis in cells of monocyte and macrophage lineage. Therefore this book aims to cover all spheres of drug and antigen delivery for developing therapeutic interventions and vaccines against infectious diseases and beyond.
\r\n\r\n\tThis book will shed light on various methods for the preparation and characterization of liposomes and their engineered versions. Technological advancements have enabled us to develop newer methods of formulating liposomes. Over time, liposomes have been modified to a larger extent and engineered to meet our growing needs for sustained and controlled delivery for developing therapeutic interventions vaccines. Further, this book will throw light on the various methods of preparation and characterization of liposomes, and discuss several biochemical and indirect methods to understand the biological and physicochemical mechanisms of action of liposomes that decide their efficiency in vivo.
\r\n\tDespite their limitations such as encapsulation efficiency, liposomes are a well-established choice for a number of unconventional and conventional biological applications. The versatility of these lipid-based vesicles presents the importance of these nanoparticles in the future applications of nanotechnology besides targeted drug delivery. Overall, this book provides the necessary and relevant information about various aspects of liposomes and their use in nanomedicine.
\r\n\t
To facilitate the work of the thoracic surgeon it has become accepted procedure in certain circumstances to collapse the diseased lung being operated upon. To accomplish this, the technique most frequently used by the anaesthetist calls for the insertion of a double lumen endobronchial tube. This makes it possible to isolate the intact dependent lung from the diseased upper one and thus to prevent contamination of the sound lung. On the other hand, collapse of the uppermost lung causes serious functional respiratory modifications which call for special compensatory measures to avoid hypoxaemia. The purpose of this study is to stress again that optimum maintenance of oxygenation is crucial for the prevention of sustained cellular hypoxia and to show how this may be achieved (1-3).
\n\t\t\tDuring one-lung ventilation (OLV) with patients in the lateral decubitus position, there is a potential risk of considerable intrapulmonary shunting of deoxygenated pulmonary arterial blood, which may result in hypoxemia. The consequences of an increase in pulmonary vascular resistance (PVR) in the nondependent (nonventilated) lung is to redistribute blood flow to the ventilated dependent lung, thereby preventing PaO2 from excessive decrease. This increase in nondependent lung pulmonary vascular resistance is predominantly due to hypoxic pulmonary vasoconstriction (HPV) (4-8).
\n\t\tSometimes, even in normal situations, and especially when there is a disease, a number of zones in the lungs are well ventilated, but the blood doesn’t run through their vessels, while there are other areas with extraordinary blood flow, but with poor or no ventilation at all. It is clear that in each of the mentioned conditions the gas exchange through the respiratory membrane is seriously damaged, leading to severe respiratory difficulties, although the total ventilation and the total blood flow through the lungs are regular. A new concept is formulated on this basis, helping understand the respiratory gas exchange even when there is a disturbance of the relation between alveolar ventilation and alveolar blood flow. This term is so called ventilation/perfusion ratio, expressed in quantitative sense as Va/Qt.
\n\t\t\tIn the awake subject, there is little or no additional ventilation/perfusion mismatch in the lateral position. The situation changes during anaesthesia. In the spontaneously breathing subject, there is a reduction in inspiratory muscle tone (particularly the diaphragm) and a decrease in the volume of both lungs with a reduction in functional residual capacity. The compliance of the non-dependent upper lung increases and it receives more ventilation. Paralysis and intermittent positive pressure ventilation are used during thoracotomy and the compliance of the non-dependent lung is increased even further. In practice, it is usual to selectively ventilate the lower lung (OLV) at this point and allow the upper lung to collapse. This eliminates the preferential ventilation and facilitates surgical access, but creates the more serious problem of ventilation/perfusion mismatch (9).
\n\t\tPulmonary blood flow continues to the upper lung during one-lung anaesthesia, creating a true shunt in a lung where there is blood flow to the alveoli but no ventilation. This shunt is the major cause of hypoxaemia during OLV, although the alveoli with low ventilation/perfusion ratios in the dependent lung also contribute. In addition, the blood to the upper lung cannot take up oxygen and therefore retains its poorly oxygenated mixed venous composition. This mixes with oxygenated blood in the left atrium causing venous admixture and lowering arterial oxygen tension (PaO2). Total venous admixture can be calculated from the shunt equation which estimates what proportion of the pulmonary blood flow would have bypassed ventilated alveoli to produce the arterial blood gas values for a particular patient. Venous admixture and shunt (Qs/Qt) are often used synonymously. Venous admixture increases from a value of approximately 10% - 15% during two-lung ventilation to 30% - 40% during OLV. The PaO2 can be maintained in the range of 9–16 kPa with an inspired oxygen concentration between 50% and 100% in the majority of patients.
\n\t\tHypoxic pulmonary vasocontriction (HPV) is a mechanism whereby pulmonary blood flow is diverted away from hypoxic/collapsed areas of lung. This should improve oxygenation during OLV. Volatile anaesthetic agents depress HPV directly, but also enhance HPV by reducing cardiac output. There is therefore no change in the HPV response with volatile agents during thoracotomy and OLV.
\n\t\t\tIntravenous agents, such as propofol, do not inhibit HPV and should improve arterial oxygenation during OLV. There is some evidence to support this contention (10-17).
\n\t\tChanges in cardiac output affect arterial oxygenation during thoracotomy. A decrease in cardiac output results in a reduced mixed venous oxygen content. Some of this desaturated blood is shunted during OLV and further exacerbates arterial hypoxaemia. Cardiac output can decrease for a number of reasons during thoracotomy. These include blood loss/fluid depletion, the use of high inflation pressures and the application of positive end-expiratory pressure (PEEP) to the dependent lung. Surgical manipulation and retraction around the mediastinum, causing a reduction in venous return, are probably the commonest causes of a sudden drop in cardiac output during lung resection (18-20).
\n\t\tOLV should be established to adequately inflate the lung but also minimize intra-alveolar pressure and so prevent diversion of pulmonary blood flow to the upper lung. In practice, this is not easy to achieve. It is reasonable to use an inspired oxygen concentration of 50% initially, which can be increased to 100%, if required. This cannot affect the true shunt in the upper lung but improves oxygenation through the alveoll with low V/Q ratios in the lower lung. Overinflating the single lung (‘volutrauma’) can be detrimental and lead to acute lung injury. Deflation and inflation of the operative lung with the potential for ischaemia/reperfusion injury has also been implicated in lung damage. The use of low tidal volumes improves outcome in ventilated patients with adult respiratory distress syndrome (ARDS) and this may also apply to OLV. Limiting ventilation can lead to carbon dioxide retention, but a degree of permissive hypercapnia is preferable to lung trauma (21-25).
\n\t\tIt is difficult to predict which patients are likely to be hypoxic (SpO2 < 90%) during OLV. Patients with poor lung function are sometimes accepted for lung resection on the basis that their diseased lung is contributing little to gas exchange and this can be confirmed by V/Q scanning. Conversely, patients with normal lung function are more likely to be hypoxic during OLV because an essentially normal lung is collapsed to provide surgical access. The most significant predictors of a low arterial oxygen saturation during OLV are (1) a right-sided operation, (2) a low oxygen saturation during two-lung ventilation prior to OLV and (3) a high (or more normal) forced expiratory volume in 1 sec. preoperatively. Once hypoxia occurs, it is important to check the position of the endobronchial tube and readjust this if necessary. A high inflation pressure (> 30–35 cmH2O) may indicate that the tube is displaced. It may be helpful to analyse a flow/volume loop or at least manually reinflate the lung to feel the compliance. If a tube is obstructing a lobar orifice, only one or two lobes are being ventilated at most and hypoxia is likely to occur. Suction and manual reinflation of the dependent lung may be useful.Other measures which can be used to improve oxygenation include increasing the inspired oxygen concentration, introducing PEEP to the dependent lung, or supplying oxygen to the upper lung via a continuous positive airway system, thereby reducing the shunt. In the face of persistent arterial hypoxaemia during OLV, it is pertinent to ask ‘What is a low PaO2 for this patient?’. An oxygen saturation below 90% is commonly tolerated. This arbitrary figure is affected by a variety of factors, including acidosis and temperature. Many patients will have a low PaO2 when measured while breathing air preoperatively; hence, the usefulness of this preoperative measurement. Arterial hypoxaemia is obviously undesirable but it may be preferable to accept a PaO2 slightly lower than the preoperative value, rather than undertake measures such as upper lung inflation which may hinder and prolong surgery (26-31).
\n\t\tThoracic epidural anesthesia (TEA) with local anesthetics during OLV is increasingly being combined with general anesthesia (GA) in our clinical practice for thoracic surgery. A combination of TEA with GA might maximize the benefits of each form of anesthesia. Furthermore, epidural anesthesia and postoperative epidural analgesia with their effects that exceed pain release, may improve outcome in high-risk patients (32, 33).
\n\t\t\tThoracic epidural anesthesia reduces the incidence of respiratory complications as well as thoracic morbidity. Besides the excellent postoperative analgesia, it improves the strength and coordination of respiratory muscles; blocking the inhibitory phrenic reflex recovers the function of the diaphragm and the lungs, decreasing the occurrence of athelectasis as well as lung infections. On account of all these effects, the thoracic epidural anesthesia permits early extubation along with decreased length of ICU treatment.
\n\t\t\tThis type of anesthetic technique provides particular advantage in COPD patients as well as cardiac patients: controls tachyarrhythmia, lessens thrombotic complications, liberates from the angina pectoris, reduces myocardial straining, improves left-ventricular function, and makes the balance of myocardial oxygen supply better. By blocking sympathetic nervous system, the high thoracic epidural technique leads to vasodilatation and hypotension, reducing cardiac output. Furthermore, the consequence mentioned above enhances skin perfusion and improves the oxygen supply of peripheral tissues (34).
\n\t\t\tThe blockade of the afferent nervous impulses made by the thoracic epidural anesthesia prevents and modifies neuro-endocrine, metabolic, immune, as well as autonomic response of the human body to surgical stress.
\n\t\t\tPotential disadvantages include the time required to establish epidural anesthesia, intravascular fluid administration needed to avoid hypotension, and the potential for technical complications, such as epidural hematoma.
\n\t\t\tThe effect of intraoperative TEA with local anesthetics on HPV during thoracic surgery and OLV is unclear. Up till now, there isn’t sufficient number of studies in the literature, capable to offer a definite answer to this dilemma. The pulmonary vasculature is innervated by the autonomic nervous system, and the sympathetic tone is dominant in the pulmonary circulation relative to parasympathetic activity. Theoretically, a TEA-induced sympathectomy might attenuate HPV (35). However, in one recent experimental study, TEA did not affect the primary pulmonary vascular tone, but it improved PaO2 because of enhanced blood flow diversion from the hypoxic lobe (36-38).
\n\t\t\tOur aim in this study was:
\n\t\t\tTo determine the quantity of intrapulmonary shunt during general anesthesia and OLV.
\n\t\t\tTo determine the quantity of intrapulmonary shunt during combination of thoracic epidural anesthesia and general anesthesia with OLV.
\n\t\t\tTo compare the values of intrapulmonary shunt in both mentioned techniques.
\n\t\tThis prospective, longitudinal, randomized, interventional clinical study was performed at the Clinic of Anesthesiology, Reanimation and Intensive care and the Clinic of Thoracic-vascular surgery in Skopje, after getting an approvalal by our ethics committee, and signed, informed consent from each patient.
\n\t\t\tWe studied 60 patients who underwent elective lung surgery (by thoracotomy / thoracoscopy), or other surgical procedure which required OLV in lateral decubitus position (LDP). Patients were randomized to one of two study groups by lottery: general iv anesthesia (GA group = Group A) or general iv anesthesia combined with TEA (TEA group = Group B).
\n\t\t\t\n\t\t\t\t
Patients undergoing lung resection (by thoracotomy: pneumonectomy, bilobectomy, lobectomy,segmentectomy) or thoracoscopic procedures;
\n\t\t\tProcedures other than lung resection, requiring OLV in LDP;
\n\t\t\tAge between 15 and 75 years;
\n\t\t\tASA 1, 2;
\n\t\t\tPreoperative values of SaO2 ≥ 90%.
\n\t\t\t\n\t\t\t\t
Renal insufficiency (creatinine>114 umol/L);
\n\t\t\tLiver dysfunction (aspartate amino transferase-AST >40 U/L, alanine amino transferase-ALT >40 U/L);
\n\t\t\tDocumented coronary or vascular disease (EF<50%);
\n\t\t\tPreviously existing chronic respiratory disease of non-operated lung;
\n\t\t\tFVC, FEV1 < 50%,
\n\t\t\tPatients who intraoperatively needed FiO2>0.5.
\n\t\t\t\n\t\t\t\t
Patients with serious haemostatic disorders and/or those under anticoagulant therapy (<12 hours since the last dose of LMWH);
\n\t\t\tPatients with serious deformities of the vertebral column, neurological diseases, and/or
\n\t\t\tInfection in the thoracic or lumbosacral region of the spine.
\n\t\t\tThe methods used in this study included as follows:
\n\t\t\t\n\t\t\t\t
\n\t\t\t\t
In the TEA group – group B (combined anesthesia), an epidural catheter was placed at the Th5-6, Th6-7 or Th7-8 interspaces and advanced 3 cm in the epidural space before anaesthesia induction. TEA was then induced using an initial 6 to 8-ml dose of plain bupivacaine 0.5%; if necessary, additional increment doses up to 14 ml were administered until a thoracic-sensitive blockade was induced. The level of anesthesia was determined by the loss of pinprick sensation. During the onset of epidural anesthesia, colloids were infused (7 ml/kg); crystalloids (8 ml/kg/h) were subsequently infused throughout the study (the same rate as in group A), and when systolic arterial blood pressure decreased to 100 mm Hg, ephedrine was planned to be injected in increments of 5 mg (yet, no patient received ephedrine). GA was induced using the same method as in group A. After tracheal intubation, with a double-lumen endobronchial tube, anesthesia was maintained by continuous epidural infusion (6–8 ml/h) of bupivacaine 0.25%, plus propofol in continuous perfusion (6–7 mg/kg/h) and rocuronium (0.3 mg/kg/h) in continuous perfusion, or pancuronium (0.01 mg/kg), as well as fentanyl.
\n\t\t\tIn both groups, fluid replacement and transfusion management were based on hemodynamic monitoring and were under the direction of the attending anesthesiologist.
\n\t\t\tAfter the induction of anesthesia, an arterial catheter was placed in the radial artery, contra lateral from the operated side, with the intention of extraction of arterial blood samples and consequent blood gases and intrapulmonary shunt analysis.
\n\t\t\tAfter clinical confirmation of correct double-lumen tube placement (by inspection and auscultation) with the patient in both supine and lateral decubitus position, ventilation was controlled (volume-controlled mechanical ventilation – VC) by using 50% oxygen in air (for all patients) and tidal volume of 6-8 ml/kg at a respiratory rate to maintain PaCO2 between 35 and 40 mm Hg (4, 5 – 6 kPa). Effective lung isolation was determined by the absence of leak from the nonventilated lumen of the endobronchial tube. When the pleura was opened, the isolation was confirmed by direct observation of the collapsed nonventilated lung and the absence of leak from this lung. During OLV, the same tidal volume, respiratory rate, and fraction of inspired oxygen were used; the bronchus of the lung not being ventilated upon was excluded and open to atmospheric pressure.
\n\t\t\tMonitoring during anesthesia:
\n\t\t\theart rate (HR)
ECGmean arterial pressure (MAP)
\n\t\t\trespiratory rate (RR)
\n\t\t\toxygen saturation from pulsoxymetry – SAT%
\n\t\t\tinspired oxygen fraction – FiO2
\n\t\t\tpartial pressure of carbon dioxide in arterial blood – PaCO2
\n\t\t\t\n\t\t\t\t
T0 - during TLV
\n\t\t\tT1 - immediately after beginning of OLV
\n\t\t\tT2 - 10 min. after beginning of OLV
\n\t\t\tT3 - 30 min after beginning of OLV
\n\t\t\tBlood samples were drawn simultaneously from the arterial catheter and analyzed within 10 min., using the blood gases analyzator AVL
\n\t\t\t\t
partial pressure of oxygen in arterial blood (PaO2)
\n\t\t\toxygen saturation of arterial blood (SaO2)
\n\t\t\tintrapulmonary shunt value (Qs/Qt).
\n\t\t\tThe Qs/Qt% is usually calculated using the venous admixture equation:
\n\t\t\tBut for the purpose of this study, the quantitative value of Qs/Qt % was mathematically calculated by the blood gases analyzator
\n\t\t\t\t
For CI (confindence interval ) was considered p<0,05.
\n\t\t\tResults were displayed with table and graph illustrations.
\n\t\t60 patients were enrolled in the study, 47 of which were men, and 13 were women (p=0,020). The examinated patients were divided in two groups, each with 30 pts: group A, whose patients underwent thoracic surgery with OLV in general anesthesia, and Group B, subjected to the same operative procedure, performed in combined general and thoracic epidural anesthesia.
\n\t\t\t\t\n\t\t\t\t\tFigure 1 demonstrates patients’ gender in groups, showing that no statistically significant difference exists between two examinated groups of patients.
\n\t\t\t\tGender distribution of patients.
In group A are recorded 76,7% male pts and 23,3% females. Percentage variation registered among gender categories is statistically significant for p=0,0001. In group B 80,0% pts are male, and 20,0% female. This proportion dissimilarity is also statistically significant for p=0,0000. The diversity recorded among genders between two examinated groups is statistically irrelevant for p>0,05, confirming similarity i.e. equal presence of genders among two studied groups of patients (Figure 1).
\n\t\t\t\tAverage age of patients.
The average age of patients in group A is 49,96±16,6 years, minimum 17, maximum 74 years. The average age of patients in group B is 57,03±13,0 years, minimum 26, maximum 78 years. The recorded difference in average age of patients among two studied groups is statistically insignificant for p=0,0714 (Figure 2).
\n\t\t\t\tAverage body weight of patients.
The average body weight of patients in group A is 75,4±14,0 kg, minimum 53,7, maximum 105 kg. The average body weight of patients in group B is 72,0±16,7 kg, minimum 40, maximum 120 kg. The difference in average body weight recorded between patients from two examinated groups is not statistically important for p=0,359335 (Figure 3).
\n\t\t\tIn group A, ASA 1 status is listed in 36,7% of patients, while in 63,3% pts ASA 2 status is recorded. In group B, 33,3% of patients had ASA 1 status, whereas 66,7% had status ASA 2. The percentage variety registered between the presence of ASA 1 and 2 inside both groups is statistically significant for p<0,05; on the other hand, percentage difference among both groups A and B is statistically insignificant for p>0,05 (Figure 4).
\n\t\t\t\tDistribution of patients according to ASA classification.
Patients with / without positive medical history in both groups.
30,0% of patients in group A don’t have positive medical history for co-morbidities, and in group B - 16,7%; the difference is not statistically important for p>0,05. In both groups of patients, the most frequently recorded co-morbidities are smoking, hypertension, diabetes, duodenal ulcer etc. In some patients more than one disorder is listed (Figure 5).
\n\t\t\t\tBiochemistry | \n\t\t\t\t\t\t\tRank Sum-A | \n\t\t\t\t\t\t\tRank Sum-B | \n\t\t\t\t\t\t\tU | \n\t\t\t\t\t\t\tZ | \n\t\t\t\t\t\t\tp-level | \n\t\t\t\t\t\t
Hb | \n\t\t\t\t\t\t\t916,5 | \n\t\t\t\t\t\t\t913,5 | \n\t\t\t\t\t\t\t448,5 | \n\t\t\t\t\t\t\t0,022177 | \n\t\t\t\t\t\t\t0,982307 | \n\t\t\t\t\t\t
Hct | \n\t\t\t\t\t\t\t941,0 | \n\t\t\t\t\t\t\t889,0 | \n\t\t\t\t\t\t\t424,0 | \n\t\t\t\t\t\t\t0,384395 | \n\t\t\t\t\t\t\t0,700686 | \n\t\t\t\t\t\t
Creatinin | \n\t\t\t\t\t\t\t872,5 | \n\t\t\t\t\t\t\t957,5 | \n\t\t\t\t\t\t\t407,5 | \n\t\t\t\t\t\t\t-0,628338 | \n\t\t\t\t\t\t\t0,529783 | \n\t\t\t\t\t\t
ALT | \n\t\t\t\t\t\t\t1027,5 | \n\t\t\t\t\t\t\t802,5 | \n\t\t\t\t\t\t\t337,5 | \n\t\t\t\t\t\t\t1,663248 | \n\t\t\t\t\t\t\t0,096264 | \n\t\t\t\t\t\t
AST | \n\t\t\t\t\t\t\t998,0 | \n\t\t\t\t\t\t\t832,0 | \n\t\t\t\t\t\t\t367,0 | \n\t\t\t\t\t\t\t1,227107 | \n\t\t\t\t\t\t\t0,219783 | \n\t\t\t\t\t\t
Mann-Whitney U test for preoperative laboratory data.
The average values of laboratory data (hemoglobin, hematocrit, creatinin, ALT, AST) in both studied groups are in the range of referent values. The recorded difference in average values of examinated parameters among two groups of patients is statistically insignificant for p>0,05, according to Mann-Whitney U test (Table 1).
\n\t\t\t\tScreening haemostasis | \n\t\t\t\t\t\t\tRank Sum-A | \n\t\t\t\t\t\t\tRank Sum-B | \n\t\t\t\t\t\t\tU | \n\t\t\t\t\t\t\tZ | \n\t\t\t\t\t\t\tp-level | \n\t\t\t\t\t\t
PT | \n\t\t\t\t\t\t\t963,5 | \n\t\t\t\t\t\t\t866,5 | \n\t\t\t\t\t\t\t401,5 | \n\t\t\t\t\t\t\t0,71704 | \n\t\t\t\t\t\t\t0,473347 | \n\t\t\t\t\t\t
aPTT | \n\t\t\t\t\t\t\t802,0 | \n\t\t\t\t\t\t\t1028,0 | \n\t\t\t\t\t\t\t337,0 | \n\t\t\t\t\t\t\t-1,67064 | \n\t\t\t\t\t\t\t0,094794 | \n\t\t\t\t\t\t
TT | \n\t\t\t\t\t\t\t854,5 | \n\t\t\t\t\t\t\t975,5 | \n\t\t\t\t\t\t\t389,5 | \n\t\t\t\t\t\t\t-0,89446 | \n\t\t\t\t\t\t\t0,371078 | \n\t\t\t\t\t\t
PLT | \n\t\t\t\t\t\t\t913,5 | \n\t\t\t\t\t\t\t916,50 | \n\t\t\t\t\t\t\t448,5 | \n\t\t\t\t\t\t\t-0,02218 | \n\t\t\t\t\t\t\t0,982307 | \n\t\t\t\t\t\t
Mann-Whitney U test for screening haemostasis.
The average values of PT, aPTT, TT and PLT from haemostasis in both studied groups are in the range of refferent values. The recorded difference between these average values among two groups is statistically insignificant for p>0,05, according to Mann-Whitney U test (Table 2).
\n\t\t\t\tGas status | \n\t\t\t\t\t\t\tRank Sum-A | \n\t\t\t\t\t\t\tRank Sum-B | \n\t\t\t\t\t\t\tU | \n\t\t\t\t\t\t\tZ | \n\t\t\t\t\t\t\tp-level | \n\t\t\t\t\t\t
PaO2 | \n\t\t\t\t\t\t\t934,0 | \n\t\t\t\t\t\t\t896,0 | \n\t\t\t\t\t\t\t431,0 | \n\t\t\t\t\t\t\t0,280904 | \n\t\t\t\t\t\t\t0,778784 | \n\t\t\t\t\t\t
PaCO2 | \n\t\t\t\t\t\t\t979,0 | \n\t\t\t\t\t\t\t851,0 | \n\t\t\t\t\t\t\t386,0 | \n\t\t\t\t\t\t\t0,946203 | \n\t\t\t\t\t\t\t0,344046 | \n\t\t\t\t\t\t
SaO2 | \n\t\t\t\t\t\t\t890,0 | \n\t\t\t\t\t\t\t940,0 | \n\t\t\t\t\t\t\t425,0 | \n\t\t\t\t\t\t\t-0,369611 | \n\t\t\t\t\t\t\t0,711673 | \n\t\t\t\t\t\t
Mann-Whitney U test for preoperative gas status.
The average values of PaO2, PaCO2 and SaO2 from preoperative gas status in both studied groups are in extend of refferent values. The recorded differentiation between these values among two groups is not statistically significant for p>0,05, in accordance with Mann-Whitney U test (Table 3).
\n\t\t\t\t\n\t\t\t\t\tFigure 6 shows the dispersal of patients from both examinated groups in relation to the value of preoperative intrapulmonary shunt - Qs/Qt.
\n\t\t\t\tThe average values of FVC and FEV1 in patients from both studied groups are in range of refferent values. The recorded variation between these average values among the two groups is statistically irrelevant for p>0,05, consistent with Mann-Whitney U test (Table 4).
\n\t\t\t\tPreoperative value of intrapulmonary shunt (Qs/Qt).
\n\t\t\t\t\t\t\t | Rank Sum-А | \n\t\t\t\t\t\t\tRank Sum-B | \n\t\t\t\t\t\t\tU | \n\t\t\t\t\t\t\tZ | \n\t\t\t\t\t\t\tp-level | \n\t\t\t\t\t\t
FVC | \n\t\t\t\t\t\t\t850,5 | \n\t\t\t\t\t\t\t979,5 | \n\t\t\t\t\t\t\t385,5 | \n\t\t\t\t\t\t\t-0,95360 | \n\t\t\t\t\t\t\t0,340289 | \n\t\t\t\t\t\t
FEV1 | \n\t\t\t\t\t\t\t831,0 | \n\t\t\t\t\t\t\t999,0 | \n\t\t\t\t\t\t\t366,0 | \n\t\t\t\t\t\t\t-1,24189 | \n\t\t\t\t\t\t\t0,214277 | \n\t\t\t\t\t\t
Mann-Whitney U test for FVC and FEV1.
\n\t\t\t\t\t\t\t | Rank Sum-А | \n\t\t\t\t\t\t\tRank Sum- B | \n\t\t\t\t\t\t\tU | \n\t\t\t\t\t\t\tZ | \n\t\t\t\t\t\t\tp-level | \n\t\t\t\t\t\t
EF% | \n\t\t\t\t\t\t\t465,0 | \n\t\t\t\t\t\t\t1365,0 | \n\t\t\t\t\t\t\t0,00 | \n\t\t\t\t\t\t\t-6,65299 | \n\t\t\t\t\t\t\t0,000000* | \n\t\t\t\t\t\t
Mann-Whitney U test for EF%.
The average values of EF% in patients from both examinated groups are in extend of refferent values. The disclosed difference between these parameters among two groups is statistically significant for p=0,00000*, according to Mann-Whitney U test (Table 5), but without clinical importance.
\n\t\t\tAverage values of HR/min. in both groups show rise during the operative monitoring from T0 to T3. The difference in HR/min. between groups A and B (Mann-Whitney U test) is statistically significant only for Т0 and Т3 (p=0,02* and p=0,04*). On the other hand, the differences in these values inside groups A and B (ANOVA test) are statistically insignificant (Tables 6, 7).
\n\t\t\t\tAverage values of MAP/mmHg in both groups illustrate increase during the operative monitoring from T0 to T2, and then decrease in T3. This difference between groups A and B is statistically irrelevant. Inside groups, the discrepancy of average values of MAP/mmHg is statistically significant only in group A (p=0,019*).These statistically relevant differences for HR/min. and MAP/mmHg don’t have clinical importance (Table 6,7).
\n\t\t\t\tParameters \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\tRank Sum-А | \n\t\t\t\t\t\t\tRank Sum-B | \n\t\t\t\t\t\t\tU | \n\t\t\t\t\t\t\tZ | \n\t\t\t\t\t\t\tp-level | \n\t\t\t\t\t\t
HR/minT0 | \n\t\t\t\t\t\t\t1076,500 | \n\t\t\t\t\t\t\t753,500 | \n\t\t\t\t\t\t\t288,5000 | \n\t\t\t\t\t\t\t2,38768 | \n\t\t\t\t\t\t\t0,016955* | \n\t\t\t\t\t\t
HR/min T1 | \n\t\t\t\t\t\t\t969,000 | \n\t\t\t\t\t\t\t861,000 | \n\t\t\t\t\t\t\t396,0000 | \n\t\t\t\t\t\t\t0,79836 | \n\t\t\t\t\t\t\t0,424663 | \n\t\t\t\t\t\t
HR/min T2 | \n\t\t\t\t\t\t\t1020,000 | \n\t\t\t\t\t\t\t810,000 | \n\t\t\t\t\t\t\t345,0000 | \n\t\t\t\t\t\t\t1,55236 | \n\t\t\t\t\t\t\t0,120576 | \n\t\t\t\t\t\t
HR/min T3 | \n\t\t\t\t\t\t\t1049,000 | \n\t\t\t\t\t\t\t781,000 | \n\t\t\t\t\t\t\t316,0000 | \n\t\t\t\t\t\t\t1,98111 | \n\t\t\t\t\t\t\t0,047579* | \n\t\t\t\t\t\t
MAP/mmHg T0 | \n\t\t\t\t\t\t\t787,000 | \n\t\t\t\t\t\t\t1043,000 | \n\t\t\t\t\t\t\t322,0000 | \n\t\t\t\t\t\t\t-1,89241 | \n\t\t\t\t\t\t\t0,058438 | \n\t\t\t\t\t\t
MAP/mmHg T1 | \n\t\t\t\t\t\t\t916,000 | \n\t\t\t\t\t\t\t914,000 | \n\t\t\t\t\t\t\t449,0000 | \n\t\t\t\t\t\t\t0,01478 | \n\t\t\t\t\t\t\t0,988204 | \n\t\t\t\t\t\t
MAP/mmHg T2 | \n\t\t\t\t\t\t\t922,000 | \n\t\t\t\t\t\t\t908,000 | \n\t\t\t\t\t\t\t443,0000 | \n\t\t\t\t\t\t\t0,10349 | \n\t\t\t\t\t\t\t0,917573 | \n\t\t\t\t\t\t
MAP/mmHg T3 | \n\t\t\t\t\t\t\t857,000 | \n\t\t\t\t\t\t\t973,000 | \n\t\t\t\t\t\t\t392,0000 | \n\t\t\t\t\t\t\t-0,85750 | \n\t\t\t\t\t\t\t0,391171 | \n\t\t\t\t\t\t
RR/min T0 | \n\t\t\t\t\t\t\t915,000 | \n\t\t\t\t\t\t\t915,000 | \n\t\t\t\t\t\t\t450,0000 | \n\t\t\t\t\t\t\t0,00000 | \n\t\t\t\t\t\t\t1,000000 | \n\t\t\t\t\t\t
RR/min T1 | \n\t\t\t\t\t\t\t986,500 | \n\t\t\t\t\t\t\t843,500 | \n\t\t\t\t\t\t\t378,5000 | \n\t\t\t\t\t\t\t1,05709 | \n\t\t\t\t\t\t\t0,290473 | \n\t\t\t\t\t\t
RR/min T2 | \n\t\t\t\t\t\t\t973,000 | \n\t\t\t\t\t\t\t857,000 | \n\t\t\t\t\t\t\t392,0000 | \n\t\t\t\t\t\t\t0,85750 | \n\t\t\t\t\t\t\t0,391171 | \n\t\t\t\t\t\t
RR/min T3 | \n\t\t\t\t\t\t\t942,000 | \n\t\t\t\t\t\t\t888,000 | \n\t\t\t\t\t\t\t423,0000 | \n\t\t\t\t\t\t\t0,39918 | \n\t\t\t\t\t\t\t0,689761 | \n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t\t | \n\t\t\t\t\t\t |
SAT% T0 | \n\t\t\t\t\t\t\t1021,000 | \n\t\t\t\t\t\t\t809,000 | \n\t\t\t\t\t\t\t344,0000 | \n\t\t\t\t\t\t\t1,56715 | \n\t\t\t\t\t\t\t0,117081 | \n\t\t\t\t\t\t
SAT% T1 | \n\t\t\t\t\t\t\t1009,500 | \n\t\t\t\t\t\t\t820,500 | \n\t\t\t\t\t\t\t355,5000 | \n\t\t\t\t\t\t\t1,39713 | \n\t\t\t\t\t\t\t0,162376 | \n\t\t\t\t\t\t
SAT% T2 | \n\t\t\t\t\t\t\t961,000 | \n\t\t\t\t\t\t\t869,000 | \n\t\t\t\t\t\t\t404,0000 | \n\t\t\t\t\t\t\t0,68008 | \n\t\t\t\t\t\t\t0,496452 | \n\t\t\t\t\t\t
SAT% T3 | \n\t\t\t\t\t\t\t915,000 | \n\t\t\t\t\t\t\t915,000 | \n\t\t\t\t\t\t\t450,0000 | \n\t\t\t\t\t\t\t0,00000 | \n\t\t\t\t\t\t\t1,000000 | \n\t\t\t\t\t\t
PCO2 /mmHg T0 | \n\t\t\t\t\t\t\t914,500 | \n\t\t\t\t\t\t\t915,500 | \n\t\t\t\t\t\t\t449,5000 | \n\t\t\t\t\t\t\t-0,00739 | \n\t\t\t\t\t\t\t0,994102 | \n\t\t\t\t\t\t
PCO2 /mmHg T1 | \n\t\t\t\t\t\t\t953,500 | \n\t\t\t\t\t\t\t876,500 | \n\t\t\t\t\t\t\t411,5000 | \n\t\t\t\t\t\t\t0,56920 | \n\t\t\t\t\t\t\t0,569221 | \n\t\t\t\t\t\t
PCO2 /mmHg T2 | \n\t\t\t\t\t\t\t912,500 | \n\t\t\t\t\t\t\t917,500 | \n\t\t\t\t\t\t\t447,5000 | \n\t\t\t\t\t\t\t-0,03696 | \n\t\t\t\t\t\t\t0,970516 | \n\t\t\t\t\t\t
PCO2 /mmHg T3 | \n\t\t\t\t\t\t\t919,000 | \n\t\t\t\t\t\t\t911,000 | \n\t\t\t\t\t\t\t446,0000 | \n\t\t\t\t\t\t\t0,05914 | \n\t\t\t\t\t\t\t0,952842 | \n\t\t\t\t\t\t
Mann-Whitney U test for parametres of intraoperative monitoring.
Group | \n\t\t\t\t\t\t\tMonitoring | \n\t\t\t\t\t\t\tSS | \n\t\t\t\t\t\t\tdf | \n\t\t\t\t\t\t\tMS | \n\t\t\t\t\t\t\tSS | \n\t\t\t\t\t\t\tDf | \n\t\t\t\t\t\t\tMS | \n\t\t\t\t\t\t\tF | \n\t\t\t\t\t\t\tP | \n\t\t\t\t\t\t
А | \n\t\t\t\t\t\t\tHR/min | \n\t\t\t\t\t\t\t236,425 | \n\t\t\t\t\t\t\t3 | \n\t\t\t\t\t\t\t78,8083 | \n\t\t\t\t\t\t\t17165,177 | \n\t\t\t\t\t\t\t116 | \n\t\t\t\t\t\t\t147,97566 | \n\t\t\t\t\t\t\t0,5326 | \n\t\t\t\t\t\t\t0,660834 | \n\t\t\t\t\t\t
MAP/mmHg | \n\t\t\t\t\t\t\t1422,1588 | \n\t\t\t\t\t\t\t3 | \n\t\t\t\t\t\t\t474,0528 | \n\t\t\t\t\t\t\t16113,43 | \n\t\t\t\t\t\t\t116 | \n\t\t\t\t\t\t\t138,9089 | \n\t\t\t\t\t\t\t3,4127 | \n\t\t\t\t\t\t\t0,019858*8 | \n\t\t\t\t\t\t|
RR/min | \n\t\t\t\t\t\t\t369,000 | \n\t\t\t\t\t\t\t3 | \n\t\t\t\t\t\t\t123,0000 | \n\t\t\t\t\t\t\t36,87 | \n\t\t\t\t\t\t\t116 | \n\t\t\t\t\t\t\t0,3178 | \n\t\t\t\t\t\t\t387,0163 | \n\t\t\t\t\t\t\t0,000000* | \n\t\t\t\t\t\t|
SAT% | \n\t\t\t\t\t\t\t429,425 | \n\t\t\t\t\t\t\t3 | \n\t\t\t\t\t\t\t143,1417 | \n\t\t\t\t\t\t\t1745,17 | \n\t\t\t\t\t\t\t116 | \n\t\t\t\t\t\t\t15,0445 | \n\t\t\t\t\t\t\t9,5145 | \n\t\t\t\t\t\t\t0,000011* | \n\t\t\t\t\t\t|
PCO2 /mmHg | \n\t\t\t\t\t\t\t20,852 | \n\t\t\t\t\t\t\t3 | \n\t\t\t\t\t\t\t6,9508 | \n\t\t\t\t\t\t\t106,57 | \n\t\t\t\t\t\t\t116 | \n\t\t\t\t\t\t\t0,9187 | \n\t\t\t\t\t\t\t7,5659 | \n\t\t\t\t\t\t\t0,000115* | \n\t\t\t\t\t\t|
B | \n\t\t\t\t\t\t\tHR/min | \n\t\t\t\t\t\t\t741,6667 | \n\t\t\t\t\t\t\t3 | \n\t\t\t\t\t\t\t247,2222 | \n\t\t\t\t\t\t\t20349,13 | \n\t\t\t\t\t\t\t116 | \n\t\t\t\t\t\t\t175,4236 | \n\t\t\t\t\t\t\t1,4093 | \n\t\t\t\t\t\t\t0,243640 | \n\t\t\t\t\t\t
MAP/mmHg | \n\t\t\t\t\t\t\t119,4917 | \n\t\t\t\t\t\t\t3 | \n\t\t\t\t\t\t\t39,8306 | \n\t\t\t\t\t\t\t25576,10 | \n\t\t\t\t\t\t\t116 | \n\t\t\t\t\t\t\t220,4836 | \n\t\t\t\t\t\t\t0,1807 | \n\t\t\t\t\t\t\t0,909345 | \n\t\t\t\t\t\t|
RR/min | \n\t\t\t\t\t\t\t333,0250 | \n\t\t\t\t\t\t\t3 | \n\t\t\t\t\t\t\t111,0083 | \n\t\t\t\t\t\t\t62,10 | \n\t\t\t\t\t\t\t116 | \n\t\t\t\t\t\t\t0,5353 | \n\t\t\t\t\t\t\t207,3586 | \n\t\t\t\t\t\t\t0,000000* | \n\t\t\t\t\t\t|
SAT% | \n\t\t\t\t\t\t\t408,4250 | \n\t\t\t\t\t\t\t3 | \n\t\t\t\t\t\t\t136,1417 | \n\t\t\t\t\t\t\t1267,57 | \n\t\t\t\t\t\t\t116 | \n\t\t\t\t\t\t\t10,9273 | \n\t\t\t\t\t\t\t12,4589 | \n\t\t\t\t\t\t\t0,000000* | \n\t\t\t\t\t\t|
PCO2 /mmHg | \n\t\t\t\t\t\t\t22,8277 | \n\t\t\t\t\t\t\t3 | \n\t\t\t\t\t\t\t7,6092 | \n\t\t\t\t\t\t\t112,34 | \n\t\t\t\t\t\t\t116 | \n\t\t\t\t\t\t\t0,9685 | \n\t\t\t\t\t\t\t7,8570 | \n\t\t\t\t\t\t\t0,000081* | \n\t\t\t\t\t\t
Analysis of Variance –ANOVA test.
The average values of RR/min. in both groups show rise during operative monitoring. The differences in these values are insignificant between groups A and B, and statistically significant inside groups (p=0,00000*) (Tables 6,7). This difference doesn’t have clinical importance for the aims of the study (since respiratory rate during OLV is deliberately increased in all patients, in order to decrease the value of PaCO2).
\n\t\t\t\tThe average values of SAT% in both studied groups demonstrate fall during the operative monitoring. The difference in these values is statistically irrelevant between groups A and B; however, the dissimilarities inside groups A and B is statisticaly significant for p=0,000011* and p=0,00000* (Tables 6, 7), showing decrease in arterial oxygen saturation during OLV in patients from both groups.
\n\t\t\t\tThe average values of PCO2/mmHg in both groups demonstrate increase during operative monitoring. The differences in these values are statistically insignificant between groups A and B; on the other hand, inside groups A and B, the discrepancy is statisticaly significant for p=0,000115* and p=0,000081* (Tables 6, 7). This inequality illustrates the phenomenon of so called
The average values of PaO2 in both studied groups show fall during the operative monitoring. The differences in these values between groups A and B are statistically insignificant. Inside groups A and B the dissimilarities are statistically significant for p=0,0000021* and p=0,000000*. The additionally performed post-hoc test for PaO2 in group A and B shows which differences (i.e. measuring times) are statistically relevant (Tables 8, 9, 10, 12).
\n\t\t\t\tParametres from intraoperative gas status. (a) – PaO2 in both groups. (b) – SaO2 in both groups.
Parameters | \n\t\t\t\t\t\t\tRank Sum-А | \n\t\t\t\t\t\t\tRank Sum-B | \n\t\t\t\t\t\t\tU | \n\t\t\t\t\t\t\tZ | \n\t\t\t\t\t\t\tp-level | \n\t\t\t\t\t\t
PaO2 T0 | \n\t\t\t\t\t\t\t973,000 | \n\t\t\t\t\t\t\t857,0000 | \n\t\t\t\t\t\t\t392,0000 | \n\t\t\t\t\t\t\t0,857497 | \n\t\t\t\t\t\t\t0,391171 | \n\t\t\t\t\t\t
PaO2 T1 | \n\t\t\t\t\t\t\t961,000 | \n\t\t\t\t\t\t\t869,0000 | \n\t\t\t\t\t\t\t404,0000 | \n\t\t\t\t\t\t\t0,680084 | \n\t\t\t\t\t\t\t0,496452 | \n\t\t\t\t\t\t
PaO2 T2 | \n\t\t\t\t\t\t\t1019,500 | \n\t\t\t\t\t\t\t810,5000 | \n\t\t\t\t\t\t\t345,5000 | \n\t\t\t\t\t\t\t1,544972 | \n\t\t\t\t\t\t\t0,122354 | \n\t\t\t\t\t\t
PaO2 T3 | \n\t\t\t\t\t\t\t914,000 | \n\t\t\t\t\t\t\t916,0000 | \n\t\t\t\t\t\t\t449,0000 | \n\t\t\t\t\t\t\t-0,014784 | \n\t\t\t\t\t\t\t0,988204 | \n\t\t\t\t\t\t
SaO2 T0 | \n\t\t\t\t\t\t\t947,000 | \n\t\t\t\t\t\t\t883,0000 | \n\t\t\t\t\t\t\t418,0000 | \n\t\t\t\t\t\t\t0,473102 | \n\t\t\t\t\t\t\t0,636141 | \n\t\t\t\t\t\t
SaO2 T1 | \n\t\t\t\t\t\t\t935,000 | \n\t\t\t\t\t\t\t895,0000 | \n\t\t\t\t\t\t\t430,0000 | \n\t\t\t\t\t\t\t0,295689 | \n\t\t\t\t\t\t\t0,767468 | \n\t\t\t\t\t\t
SaO2 T2 | \n\t\t\t\t\t\t\t978,500 | \n\t\t\t\t\t\t\t851,5000 | \n\t\t\t\t\t\t\t386,5000 | \n\t\t\t\t\t\t\t0,938811 | \n\t\t\t\t\t\t\t0,347829 | \n\t\t\t\t\t\t
SaO2 T3 | \n\t\t\t\t\t\t\t899,000 | \n\t\t\t\t\t\t\t931,0000 | \n\t\t\t\t\t\t\t434,0000 | \n\t\t\t\t\t\t\t-0,236551 | \n\t\t\t\t\t\t\t0,813005 | \n\t\t\t\t\t\t
Mann-Whitney U test.
Group | \n\t\t\t\t\t\t\tParameters | \n\t\t\t\t\t\t\tSS | \n\t\t\t\t\t\t\tdf | \n\t\t\t\t\t\t\tMS | \n\t\t\t\t\t\t\tSS | \n\t\t\t\t\t\t\tdf | \n\t\t\t\t\t\t\tMS | \n\t\t\t\t\t\t\tF | \n\t\t\t\t\t\t\tp | \n\t\t\t\t\t\t
А | \n\t\t\t\t\t\t\tPaO2 | \n\t\t\t\t\t\t\t1561,721 | \n\t\t\t\t\t\t\t3 | \n\t\t\t\t\t\t\t520,5735 | \n\t\t\t\t\t\t\t5550,851 | \n\t\t\t\t\t\t\t116 | \n\t\t\t\t\t\t\t47,85217 | \n\t\t\t\t\t\t\t10,87879 | \n\t\t\t\t\t\t\t0,0000021 | \n\t\t\t\t\t\t
SaO2 | \n\t\t\t\t\t\t\t520,737 | \n\t\t\t\t\t\t\t3 | \n\t\t\t\t\t\t\t173,5789 | \n\t\t\t\t\t\t\t2047,983 | \n\t\t\t\t\t\t\t116 | \n\t\t\t\t\t\t\t17,65503 | \n\t\t\t\t\t\t\t9,83170 | \n\t\t\t\t\t\t\t0,000008 | \n\t\t\t\t\t\t|
B | \n\t\t\t\t\t\t\tPaO2 | \n\t\t\t\t\t\t\t1358,527 | \n\t\t\t\t\t\t\t3 | \n\t\t\t\t\t\t\t452,8423 | \n\t\t\t\t\t\t\t2778,338 | \n\t\t\t\t\t\t\t116 | \n\t\t\t\t\t\t\t23,95119 | \n\t\t\t\t\t\t\t18,90688 | \n\t\t\t\t\t\t\t0,000000 | \n\t\t\t\t\t\t
SaO2 | \n\t\t\t\t\t\t\t652,413 | \n\t\t\t\t\t\t\t3 | \n\t\t\t\t\t\t\t217,4710 | \n\t\t\t\t\t\t\t1334,600 | \n\t\t\t\t\t\t\t116 | \n\t\t\t\t\t\t\t11,50518 | \n\t\t\t\t\t\t\t18,90201 | \n\t\t\t\t\t\t\t0,000000 | \n\t\t\t\t\t\t
Analysis of Variance –ANOVA test.
PaO2 | \n\t\t\t\t\t\t\tT0 | \n\t\t\t\t\t\t\tT1 | \n\t\t\t\t\t\t\tT2 | \n\t\t\t\t\t\t\tT3 | \n\t\t\t\t\t\t
T0 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | 0,075231 | \n\t\t\t\t\t\t\t0,000139* | \n\t\t\t\t\t\t\t0,000352* | \n\t\t\t\t\t\t
T1 | \n\t\t\t\t\t\t\t0,075231 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | 0,024138* | \n\t\t\t\t\t\t\t0,265002 | \n\t\t\t\t\t\t
T2 | \n\t\t\t\t\t\t\t0,000139* | \n\t\t\t\t\t\t\t0,024138* | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | 0,719175 | \n\t\t\t\t\t\t
T3 | \n\t\t\t\t\t\t\t0,000352* | \n\t\t\t\t\t\t\t0,265002 | \n\t\t\t\t\t\t\t0,719175 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t |
Post- hoc - Tukey honest significant difference (HSD) test for Group A - PaO2.
SaO2 | \n\t\t\t\t\t\t\tT0 | \n\t\t\t\t\t\t\tT1 | \n\t\t\t\t\t\t\tT2 | \n\t\t\t\t\t\t\tT3 | \n\t\t\t\t\t\t
T0 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | 0,371996 | \n\t\t\t\t\t\t\t0,000142* | \n\t\t\t\t\t\t\t0,004258* | \n\t\t\t\t\t\t
T1 | \n\t\t\t\t\t\t\t0,371996 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | 0,003861* | \n\t\t\t\t\t\t\t0,259930 | \n\t\t\t\t\t\t
T2 | \n\t\t\t\t\t\t\t0,000142* | \n\t\t\t\t\t\t\t0,003861* | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | 0,355108 | \n\t\t\t\t\t\t
T3 | \n\t\t\t\t\t\t\t0,004258* | \n\t\t\t\t\t\t\t0,259930 | \n\t\t\t\t\t\t\t0,355108 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t |
Post-hoc - Tukey honest significant difference (HSD) test for Group A - SaO2.
PaO2 | \n\t\t\t\t\t\t\tT0 | \n\t\t\t\t\t\t\tT1 | \n\t\t\t\t\t\t\tT2 | \n\t\t\t\t\t\t\tT3 | \n\t\t\t\t\t\t
T0 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | 0,045269* | \n\t\t\t\t\t\t\t0,000137* | \n\t\t\t\t\t\t\t0,000158* | \n\t\t\t\t\t\t
T1 | \n\t\t\t\t\t\t\t0,045269* | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | 0,000202* | \n\t\t\t\t\t\t\t0,135773 | \n\t\t\t\t\t\t
T2 | \n\t\t\t\t\t\t\t0,000137* | \n\t\t\t\t\t\t\t0,000202* | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | 0,086017 | \n\t\t\t\t\t\t
T3 | \n\t\t\t\t\t\t\t0,000158* | \n\t\t\t\t\t\t\t0,135773 | \n\t\t\t\t\t\t\t0,086017 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t |
Post-hoc - Tukey honest significant difference (HSD) test for Group B - PaO2.
SaO2 | \n\t\t\t\t\t\t\tT0 | \n\t\t\t\t\t\t\tT1 | \n\t\t\t\t\t\t\tT2 | \n\t\t\t\t\t\t\tT3 | \n\t\t\t\t\t\t
T0 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | 0,503957 | \n\t\t\t\t\t\t\t0,000137* | \n\t\t\t\t\t\t\t0,002297* | \n\t\t\t\t\t\t
T1 | \n\t\t\t\t\t\t\t0,503957 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | 0,000137* | \n\t\t\t\t\t\t\t0,115369 | \n\t\t\t\t\t\t
T2 | \n\t\t\t\t\t\t\t0,000137* | \n\t\t\t\t\t\t\t0,000137* | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | 0,005223* | \n\t\t\t\t\t\t
T3 | \n\t\t\t\t\t\t\t0,002297* | \n\t\t\t\t\t\t\t0,115369 | \n\t\t\t\t\t\t\t0,005223* | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t |
Post-hoc - Tukey honest significant difference (HSD) test for Group B - SaO2.
The average values of SaO2 in both groups illustrate decrease during the operative monitoring. The difference between these values among groups A and B is statistically insignificant. Inside groups A and B, the discrepancies are statistically relevant for p=0,000008* and p=0,000000*. The additionally performed post-hoc test for SaO2 in groups A and B demonstrates which differences (i.e. measuring times) are statistically relevant (Tables 8, 9, 11, 13).
\n\t\t\t\tThe acquired statistically significant differences for PaO2 and SaO2 inside the groups A and B show that after some time of OLV initiation (after 10 min.) hypoxia develops, with decrease of the values of PaO2 and SaO2.
\n\t\t\t\tThe absence of statistically relevant variation for PaO2 and SaO2 among the groups A and B demonstrates that TEA doesn’t provoke augmentation of hypoxia during OLV.
\n\t\t\t\tAverage intraoperative values of intrapulmonary shunt – Qs/Qt in both groups.
Parameters | \n\t\t\t\t\t\t\tRank Sum-А | \n\t\t\t\t\t\t\tRank Sum-B | \n\t\t\t\t\t\t\tU | \n\t\t\t\t\t\t\tZ | \n\t\t\t\t\t\t\tp-level | \n\t\t\t\t\t\t
Qs/Qt T0 | \n\t\t\t\t\t\t\t915,0000 | \n\t\t\t\t\t\t\t915,0000 | \n\t\t\t\t\t\t\t450,0000 | \n\t\t\t\t\t\t\t0,000000 | \n\t\t\t\t\t\t\t1,000000 | \n\t\t\t\t\t\t
Qs/Qt T1 | \n\t\t\t\t\t\t\t925,0000 | \n\t\t\t\t\t\t\t905,0000 | \n\t\t\t\t\t\t\t440,0000 | \n\t\t\t\t\t\t\t0,147844 | \n\t\t\t\t\t\t\t0,882466 | \n\t\t\t\t\t\t
Qs/Qt T2 | \n\t\t\t\t\t\t\t853,5000 | \n\t\t\t\t\t\t\t976,5000 | \n\t\t\t\t\t\t\t388,5000 | \n\t\t\t\t\t\t\t-0,909242 | \n\t\t\t\t\t\t\t0,363223 | \n\t\t\t\t\t\t
Qs/Qt T3 | \n\t\t\t\t\t\t\t939,0000 | \n\t\t\t\t\t\t\t891,0000 | \n\t\t\t\t\t\t\t426,0000 | \n\t\t\t\t\t\t\t0,354826 | \n\t\t\t\t\t\t\t0,722720 | \n\t\t\t\t\t\t
Mann-Whitney U test.
Group | \n\t\t\t\t\t\t\tParameters | \n\t\t\t\t\t\t\tSS | \n\t\t\t\t\t\t\tdf | \n\t\t\t\t\t\t\tMS | \n\t\t\t\t\t\t\tSS | \n\t\t\t\t\t\t\tdf | \n\t\t\t\t\t\t\tMS | \n\t\t\t\t\t\t\tF | \n\t\t\t\t\t\t\tp | \n\t\t\t\t\t\t
А | \n\t\t\t\t\t\t\tQs/Qt | \n\t\t\t\t\t\t\t801,6449 | \n\t\t\t\t\t\t\t3 | \n\t\t\t\t\t\t\t267,2150 | \n\t\t\t\t\t\t\t5133,088 | \n\t\t\t\t\t\t\t116 | \n\t\t\t\t\t\t\t44,25076 | \n\t\t\t\t\t\t\t6,038653 | \n\t\t\t\t\t\t\t0,000739 | \n\t\t\t\t\t\t
B | \n\t\t\t\t\t\t\tQs/Qt | \n\t\t\t\t\t\t\t1692,620 | \n\t\t\t\t\t\t\t3 | \n\t\t\t\t\t\t\t564,2068 | \n\t\t\t\t\t\t\t5648,059 | \n\t\t\t\t\t\t\t116 | \n\t\t\t\t\t\t\t48,69017 | \n\t\t\t\t\t\t\t11,58769 | \n\t\t\t\t\t\t\t0,000001 | \n\t\t\t\t\t\t
Analysis of Variance –ANOVA test.
Qs/Qt | \n\t\t\t\t\t\t\tT0 | \n\t\t\t\t\t\t\tT1 | \n\t\t\t\t\t\t\tT2 | \n\t\t\t\t\t\t\tT3 | \n\t\t\t\t\t\t
T0 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | 0,725131 | \n\t\t\t\t\t\t\t0,000563* | \n\t\t\t\t\t\t\t0,320393 | \n\t\t\t\t\t\t
T1 | \n\t\t\t\t\t\t\t0,725131 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | 0,014827* | \n\t\t\t\t\t\t\t0,907021 | \n\t\t\t\t\t\t
T2 | \n\t\t\t\t\t\t\t0,000563* | \n\t\t\t\t\t\t\t0,014827* | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | 0,086875 | \n\t\t\t\t\t\t
T3 | \n\t\t\t\t\t\t\t0,320393 | \n\t\t\t\t\t\t\t0,907021 | \n\t\t\t\t\t\t\t0,086875 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t |
Post-hoc - Tukey honest significant difference (HSD) test for Group A - Qs/Qt.
Qs/Qt | \n\t\t\t\t\t\t\tT0 | \n\t\t\t\t\t\t\tT1 | \n\t\t\t\t\t\t\tT2 | \n\t\t\t\t\t\t\tT3 | \n\t\t\t\t\t\t
T0 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | 0,776395 | \n\t\t\t\t\t\t\t0,000137* | \n\t\t\t\t\t\t\t0,152861 | \n\t\t\t\t\t\t
T1 | \n\t\t\t\t\t\t\t0,776395 | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | 0,000202* | \n\t\t\t\t\t\t\t0,648599 | \n\t\t\t\t\t\t
T2 | \n\t\t\t\t\t\t\t0,000137* | \n\t\t\t\t\t\t\t0,000202* | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t | 0,005223* | \n\t\t\t\t\t\t
T3 | \n\t\t\t\t\t\t\t0,152861 | \n\t\t\t\t\t\t\t0,648599 | \n\t\t\t\t\t\t\t0,005223* | \n\t\t\t\t\t\t\t\n\t\t\t\t\t\t |
Post-hoc - Tukey honest significant difference (HSD) test for Group B - Qs/Qt.
The average values of Qs/Qt in both inspected groups illustrate dynamic trend during the operative monitoring. In group A it begins with the value < 1 in Т0, increases in Т2, and then decreases in Т3. In group B it also starts with a value < 1 in Т0, grows up in Т2, and then the value drops. The difference between the average values of Qs/Qt recorded among groups A and B is statistically insignificant. On the other hand, the variations in these values inside groups A and B are statistically relevant for p=0,000739* and p=0,000001*. With the additionally performed post-hoc test for Qs/Qt in group A it is evident that the difference is statistically significant between Т0 and Т2 and Т1 and Т2. The completed post-hoc test for Qs/Qt in group B shows that the dissimilarity is statistically relevant between Т0 and Т2, Т1 and Т2, as well as Т2 and Т3 (Tables 14-17).
\n\t\t\t\tThe obtained statistically significant differences for Qs/Qt inside groups A and B demonstrate that some time after beginning of OLV (after 10 min.) hypoxia develops, with an increase of the value of intrapulmonary shunt.
\n\t\t\t\tThe nonexistence of statistically relevant dissimilarity for Qs/Qt among the groups A and B, confirms that TEA neither leads to intensification of hypoxia, nor to an increase of the shunt during OLV.
\n\t\t\tOLV creates an obligatory transpulmonary shunt through the atelectatic lung. Passive (gravitation and surgical manipulation) and active (HPV) mechanisms minimize the redirection of blood flow towards the atelectatic lung, thus preventing the fall of PaO2; yet, the most important turn of the blood flow towards the dependent lung is caused by HPV (39).
\n\t\t\tHurford et al. in their study (40) tested the hypothesis that during OLV is more likely to come to intraoperative hypoxia if there is bigger pulmonary blood flow in the operated lung before surgery. In their study they examinated 30 patients with previously performed ventilation-perfusion scan preoperatively, who underwent a thoracic procedure in lateral decubitus position with OLV. The percentage of blood flow in the operated lung seen on the preoperative perfusion scan reversely correlated with PaO2, 10 minutes after initiating of OLV (р=-.72). If the percentage of blood flow in the operated lung on the preoperative scan was greater than 45%, the probability for hypoxemia (PaO2 < 75 mm Hg) was bigger. Since the preoperative regional ventilation in these patients was equivalent with the perfusion, also the percentage of preoperative ventilation correlated reversely with PaO2 after 10 min. of OLV initiation (р=-.73).
This is opposite of the results of Slinger et al. (41). In their study they discovered that one equation with three variables [PaO2 during intraoperative two lung ventilation in lateral decubitus position, side of surgery and preoperative relation of forced expiratory volume in 1st second (FEV1) and vital capacity (VC)], could be used to predict (р =.73) PaO2 during OLV, using CPAP (continuous positive airway pressure) in non-ventilated lung. However, Katz et al. (51) agreed with the findings of Hurford et al. (40) that routine preoperative arterial gas analysis and pulmonary functional tests do not anticipate precisely which patients are under risk of developing hypoxia during OLV.
\n\t\t\tOur results from this study verify that preoperative arterial gas analysis, as well as FVC and FEV1, can’t be perceived as confident evidence that the exact patient will develop hypoxia of bigger or smaller extent during OLV.
\n\t\t\tPrevious clinical research studies showed controversial results regarding oxygenation, shunt fraction and hemodynamic parameters during OLV (42, 43, 44, 45).
\n\t\t\tSpies et al. (42) compared TIVA with propofol (10 mg/kg/h) versus 1 MAC enflurane in patients during thoracotomy. Cardiac output and shunt significantly increased when TLV was converted to OLV, and PaO2 decreased.
\n\t\t\tVan Keer et al. (43) studied 10 patients who underwent thoracotomy. Their anesthesia was maintained with continuous iv infusion of propofol (10 mg/kg/h). No changes were noticed concerning cardiac output, shunt and PaO2, during TLV (two lung ventilation) and OLV. This fact could be due to methodological differences because all the measurements for the duration of OLV were initiated before opening of the thoracic cavity.
\n\t\t\tSteegers et al. (44) examined 14 patients who were about to undertake lobectomy, in intravenous general anesthesia with continuous infusion of propofol (6-9 mg/kg/h). The shunt fraction and PaO2 didn’t differ during OLV compared with TLV. Their study doesn’t include any basic data, like cardiac output. Changes in these hemodynamic parameters would cause secondary alterations in pulmonary circulation.
\n\t\t\tKellow et al. (45) studied patients who underwent thoracotomy and noticed significant increase of cardiac index and shunt fraction when TLV was switched to OLV. Nevertheless, interpretation of the shunt fraction is limited as the patients were ventilated with 50% nitrous oxide in oxygen and no PaO2 was measured.
\n\t\t\tSeveral studies, including the one of Slinger et al. (46), demonstrated that the beginning of hypoxia is, approximately, about 5-10 min. after initiating of OLV and reaches maximum after 15 min. This matches the time needed for complete absorption of the gases (oxygen and nitrous oxide) from closed cavities, when blood flow is maintained. PaO2 and Qs/Qt usually begin to return towards values existing during TLV about 30 min. after commencing OLV. That is the period required for development of the compensatory mechanism called HPV (hypoxic pulmonary vasoconstriction) and redirection of blood flow away from the atelectatic lung. As a result, the shunt fraction will also decrease.
\n\t\t\tOur results confirmed the conclusions from the last mentioned studies - that during conversion from TLV to OLV in patient placed in lateral decubitus position throughout thoracotomy / thoracoscopy, it comes to decrease in arterial oxygenation, as well as increase in shunt fraction. Namely, the average values of PaO2 in two examinated groups of patients fall down throughout the operative monitoring (group А from 23,29+/-7,97 kPa in TLV, to 13,78+/-5,84 kPa after 10 min. of OLV, and returns to 15,66+/-6,62 kPa, 30 min. after OLV; and group B – from 20,98+/-4,68 kPa during TLV, to 11,87+/-4,95 kPa, 10 min. after OLV, and returns to 14,88+/-4,45 kPa 30 min. after OLV); the average values of SaO2 in the two groups show decrease during operative monitoring (group А - from 99,06+/-0,81% during TLV, to 93,52+/-6,03%, 10 min. after OLV, and returns to 95,31+/-4,62%, 30 min. after OLV; and group B – from 99,09+/-0,6% during TLV, to 92,92+/-5,2%, 10 min. after OLV, and returns to 95,89+/-3,78%, 30 min. after OLV); also, the average values of Qs/Qt in two examinated groups demonstrate dynamic changes during operative monitoring – in the group A begins with quantity < 1% in T0, increases to 8,03+/-10,59% in T2, and in T3 decreases to 3,94+/-6,21%; in the group B, it begins with value <1% in T0, increases to 10,93+/-10,8% in T2, and in T3 decreases to 4,82+/-7,58%. The statistically significant differences for PaO2, SaO2 and Qs/Qt, inside the groups A and B, show that after a certain time from initiating of OLV (after 10 min.), hypoxia develops with drop of values of PaO2 and SaO2, as well as increase of the quantity of intrapulmonary shunt. The subsequent decrease of Qs/Qt in the fourth measurement (T3), illustrates the development of HPV in this period of time, over and above the decrease of the shunt fraction 30 min. after the beginning of OLV in lateral decubitus position during thoracotomy / thoracoscopy.
\n\t\t\tOther factors that could reduce PaO2 are cardio-vascular and hemodynamic effects of thoracic epidural anesthesia (ТЕА): the decline of HR, SAP, stroke volume and cardiac output (CO), as a result of the blockade of sympathetic nervous system. Even more, the systemic consequences from the absorption of local anesthetics could lead to circulatory changes, like reduction of CO (47,48).
\n\t\t\tThe results in our study demonstrated that the average values of HR/min. in both groups showed increase during operative monitoring from T0 to T3 (group А-85,56+/-12,53 to 88,53+/-12,19 and group B -76,16+/-13,15 to 81,6+/-13,49). The difference in average values for HR/min. recorded between groups A and B is statistically significant in T0 and T3 (p<0,05), whilst in T1 and T2 it isn’t statistically significant (p>0,05). Inside the groups A and B, the variation in average values of HR/min. is statistically non-significant (p>0,05). But, as it is demonstrated by the comparison of the data from intraoperative arterial gas analysis between the groups A and B, obviously this dissimilarity for HR/min. which is a result of the depth of anesthesia, as well as administration of TEA in group B, doesn’t lead to an important difference in arterial oxygenation and shunt fraction between two groups. The other hemodynamic parameter which is intraoperatively monitored in our patients, SAP/mmHg, doesn’t differ considerably among two groups, which advocates even more the previous statement – that the mentioned hemodynamic diversity in our patients doesn’t have any significance in the process of delivering the conclusions in this study.
\n\t\t\tThe degree of difficulty of the disease in non-dependent lung is also a critical determinant of the quantity of blood flow in non-dependent lung. If this lung is seriously ‘diseased’, there could be a preoperative fixed reduction of its blood flow, thus its ‘collapse’ may not cause considerable increase in shunt fraction.
\n\t\t\tIn fact, Hurford et al. (40) in their prospective study provided evidence that the patients who had in affected lung less than 45% of their pulmonary blood flow, had notably smaller risk for development of hypoxia during OLV.
\n\t\t\tAs literature shows, the administration of sodium nitroprussid or nitroglycerin – which is supposed to diminish hypoxic pulmonary vasoconstriction (HPV) in patients with COPD (chronic obstructive pulmonary disease), who have fixed reduction of their pulmonary vascular bed, doesn’t initiate enhancement of the shunt. This observation supports the fact that the affected (diseased) pulmonary vasculature is incapable to develop HPV (49, 50). On the other hand, these medicaments augment the shunt fraction in patients with acute regional lung disease, who otherwise have normal pulmonary vascular bed.
This statement was confirmed with our patients also. In three patients with diagnosis Ca esophagi who underwent thoracotomy with intraoperative utilization of OLV (one in group A and two in group B), are recorded values of Qs/Qt during OLV that are very close to the maximal registered ones in two groups of patients. However, this clinical feature could be only understood as higher probability, but not as a rule.
\n\t\t\tOLV has much less effect on PaCO2 than on PaO2 (52). During clinical use of OLV, the respiratory rate is adjusted in order to maintain a ‘safe’ level of elimination of CO2, guided by the measurements of capnography (End-tidal CO2) and/or arterial gas analysis. Sometimes the minute ventilation achieved by employing these ventilatory parameters could be minor than the ideal one. The minute ventilation could be limited due to air trapping, not only in patients with COPD, but also in patients with normal preoperative lung function. Controlled hypoventilation is called permissive hypercapnia; furthermore, it is demonstrated as a harmless technique in patients with ARDS (acute respiratory distress syndrome), even with values of pH of 7.15 and of PaCO2 up to 80 mm Hg (10,66 kPa) (53). Maintaining adequate oxygenation (PaO2 > 60 mm Hg, i.e. 8 kPa) is crucial during this period. The secure level of acute hypercapnia for patients under general anesthesia is not known, but the values in this range could be adequate.
\n\t\t\tIn our study, the average (middling) values of PaCO2/kPa in both examinated groups show increase during the operative monitoring (group А and B - from 5,4 to 6,4 kPa). The difference in average values of PaCO2/kPa between two groups (А and B) is not statistically significant (p>0,05), whereas this variation inside the groups A and B is statistically significant (p<0,05). Precisely this difference illustrates the appearance of already mentioned permissive hypercapnia during OLV (which is expected, although RR/min. was increased to facilitate preservation of PaCO2 in normal ranges).
\n\t\t\tIn experimental studies using thoracic epidural anesthesia, TEA didn’t inhibit HPV (36, 54). Ishibe et al. (36) demonstrated enhanced response of HPV and improved arterial oxygenation during OLV and TEA in dogs, which was a result of decreased PvO2 and CO owing to the blockade of sympathetic nerve activity. The sensitivity of these variables depends on the extent of lung tissue exposed to hypoxia. In this study the authors used left lower lobe-LLL, which represents approximately one sixth of total lung volume. The hypoxic ventilation reduced the blood flow of LLL and PaO2. The extent of these changes is “realistic”, if the pulmonary artery of LLL is supposed to contract maximally. It is obvious that TEA inhibited sympathetic efferent nerve activity in dogs from this study. Because of that, it is probable that TEA-induced changes in systemic hemodynamics resulted in enhancement of HPV, since it is well known that decrease of CO, PAP and PvO2 augment HPV response. However, in this study, the effects of TEA-induced enhancement of HPV on pulmonary hemodynamics and systemic oxygenation were minimal, most probably because the relative extent of hypoxic lung tissue was minor and the intensity of basic HPV response was already near the maximal level before commencement of TEA.
\n\t\t\tBrimioulle et al. (54) noticed enhancement of HPV during epidural blockade, but without an effect of the previous α- or β-blockade, meaning that all its consequences on pulmonary circulation are connected with sympathetic blockade.
\n\t\t\tOn the contrary, Garutti et al. (55) observed higher shunt fractions (39,5%) and lower values of PaO2 (120 mmHg) during OLV in TEA group, compared with TIVA group in patients who underwent thoracotomy. They concluded that TEA could not be recommended for use in thoracic surgery when OLV is needed (55). Nonetheless, their study has great limitations. CO and PvO2, which are important factors for assessment of the impact of HPV, were not measured. The venous blood for gas analysis used to determine shunt fraction, was taken using central venous catheter (55). ТЕА was combined with propofol. Kasaba et al. (56) reported that hypotensive effects of propofol are additive to those of epidural anesthesia. Garuti et al. (55) used iv ephedrine only in TEA group when systolic arterial pressure dropped below 100 mmHg. Ephedrine is partial α and β agonist (57). This explains the similarity of compared values of HR and SAP in both groups, but does not make clear the worst oxygenation, because it seems that ephedrine provides an increase of PaO2 without alteration of intrapulmonary shunt during OLV in thoracic surgery. For the reason that copies of β-adrenergic subtype are found in porcine tissue of the lungs and left ventricle (β1: 67/72; β2: 33/28; β3: 2/25) (58), it can’t be excluded that augmentation of cardiac output through β-receptor activity could be responsible for increasing the shunt fraction and poorer oxygenation in the study of Garutti et al. (55).
\n\t\t\tHackenberg et al. (59), by using multiple elimination of inert gas for analysis of inequality of ventilation/perfusion matching, demonstrated that TEA didn’t influenced the development of shunt, before and after induction in general anesthesia.
\n\t\t\tThe reason for the eventual fall of PaO2 while using TEA could be as follows: pulmonary vasculature is innervated by autonomous nervous system. Stimulation of the sympathetic nerves in the lungs causes enhancement of PVR (pulmonary vascular resistance), as a result of the activation of α-receptors in pulmonary vascular bed. The mediator released on the sympathetic nerve endings is norepinephrine (47, 48, 54). The blockade of the sympathetic nervous system with α-adrenergic antagonists or β-adrenergic agonists diminishes HPV, while β-adrenergic antagonists enhance this response. So, maybe the actual factor is the block of the activity of thoracic sympathetic system over pulmonary vascular response.
\n\t\t\tHowever, previously mentioned studies, like the one of Ishibe et al. (36), demonstrate that TEA didn’t affect the primary pulmonary vascular tone during OLV, but slightly augmented the redistribution of blood flow away from hypoxic lobe and towards other well oxygenated lung areas.
\n\t\t\tThe explanation lies in the fact that most of these studies were not completed under same conditions (for example, anesthetized patients, lateral decubitus position, atelectatic lung tissue).
\n\t\t\tOur results show that no statistically significant difference exists (p>0,05) for Qs/Qt % between the groups A and B in all stages of measurements. This points to the fact that when two anesthetic techniques are compared, the use of combined anesthesia (GA plus TEA with local anesthetics) for thoracic surgery doesn’t lead to bigger reduction of PaO2 and greater increase of intrapulmonary shunt during OLV, than intravenous GA.
\n\t\tBased on the experiences of other authors from literature, as well as on our own research, we would provide following recommendations for safe anesthesia during OLV, regarding
OLV should be established in a way that the lungs would inflate adequately, but minimizing the intra-alveolar pressure at the same time, in order to prevent redistribution of pulmonary blood flow towards upper (non-dependent, non-ventilated) lung. It is not easy to accomplish this in practice.
\n\t\t\tIt seems reasonable to use initial FiO2 of 50%, which could be increased up to 100%, as needed. This can’t influence the real shunt in upper lung, but it improves oxygenation throughout alveoli with low Va/Qt relations in lower lung.
\n\t\t\t„Over inflation“ of one lung (volutrauma) is harmful and leads to acute lung injury. Deflation and inflation of the operated lung, with a possibility of ischemic/reperfusion injury, is also included in lung trauma. Application of very low tidal volumes improves the outcome of mechanically ventilated patients (50, 51, 56).
\n\t\t\tArterial hypoxemia is obviously undesirable, but in spite of everything, it might be better to accept PaO2 a little lower than preoperative value, than to undertake measures like inflation of the upper lung, which could present an obstacle for surgical intervention and could prolong it (21, 22, 42, 59, 66, 67).
\n\t\t\tAt the end, it could be concluded that:
\n\t\t\tIn patients subjected to OLV in general anesthesia (GA), hypoxia develops, with decrease in PaO2 and increase of the value of intrapulmonary shunt, a period of time after initiation of OLV (after 10 min.), with subsequent return of Qs/Qt towards lower values (after 30 min. of OLV), because of the development of compensatory mechanisms (HPV).
\n\t\t\tIn patients subjected to OLV managed with thoracic epidural anesthesia (TEA) combined with general anesthesia (GA), hypoxia occurs, also, with fall of PaO2 and increase of the value of intrapulmonary shunt, 10 min. after commencement of OLV, and returning of Qs/Qt towards normal values (approximately), about 30 min. after initiated OLV.
\n\t\t\tThoracic epidural anesthesia (TEA) doesn’t lead to augmentation of hypoxia and enhancement of the shunt fraction during OLV.
\n\t\tLDP = lateral decubitus position
\n\t\t\tOLV = one lung ventilation
\n\t\t\tTLV = two lung ventilation
\n\t\t\t(i)PEEP = (intrinsic) positive end expiratory pressure
\n\t\t\tCPAP = continuous positive airway pressure
\n\t\t\tVa/Qt = ventilation/perfusion ratio
\n\t\t\tQs/Qt% = intrapulmonary shunt
\n\t\t\tPA = alveolar pressure
\n\t\t\tPpa = pulmonary artery pressure
\n\t\t\tPpv = pulmonary venous pressure
\n\t\t\tPisf = pulmonary interstitial pressure
\n\t\t\tPpl = pleural pressure
\n\t\t\tPO2 = partial pressure of oxygen (a = in arterial blood, v = in venous blood, A = in the alveoli)
\n\t\t\tPCO2 = partial pressure of carbon dioxide (a = in arterial blood, v = in venous blood, A = in the alveoli)
\n\t\t\tFRC = functional residual capacity
\n\t\t\tFiO2 = inspired oxygen fraction
\n\t\t\tPVR = pulmonary vascular resistance
\n\t\t\tHPV = hypoxic pulmonary vasoconstriction
\n\t\t\tTIVA = total intravenous anesthesia
\n\t\t\tMAC = minimal alveolar concentration
\n\t\t\tТЕА = thoracic epidural anesthesia
\n\t\t\tGA = general anesthesia
\n\t\t\tFOB = fiber-optic bronchoscope
\n\t\t\tARDS = acute respiratory distress syndrome
\n\t\t\tPPPE = post pneumonectomy pulmonary edema
\n\t\t\tCOPD = chronic obstructive pulmonary disease
\n\t\t\tI : E = inspiration : expiration
\n\t\t\tASA = „American Society of Anesthesiologists“ (classification)
\n\t\t\tSaO2 = oxygen saturation of arterial blood
\n\t\t\tAST = aspartate amino transferase
\n\t\t\tALT = alanine amino transferase
\n\t\t\tЕF = ejection fraction of the heart
\n\t\t\tCO = cardiac output
\n\t\t\tFEV1 = forced expiratory volume in 1st sec.
\n\t\t\tFVC = forced vital capacity
\n\t\t\tVC = volume controlled mechanical ventilation
\n\t\t\tPC = pressure controlled mechanical ventilation
\n\t\t\tHR = heart rate
\n\t\t\tECG = electrocardiography
\n\t\t\tMAP = mean arterial pressure
\n\t\t\tRR = respiratory rate
\n\t\t\tSAT% = oxygen saturation from pulsoximetry
\n\t\t\tCc׳O2 = oxygen content of pulmonary capillary blood
\n\t\t\tCaO2 = oxygen content – ml O2/100 ml arterial blood
\n\t\t\tCvO2 = oxygen content – ml O2/100 ml venous blood
\n\t\t\tLLL = lower left lobe
\n\t\t\tHb = hemoglobin
\n\t\t\t1.39 = Hifner coefficient (1g Hb binds 1.39 ml O2 when totally saturated)
\n\t\t\t0.0031 = coefficient of oxygen dissolution in plasma
\n\t\t\tFFP = fresh frozen plasma
\n\t\t\tSAGM = packed erythrocytes
\n\t\t\tLMWH=low molecular weight heparin
\n\t\tPosttraumatic stress disorder (PTSD) is an often debilitating mental disorder that may occur following trauma exposure [1]. PTSD is characterized by four diagnostic clusters—(1) the re-experiencing the traumatic event (e.g., recurrent memories, dreams, or flashbacks); (2) symptoms of avoidance (e.g., efforts to evade trauma reminders); (3) arousal (e.g., hypervigilance, sleep disruptions); and (4) negative cognitions and mood (e.g., self-blame) [1]. Substance use disorder (SUD) is another psychiatric disorder characterized by 11 possible symptoms which involve negative consequences arising from one’s substance use and inability to control one’s substance use [1]. In the last version of the
PTSD often co-occurs with SUD. Research has documented high rates of comorbidity between PTSD and alcohol use disorder (AUD) [2], cannabis use disorder (CUD) [3, 4], and other SUDs [5]. The prognosis of comorbid PTSD-SUD is worse than either disorder alone [6] with comorbid PTSD-SUD leading to greater functional impairment in comparison to those with only PTSD or a SUD [7].
It has been suggested that PTSD and SUD are likely functionally related to one another [8] in comorbid individuals. While the precise underlying mechanisms are not well understood, there are several learning theories that may help explain the high rates of substance misuse in people with trauma histories and help us understand the high comorbidity of PTSD with SUD. The first is the two-factor learning theory which was originally developed by Mowrer to explain the acquisition and maintenance of phobias [9] and which has more recently been applied by Stasiewicz [10] to the acquisition and maintenance of SUDs. Two-factor learning theory applies a combination of classical conditioning and operant conditioning mechanisms to the development and maintenance phases of these disorders, respectively. Applying this theory to the co-occurrence of PTSD and SUDs in traumatized individuals, trauma-relevant cues that were paired with the original traumatic experience (e.g., loud noises of gunfire paired with witnessing a comrade fatally injured in wartime) are thought to come to elicit negative affect through the process of classical conditioning [10]. Future exposures to the trauma cue alone (e.g., loud noises alone) motivate avoidance/escape behavior, including substance misuse, to reduce the associated negative affect and thereby experience relief [10]. Avoidance/escape behaviors like substance misuse are thus negatively reinforced in individuals with trauma histories/PTSD as they remove the aversive experience of negative affect. Therefore, substance misuse is maintained as a self-medication type of coping response through operant conditioning processes where behavior is repeated when it is followed by desirable consequences, in this case, relief from negative affect.
Another theory that is relevant to understanding the links of trauma/PTSD with SUD involves the role of classical conditioning in the development of conditioned craving—a strong urge to use the substance in response to exposure to the conditioned cues. It has long been known that drug-related stimuli that are frequently paired with drug-taking can come to elicit a conditioned craving response through the process of classical conditioning [11]. For example, a needle and other drug use paraphernalia that are frequently paired with heroin use can come to elicit craving when presented alone, for an injection drug user. Similarly, for a substance user with a trauma history/PTSD, the frequent pairing of trauma cues (e.g., intrusive memories of the trauma, exposure to external trauma reminders) with substance use, as explained by the two-factor learning theory above [10], can come to create strong associations between trauma cues and substance use [12]. The result is that such trauma cues can become conditioned stimuli that elicit a conditioned craving response when presented on their own [13]. For example, if a young woman with sexual assault-related PTSD drinks alcohol each time she has an intrusive memory about her sexual assault, such trauma cues can come to elicit a strong craving for a drink, which may motivate her alcohol seeking and maintain her alcohol use.
The study of the above putative mechanisms under controlled, laboratory conditions is crucial for a better understanding of the intertwined relationships between trauma/PTSD and substance misuse. Specifically, the use of cue-reactivity paradigms allows researchers to examine how substance-related and trauma cues may come to elicit craving and/or negative affective responses through the conditioning processes described above.
The cue-reactivity paradigm is broadly defined as a lab-based method in which participants are exposed to a set of stimuli meant to elicit a “reactivity” response—that is, a change from baseline in response to the stimulus [14]. In the context of addictions research, stimuli may be substance-related cues, such as a syringe or other drug-related paraphernalia for an injection drug user [15]; these stimuli serve as analogs for real-life stimuli which may evoke a craving response outside of the lab. Indeed, research in this area has shown that relevant drug-related cues presented in the lab can elicit a heightened craving response among substance users [16, 17]. More recently, cue-reactivity paradigms have been used to study conditioned craving as a possible mechanism underlying the relationship between trauma/PTSD and SUD [18, 19]. Indeed, extant research has shown that in-lab exposure to cues representing trauma reminders (e.g., a video of a violent crime) activates both substance-related craving responses as well as increased negative affect [20].
Craving has been measured in a number of ways in substance- and trauma-related cue-reactivity research, including with subjective self-report measures, such as the Desire for Drug Questionnaire [21], and measures specific to the substances used, such as the Alcohol Urge Questionnaire [22] and the Marijuana Craving Questionnaire [23]. Craving has also been measured more objectively in cue-reactivity studies, albeit less commonly than via self-report. Specifically, physiological measures, such as salivary flow and heart rate monitoring, are often used as a more objective proxy measure of craving [24]. Craving has also been further differentiated into reward-related craving (i.e., a desire for reward or stimulation from a substance) and relief-related craving (i.e., a desire for a reduction in tension or negative affect from using a substance) using certain self-report measures [23].
While cue exposure paradigms are homogenous in their goal to elicit some form of reactivity (e.g., change from baseline in craving or emotional state in response to the stimulus), the types of cues and paradigms used in this area of research have varied widely. For example, cues may be standardized across participants in the study or may be personalized to the individual’s own trauma history details; cues may be presented through the use of script-driven imagery (i.e., audio recordings, such as a retelling of a traumatic event) or
Indeed, it is evident that cue-reactivity paradigms vary widely in design, are used in an expansive variety of contexts and with a wide range of populations, with many different outcomes used to capture cue-reactivity effects. Thus, in this chapter, we intend to scope the extant cue-reactivity literature in the context of PTSD-SUD comorbidity research to identify patterns and variations in methodology, measures, and outcomes used in this growing field.
Our first aim was to examine how cue-reactivity paradigms have been used in samples of substance users with trauma histories. Specifically, we were interested in how these studies lead to a further understanding of the mechanisms underlying comorbid PTSD-SUD. Second, we intended to examine the different types of cues used within the cue-reactivity paradigm as well as the specific effects, strengths, and weaknesses of variations in paradigm design. Specifically, we compared the merit of personalized vs. non-personalized cues, as well as other cue variations, in PTSD-SUD cue-reactivity research (e.g.,
The present scoping review followed preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines appropriate for a scoping review. Specifically, we used the PRISMA Scoping Review checklist [25].
Studies were included if they used an experimental design if they utilized a cue-reactivity paradigm and if self-reported craving was assessed following the cue-reactivity paradigm. Furthermore, the population of interest had to include individuals who had experienced a traumatic event consistent with Criterion A of a DSM-5 PTSD diagnosis [1]. Alternatively, PTSD symptoms must have been assessed for each participant. Additionally, it was required that participants report on their substance use.
We excluded studies that were not written in English, or if humans were not the research participants. We did not exclude gray literature. Specifically, we included theses and dissertations to gather the full scope of research in this area and to reduce publication bias.
The databases PsycInfo, PubMed, and PTSDPubs were searched to identify studies of interest. Each search was conducted using a Boolean search logic and relevant keywords: (“PTSD” OR “post traumatic stress disorder” OR “posttraumatic stress disorder” OR “post-traumatic stress disorder” OR “trauma”) AND (“cue” OR “cue exposure” OR “cue-reactivity” OR “conditioned response” OR “stimuli”) AND (“substance” OR “substances” OR “alcohol” OR “drug” OR “drugs” OR “cocaine” OR “cannabis” OR “marijuana” OR “opioids” OR “opiates” OR “tobacco” OR “nicotine”) AND (“craving” OR “urge”). There were no search restrictions based on year of publication or language.1
One hundred fifty-eight studies were initially imported into Covidence, a literature screening software. After duplicates were removed by Covidence, 128 studies remained. Abstracts of all studies were screened by two independent raters (SDG and CS) who removed all irrelevant studies; a moderate rate of agreement of 74% was achieved [26]. A third screener (PRS) aided in resolving any conflicts between the two raters. A total of 28 studies met our final inclusion criteria (Figure 1).
PRISMA flowchart of literature search and screening.
The data were extracted into a spreadsheet, including information on the study sample, sample characteristics, outcome measures, cue-reactivity methodology, hypotheses/aims, outcomes of interest, and general findings. A quality assessment and risk of bias assessment were not conducted, as these are not typical in scoping reviews [27]. The extracted data were then synthesized into common categories by the first author to further examine themes in the scoped research.
Script-driven imagery cues were the most common cue paradigm used in the present sample of studies (n = 20). These were often paired with a substance-related
All studies used subjective self-report measures of craving as a measure of reactivity (n = 28); this was an inclusion criterion for this scoping review. However, many did include objective craving measures in addition to subjective measures (i.e., salivation, heart rate; n = 9). Other reactivity measures assessed included affect (n = 14), subjective stress (n = 6), objective stress (i.e., cortisol; n = 3), attentional/memory tasks (n = 3), and neural activation (n = 3).
Types of substances used/misused by participants in the study were alcohol (n = 17), cocaine (n = 6), nicotine (n = 3), heroin (n = 1), opioids (n = 1), and any substance (n = 4). It is important to note that some studies (n = 4) allowed for combinations of specific drugs (i.e., individuals who use alcohol and/or cocaine were recruited for one study).
Studies identified in the present scoping review employed the use of several types of cues. Specifically, neutral cues (n = 24; e.g., brushing your teeth), trauma cues (n = 23; e.g., a physical assault), substance cues (n = 14; i.e., cannabis paraphernalia), stress cues (n = 5; a presentation at work), and social cues (n = 1; speaking with a friend; [33]) were used. The average number of cue types used per study was 2.36 (SD = .731).
The majority of studies utilized pre-cue baseline as a comparator for their measures of reactivity (n = 22); a minority only compared reactivity data across cue types (i.e., comparing neutral vs. trauma responses; n = 6). However, many studies used a combination of comparators by comparing to baseline data and across cue types as well (n = 12).
While we have summarized the key components of included studies here, a full summary of each study across the coded variables of interest is available in Appendix A.
Populations of interest were largely adults who were assessed for PTSD symptoms/diagnoses and/or trauma history, and substance use. Participants across studies were more often male (
All studies included participants with either PTSD (n = 14) or those who had been exposed to a lifetime trauma (n = 10), or both with PTSD and/or trauma histories assessed continuously (n = 4). PTSD was assessed but not required for some studies, with others requiring trauma exposure but not a PTSD diagnosis (see [44, 45]). To assess for PTSD, most studies used some form of a validated structured interview (n = 25), such as the MINI [46], the SCID-5-RV [47], and the Clinician-Administered PTSD Scale [48]. Those studies examining trauma-exposed individuals typically administered a questionnaire to assess trauma history (n = 3), such as the Trauma History Questionnaire [49] or the Life Events Checklist [50], as well as continuous measures of PTSD symptoms, such as the PTSD Checklist for DSM-5 [51].
Substance use among the study populations was similarly measured. Specifically, the majority of studies (n = 18) required an SUD as inclusion criteria [18, 52], with some using inpatients receiving treatment for PTSD, SUD, or both (n = 12; [32, 53]). Fewer studies required less extreme forms of substance use, such as occasional drinking (n = 6) (see [13, 54]) and other cut-off points for use of various substances (n = 3; [55]). To assess for the presence of a SUD, most studies (n = 18) used structured interviews, such as the C-DIS IV [56] or the SCID-5-RV [47], but others used shorter self-report measures, such as the Alcohol Use Disorders Identification Test (AUDIT; n = 10) [57].
Many of the studies employed personalized cues within their cue-reactivity paradigms, either through interviews where they obtained information about a participant’s worst traumatic experience and transcribed the interview into an imagery-based cue [58] or utilized the participants’ preferred substance as part of an
Studies that utilized photographic cues as part of task-based cue paradigms found to support that their paradigms functioned as effective cue-reactivity paradigms, even though craving was not the primary outcome of interest. For example, Garland and colleagues [28] showed participants trauma-related images and asked them to either simply view the photos or reappraise the photos by reinterpreting the photo’s meaning to regulate their emotions in reaction to the photo. Following this task, relief craving increased; this increase was associated with the number of adverse childhood experiences to which participants reported having been exposed. Similarly, Beckham et al. [30] utilized a Stroop color-naming attentional [31] task with trauma-related words with a veteran sample of cigarette smokers. Results demonstrated trauma words, relative to neutral words, led to greater cigarette craving as well as more withdrawal symptoms.
One of our inclusion criteria was the measurement of craving following a cue-reactivity paradigm. Accordingly, all studies included a measure of craving, with all studies including a measure of subjective craving. Many studies measured craving using a Visual Analog Scale (VAS) or various Likert-type rating scales. Among those who examined craving changes from baseline by cue type, subjective craving responses were highest following trauma-related cues compared to substance, stress, and/or neutral cues (n = 9). Studies that did not use trauma cues found substance-related cues elicited greater craving compared to neutral cues (n = 3). In those studies that used trauma cues, substance cues, and neutral cues (n = 9), typically trauma cues elicited the greatest craving, followed by substance cues, and then neutral cues. Interestingly, studies, where trauma imagery cues were paired with
While our inclusion criteria did not specifically require an objective assessment of craving, the frequent use of salivation, heart rate, and other measures of physiological reactivity warrants a brief summary of this work. Most studies that included physiological/objective craving measures did so by measuring salivary flow (n = 5). Coffey et al. [18] found a significant increase in salivation following trauma and alcohol cues relative to neutral cues. Nosen et al. [59] found an increase in salivation following alcohol
Seven studies examined outcomes of pharmacological or psychotherapeutic treatment in clinical populations, utilizing cue reactivity as a secondary outcome measure or adjunct to symptom measures. Two studies examined the effectiveness of pharmaceuticals as a treatment for comorbid PTSD-SUD. Specifically, in a pre-clinical lab-based study, Stauffer et al. [35] examined the use of intranasal oxytocin (20 IU and 40 IU) vs. placebo in males with comorbid PTSD-AUD. Each participant took part in each condition across three counterbalanced sessions. Following drug or placebo administration, participants were exposed to
Five studies examined the effects of several psychotherapeutic interventions on cue-elicited craving as well as distress, PTSD symptoms, and resilience. Coffey and colleagues [18] examined the effects of trauma-based imaginal exposure vs. relaxation using a cue-reactivity paradigm to assess trauma cue-reactivity (i.e., craving), showing a decrease in craving to the trauma-alcohol cue combination only among those enrolled in prolonged exposure (PE) therapy but not among those in the relaxation condition. However, craving following the trauma-only cue decreased relative to baseline among both intervention groups. Similarly, two studies ([53, 61]) assessed the merits of PE therapy in comparison to a health/lifestyle therapy using a craving to a cue-reactivity paradigm as an outcome measure; one study [53] found both healthy lifestyle (control) and trauma cue-exposure treatments led to a decrease in craving responses to trauma imagery and
Three studies combined fMRI and a cue-reactivity paradigm. One study [34] examined neural activation during the presentation of stress, neutral, and substance-related cues among cocaine-dependent individuals with and without childhood maltreatment histories. The degree of craving to the stress cues predicted activation of the rostral anterior cingulate cortex to a lesser extent in the participants with maltreatment histories. The authors interpreted this to suggest that childhood maltreatment interferes with a key mechanism for resolving conflict and responding adaptively to stress [34]. Conversely, the degree of craving to the substance-related cues was associated with activation of the supplemental motor area and the visual cortex to a greater extent in those with maltreatment histories. The authors interpreted this latter finding to suggest that childhood maltreatment enhances the anticipatory reward response to substance cue exposure [34]. Further, during substance cue presentation, another study [35] found childhood trauma histories among substance users were significantly associated with increased activation of the frontal striatal circuit and the amygdala. However, a third study [32] did not find any psychological correlates of neural activation during the presentation of substance-related vs. neutral stimuli in a sample of adults with comorbid PTSD-AUD. It is difficult to know if this failure to observe an effect of cue exposure on neural activation was due to an ineffective manipulation since craving responses were not measured.
Fourteen studies included a measure of effect as part of their evaluation of cue-reactivity. Eleven of such studies examined both positive and negative affect, and three examined negative affects only. The Positive and Negative Affect Schedule or PANAS [63] was overwhelmingly used as the standardized measure of this variable (n = 10), although other measures were used as well, such as the Affect Grid [64] (n = 2). Among the majority of studies (n = 9), negative affect increased following stress and trauma-related cues [38]. In those studies which also examined positive affect, positive affect tended to decrease following stress and trauma-related cues [42, 33] but this was not always consistent. For example, Coffey et al. [39] did not find any statistically significant differences in positive affect across cue types. Interestingly, one study reported that substance-related cue exposure increased both positive and negative affect, and this ambivalent response was associated with the strongest substance cravings [55].
The primary aim of this scoping review was to map the use of cue-reactivity paradigms in PTSD-SUD research among substance users with trauma histories and/or PTSD. Specifically, we sought to summarize the characteristics of the samples, examine outcomes measured followed the cue-reactivity paradigm (e.g., subjective/objective craving, negative affect), and map how such paradigms vary across the literature on several dimensions (e.g., cue type, personalization/standardization, cue presentation). Furthermore, we aimed to assess the consequences of methodological differences in cue-reactivity research. While prior literature has summarized cue-reactivity methodology in substance use research [65] and one group has briefly summarized cue-reactivity research in a comorbid PTSD-AUD population as part of a broader review of mechanisms involved in this form of comorbidity [66], we aimed to map the use of cue-reactivity paradigms in a way which could lead to further understanding of conditioned craving as a mechanism in the maintenance of comorbid PTSD-SUD. Specifically, our systematic scoping of the literature identified 28 studies that assessed craving following a cue-reactivity paradigm in a population of substance users with trauma histories and/or PTSD.
Our scoping review revealed wide variations in methodologies used to examine cue-induced craving. Specifically, characteristics of study samples, the methodological details of the cue-reactivity paradigm, and the types of outcomes assessed, all varied broadly. We have identified four themes in the studies through our scoping of the literature that may help elucidate commonalities and important distinctions across the identified studies—(1) increases in craving following trauma cue presentation; (2) the use of methodological subtypes of cue-reactivity paradigms; (3) affect as an outcome and possible mediator of craving in cue-reactivity research; and (4) the cue-reactivity paradigm as an adjunct outcome measure in intervention research.
From the above literature review, it is evident that craving has been repeatedly shown to increase following exposure to certain cues in substance users with trauma histories and/or PTSD. In particular, trauma cues tend to elicit the greatest increase from baseline in craving responses when compared to substance-related and neutral cues. This was true across studies using both personalized [43] and standardized cues [54]. However, this effect was typically magnified when a combination of trauma-related imagery and
Second, the cue-reactivity methodologies used in the studies identified through our scoping review tended to vary widely. While the majority of studies utilized imagery-based audio cues to elicit cue-reactivity craving responses, some used combinations of imagery-based trauma and substance-related
Third, while we did not systematically aim to include effect as an outcome in the present scoping review, we decided to cover this outcome as many of the studies included in the review (50%) did include a measure of effect as an additional outcome alongside craving. Our findings elucidated the importance of effect in helping explain the relationship between trauma cue-reactivity and craving. To elaborate, negative affect has quite consistently been shown to increase following trauma cue exposure [44, 59]. This is consistent with suggestions that conditioned
Finally, it is important to note that seven studies utilized cue-reactivity paradigms as an additional outcome in trauma and/or substance-related therapeutic interventions. Notably, neither of the two pharmacological studies found an effect of the respective medications (oxytocin and neurokinin-1 receptor antagonist aprepitant) relative to placebo as a means of reducing either PTSD symptoms or stress cue- or substance cue-induced craving (see [32, 35]). Conversely, all studies examining the efficacy of PE therapy for PTSD or PTSD-SUD found that trauma cue-induced craving, as well as other forms of cue-reactivity (e.g., salivation, distress), decreased over time in those who received PE when compared to patients who received a control intervention [36, 37, 39, 53, 61]. Indeed, behavioral interventions seem to be more efficacious than pharmacological interventions in reducing reactivity to both trauma and substance-related cues among trauma-exposed substance users, at least for the few pharmacotherapies that have been investigated with this paradigm thus far, and at least in comparison to PE therapy. Furthermore, the use of cue-reactivity paradigms as a secondary outcome in randomized controlled trials of therapeutic interventions speaks to the multifaceted functionality of the cue-reactivity paradigm in the PTSD/trauma-exposed population, offering a mechanism-based outcome that informs beyond the decrease of symptoms.
First, it is important to note that no formal examination of the study quality of the included literature was completed, as this step is not typical for scoping reviews [27]. It should also be noted that our choice to include unpublished theses and dissertations in the present review may have led to the inclusion of some studies with poor methodological quality, although it does help ensure that our conclusions are not hampered by publication bias.
To further assess the studies included in the present scoping review, we recommend a formal analysis of methodological quality be completed in the future to better understand how methodological variations in cue-reactivity may influence relevant outcomes. Additionally, the use of cue-reactivity paradigms as secondary outcomes in the context of behavioral and pharmacological intervention trials is an interesting research direction that should be studied further, as this may lead to important implications for understanding the breadth of response to the use of psychotherapeutic or pharmacological interventions in this population, and may point to potential mechanisms of action. We also recommend that a formal systematic review and meta-analysis be conducted to quantify the magnitude of trauma cue-induced craving responses in this population, and to identify significant moderators of this response in terms of sample characteristics (e.g., percentage of the sample with PTSD), and methodological variables (e.g., personalized vs. standardized cues). Providing that relevant data could be obtained from published papers or authors, novel techniques, such as two-step meta-analytic structural equation modeling (TS-MASEM; [68]) could also be employed to examine theorized mediational pathways (e.g., that trauma cue exposure leads to activation of negative affect which in turn activates craving). Finally, meta-analyses could also quantify the degree of reduction in trauma cue-induced craving that is achieved with various forms of treatment for PTSD, SUD, and their comorbidity, and its relations to treatment efficacy (i.e., symptom reduction).
Our scoping review maps the use of cue-reactivity paradigms across the trauma-exposed, substance-using population with and without PTSD, and summarizes methodological variations in cue-reactivity paradigms across this body of literature, as well as the results of identified studies. Cue-reactivity paradigms have proven efficacious in eliciting cue-induced craving responses in populations of trauma-exposed individuals who use substances. Cue-reactivity research may help increase understanding of the learning processes that are involved in the development, maintenance, or exacerbation of a SUD among trauma-exposed individuals with and without PTSD who use substances. Furthermore, cue-reactivity paradigms may be used as an important means of assessing whether behavioral and/or pharmacological treatments for PTSD and/or SUD have had an impact on the ability of trauma cues to elicit a conditioned craving response in this population.
First author (year) | Sample characteristics and context | Cue reactivity paradigm and method | Outcome(s) of interest | Craving measure | Relevant findings |
---|---|---|---|---|---|
Elton et al. [34] | 38 cocaine-dependent males with (n = 20) and without (n = 18) childhood maltreatment histories. | Script-driven imagery. All participants listened to a personalized neutral, stress, and cocaine-related audio cue whilst in an fMRI scanner. | Brain region activation, anxiety, and subjective craving response. | Cue-induced cocaine craving was measured using the visual analog scale (VAS) from 0 to 10. | Stress-Neutral: The interaction between maltreatment severity and craving responses was associated with activation of the left premotor cortex and right cerebellum. Substance-Neutral: The interaction between maltreatment severity and craving responses was associated with activation of the bilateral occipital cortex, caudal pre-supplementary motor area [SMA], and cuneus. Findings suggest that childhood maltreatment alters neural correlates of cue-induced substance craving. |
Dutton [33] | 46 hazardous drinkers who met DSM-5 criterion A (trauma exposure) of a PTSD diagnosis | Script-driven imagery. Participants listened to a personalized neutral cue followed by either a neutral-social (n = 24) or a social conflict cue (n = 22). Each cue was 1 minute long followed by a 30 second visualization period. | State PTSD symptoms, subjective craving response, affect, and alcohol approach bias. | Cue-induced alcohol craving was measured using a VAS from 0 to 100. | Following the social conflict cue but not the neutral social cue, state PTSD symptoms increased. There were no differences in alcohol approach bias, affect, or craving between cues. |
Trautmann et al. [54] | 95 healthy occasional drinkers who had experienced childhood trauma. | Standardized video. Participants watched either a 15-minute trauma film (n = 47) or a 15-minute neutral film (n = 48). | Subjective craving response, anxiety, and physiological reactivity (i.e., skin conductance, heart rate, and saliva cortisol levels) | Cue-induced alcohol craving was measured using the Alcohol Craving Questionnaire-Short Form [69]. | In females, the trauma film elicited greater craving responses compared to the neutral film. In males, the number of childhood traumas positively moderated the relationship between film condition and craving responses. In males, childhood trauma was associated with increases in skin conductance, heart rate, and cortisol levels; only skin conductance was related to craving responses. |
Stauffer et al. [35]* | 47 males with comorbid PTSD-AUD and 37 healthy control males. | Effects of oxytocin as a treatment for comorbid PTSD-AUD, subjective craving responses, and heart rate variability. | Cue-induced alcohol craving was measured using a VAS from 0 to 100. | Craving responses and heart rate were higher following the alcohol cues compared to neutral cues. No effects of oxytocin compared to placebo on cue-induced craving or heart rate. | |
Ralevski et al. [38]* | 25 veterans with comorbid PTSD-AUD. | Script-driven imagery. All participants listened to personalized trauma, stress, and neutral audio cues. | Subjective craving responses, blood pressure, heart rate, negative affect, and salivary cortisol. | Cue-induced alcohol craving was measured using the Alcohol Craving Questionnaire-Short Form [69] and a VAS. | Craving responses, cardiovascular reactivity, and negative affect were highest following the trauma cue but were also high following the stress cue, both compared to the neutral cue. |
Winokur [60] | 95 individuals with (n = 31) and without (n = 39) trauma histories who were heroin (n = 25) or nicotine (n = 70) dependent. | Standardized video. Participants watched standardized video cues related to either heroin or nicotine use, and a neutral video cue. | Subjective craving responses. | Cue-induced heroin or nicotine craving was measured using a Within Sessions Rating Scale (0–9). | Post substance cue-craving responses increased among both the opiate and nicotine-dependent groups, but were highest in the opiate-dependent group, and only among those with trauma histories. |
Coffey et al. [39]* | 43 SUD inpatients with comorbid PTSD-AUD. 75% of participants who completed at least one clinical session were randomly assigned to receive six sessions of either imaginal exposure therapy (n = 12) or relaxation (control) condition (n = 12). However, only 17 participants completed the study. | Script-driven imagery and Trial 1: All participants listened to personalized neutral and trauma cues. Trial 2: All participants listened to a personalized trauma cue followed by the presentation of either alcohol or water. | Subjective craving responses, affect, and emotional distress. | Cue-induced alcohol craving was measured using a VAS from 0 to 10. | Craving responses decreased from pre- to post-treatment among those in the imaginal exposure condition following the trauma-alcohol cue (trial 2) and did not change in the relaxation condition. Craving responses also decreased in both groups following the trauma cue (trial 1). Negative affect was highest in trial 2. |
Read et al. [13] | 232 undergraduate students with PTSD (n = 28), with trauma exposure but no PTSD (n = 113), or no trauma history (n = 91) taking part in a clinical trial. | Script-driven imagery. Participants listened to either a personalized trauma (n = 111) or neutral cue (n = 121). Participants wrote about the event while continuing to imagine the scene. | Subjective craving, affect, and performance on a Stroop attentional task with trauma and alcohol-specific stimuli. | Cue-induced alcohol craving was measured using a 10-point Likert scale rating urge to drink. | Participants with PTSD in the trauma cue condition showed a slowed response in the Stroop task. This effect was associated with an urge to drink only among those with PTSD in the trauma cue condition. |
Kaag et al. [29] | 117 adults, half cocaine users (n = 59) and half healthy controls (n = 58) | Event-related cue-reactivity paradigm. All participants viewed substance-related photos, neutral photos, and photos of animals. They were instructed to press a button when photos of animals were presented. | Subjective craving and neural activation. | Cue-induced cocaine craving was measured using the Desire for Drug Questionnaire [21] at baseline and following the cue-reactivity paradigm. | Only among substance users, the presentation of cocaine cues led to neural activation in the frontal striatal circuit and the amygdala. Amygdala-striatal connectivity was associated with childhood trauma among substance users. |
Coffey et al. [58] | 75 individuals receiving SUD treatment with PTSD who were cocaine (n = 30) or alcohol-dependent (n = 45) | Script-driven imagery and | Subjective craving. | Cue-induced craving was measured using the Cocaine Craving Questionnaire-Now (CCQ-Now) [70] and Alcohol Craving Questionnaire-Now (ACQ-Now) [71] | Both alcohol-dependent and cocaine-dependent participants evidenced greater cravings following the trauma- and substance-related cues compared to the neutral cues. |
McHugh et al. [44] | 194 individuals with PTSD receiving treatment for a comorbid SUD. | Script-driven imagery. All participants listened to a personalized trauma and neutral cue, counterbalanced across two sessions, followed by a 1-minute visualization period. | Subjective craving and affect. | Cue-induced substance craving was measured on an 11-point scale. Ratings ranged from 0 (no cravings) to 11 (very strong cravings). | Craving and negative emotional reactivity were greater following the trauma cue compared to the neutral cue. Anxiety sensitivity was associated with greater emotional reactivity following the trauma cue, but there was no association between anxiety sensitivity and craving response. |
McGuire et al. [36] | 29 veterans receiving treatment for comorbid PTSD-SUD. | Interview. All participants provided a detailed verbal description of their most traumatic lifetime event. | Subjective craving, resilience, and PTSD symptoms. | Cue-induced craving for alcohol and/or other substances was measured using the Alcohol Craving Questionnaire Short Form-Revised [71] | Posttreatment, participants evidenced a decrease in cue-induced craving and fewer PTSD symptoms, as well as increased resiliency, relative to pre-treatment baseline. |
Saladin et al. [45] | 124 individuals with trauma histories receiving SUD treatment who were alcohol- (n = 70) or cocaine-dependent (n = 54). | Script-driven imagery and | Subjective craving. | Cue-induced substance craving was measured using a 21-point VAS. | Craving was greater following the trauma- and substance-related cues in comparison to the neutral cues. PTSD symptom severity predicted greater craving responses, but only following the trauma + substance cue pairing. |
Coffey et al. [18] | 40 individuals with comorbid PTSD-AUD receiving inpatient SUD treatment. | Script-driven imagery and | Subjective and objective craving responses; emotional distress. | Cue-induced craving was measured using a VAS from 0 to 10 and salivary flow. | Subjective craving responses, distress, and salivary flow were greater following substance and trauma cues compared to the neutral cue. |
Vujanovic et al. [43] | 58 low-income inner-city adults. | Script-driven imagery. All participants listened to personalized trauma, substance, and neutral audio cues. | Subjective craving responses. | Cue-induced craving was measured using a VAS from 0 to 100. | Lower distress tolerance was a significant predictor of higher craving responses following the trauma cue. |
Rodriguez et al. [40] | 305 undergraduate students with no trauma (n = 127), trauma exposure (n = 106), and PTSD (n = 72). | Script-driven imagery. Participants were instructed to close their eyes and imagine their most traumatic event as if it was happening to them. Participants then wrote about the scene while continuing to imagine the scene. | Subjective craving responses and affect. | Cue-induced craving was measured using the Urge to Drink Questionnaire [22], on a scale from 1 to 10. | Emotional responses to the trauma cue mediated the relationship between trauma exposure and the urge to drink. |
Bing-Canar et al. [41] | 184 young adults with trauma histories | Script-driven imagery and | Subjective and objective craving responses. | Cue-induced craving was measured using a three-item Alcohol Craving Scale [72] and salivation levels. | Depressive symptoms did not have any effect or interaction with the cue-reactivity paradigm to predict increased craving or salivation. |
Zambrano-Vazquez et al. [61] | 85 individuals with comorbid PTSD-SUD and current alcohol dependence receiving SUD treatment. Only 66 participants who completed 8 or more prolonged exposure treatment sessions were included in the analyses. | Script-driven imagery and | Subjective and objective (salivation) craving, subjective distress, and domains of functioning. | Cue-induced craving was measured using the Alcohol Craving Questionnaire-Now [69] and salivation levels. | Severity in all domains of functional impairment (Negative Valence, Arousal, and Cognitive) decreased from pre to post-treatment, and this change was associated with a decrease from pre-treatment baseline in self-reported craving and salivation post-treatment following alcohol and trauma cue exposure. |
Garland et al. [28]* | 36 opioid-treated chronic pain patients at risk for opioid use disorder, with adverse childhood experiences (ACEs). | Emotional Regulation Task. Participants were shown trauma-related images and were asked to both views or reappraise the images (dependent on the trial block) to regulate the emotions elicited by the image. | Subjective craving, heart rate variability, and negative affect. | Cue-induced opioid craving was measured using a 5-point scale, with 1 indicating no craving and 5 indicating very strong cravings. | Following the emotional regulation task, craving increased from the pre-task baseline. This change was related to the number of ACE exposures. ACEs and duration of opioid use also predicted a blunted heart rate variability when regulating negative emotions. |
Zaso et al. [42] | 611 college students with PTSD (n = 50), with trauma exposure but no PTSD (n = 325), and no trauma (n = 236) who drink alcohol | Script-driven imagery. Participants were randomized to listen to either a personalized trauma or neutral cue followed by a 2-minute writing period relating to the cues. | Subjective craving response and affect. | Cue-induced craving was measured using a 10-point scale, with 1 indicating no urge to drink and 10 indicating a very strong urge to drink. | Following the trauma cue, but not the neutral cue, participants reported greater cravings and negative affect relative to baseline, which was associated with coping drinking motives. |
Kwako et al. [32]* | 53 individuals with comorbid PTSD-AUD receiving inpatient SUD treatment. Participants received either aprepitant (n = 26) or a placebo (n = 27) prior to cue exposure. | Script-driven imagery, | Subjective craving, blood cortisol, and neural activation. | Cue-induced alcohol craving was measured using the Alcohol Urge Questionnaire [22] | Alcohol and stress cues induced more cravings compared to neutral cues. There was no significant neural activation following the substance-related relative to the neutral stimuli. |
Nosen et al. [59] | 108 adults with comorbid PTSD-AUD who were receiving residential treatment for SUD. | Script-driven imagery and | Subjective and objective (salivation) craving and affect. | Cue-induced alcohol craving was measured using a three-item alcohol craving scale [72] and salivation levels. | Trauma and substance cue pairings elicited the greatest subjective craving responses, negative affect, and salivation vs. all other cue combinations. Ambivalent affective responses predicted the strongest craving. |
Tull et al. [19] | 60 cocaine-dependent individuals with (n = 30) and without PTSD (n = 30) in treatment for a SUD | Script-driven imagery. Across two sessions, all participants listened to a personalized cue (trauma or neutral; 1 min) followed by a visualization period (1 min). | Subjective craving response and affect. | Cue-induced cocaine craving was measured using an 11-point scale, with 0 indicating no cravings and 10 indicating very strong cravings. | PTSD was associated with greater craving and negative affect following the trauma cue, but not the neutral cue. Among men, this relationship was mediated by self-conscious emotions. |
Nosen et al. [53] | 120 individuals with comorbid PTSD-AUD in treatment for a SUD. Participants were assigned to receive exposure therapy (n = 52) or health and lifestyle treatment (n = 35); only those who completed treatment (n = 87) were included in analyses. | Script-driven imagery and | Subjective and objective (salivation) craving response, distress, and affect. | Cue-induced craving was measured using a three-item alcohol craving scale [72] and salivation levels. | Pre-treatment, the trauma + substance cue-elicited the strongest craving responses, negative affect, and distress. Post-treatment, trauma cues no longer elicited greater craving compared to substance cues alone. Both treatments led to a decrease in salivation and subjective craving following cue exposure. |
Badour et al. [37]* | 54 veterans with comorbid PTSD-SUD taking part in a COPE RCT. | Participants were presented with personalized | Subjective craving and distress. | Cue-induced craving for participants’ preferred substance was measured using a VAS (0–100). | Between-session reduction of substance cue-induced craving and distress responses were associated with a decrease in PTSD symptom severity. |
Tull et al. [52] | 133 individuals with trauma histories in treatment for a SUD. | Script-driven imagery. Participants listened to a personalized trauma cue (1 min) followed by a visualization period (1 min). | Subjective craving, emotional regulation, negative affect, and salivary cortisol. | Cue-induced craving for participants’ preferred substance was measured using an 11-point scale, with 0 indicating no cravings and 11 indicating very strong cravings. | Following the trauma cue, craving increased relative to the pre-cue baseline. This change was associated with greater PTSD symptom severity. PTSD symptom severity was related to both adaptive and maladaptive emotional regulation strategies. |
Beckham et al. [55] | 129 smokers with (n = 82) and without PTSD (n = 47) were randomly assigned to either a nicotine or a non-nicotine smoking condition. | Script-driven imagery. Participants listened to either a personalized trauma, neutral, or stress cue (30 sec) followed by a visualization period (30 sec) both before and after smoking a nicotine or denicotinized cigarette. | Subjective craving and affect. | Cue-induced craving to smoke was measured using the Questionnaire on Smoking Urges [73]. | Trauma-related cues produced greater cravings and negative affect compared to stress scripts and neutral scripts. This effect was most pronounced among those with PTSD. Smoking either the nicotine or non-nicotine cigarettes reduced craving, negative affect, and PTSD symptoms following the trauma and stress script relative to the neutral script. |
Beckham et al. [30] | 25 veterans receiving PTSD treatment who smoke cigarettes. | Stroop task with combat/trauma-related words. Participants named the ink color of three blocks of trauma-related and three blocks of neutral words. | Subjective craving, affect somatic symptoms, and alertness. | Cue-induced craving to smoke was measured using a modified Smoking Withdrawal Questionnaire Short Form-Revised [71] | Craving, negative affect, somatic symptoms, and lack of alertness were all greater following the presentation of trauma-related words compared to neutral words. |
randomized controlled trial.
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