Peripheral nerve injury is a significant perioperative problem contributing to patient injury and professional liability in the practice of anesthesiology. The reported incidence of perioperative peripheral nerve injury is 0.03% to 0.1%.1–3 According to the American Society of Anesthesiologists (ASA) closed claims analysis studies, perioperative nerve injuries comprise 15% to 16% of anesthesia malpractice claims. This percentage has remained unchanged for almost a decade.4,5
The etiology of nerve injury is multifactorial and complex. Chronic hypertension, diabetes mellitus, tobacco use, neurosurgical procedures, orthopedic procedures, prone position, prolonged hospitalization, extreme body habitus, and male gender have all been associated with perioperative peripheral nerve injury.1,3,4,6,7
Perioperative peripheral nerve injury is characterized by the slowing or cessation of impulse conduction. The fact that it is usually identified in the postoperative period makes it difficult to identify the intraoperative risk factors associated with conduction changes in the peripheral nerve.1,5 An even bigger challenge has been to temporally link such risk factors with the onset of intraoperative conduction changes within the nerve itself.
Neurapraxia is a temporary and reversible failure of conduction in the peripheral nerve. Position-related neurapraxia may indicate impending peripheral nerve injury.8–14 Prevention of upper extremity perioperative peripheral nerve injury by using somatosensory evoked potentials (SSEP) monitoring to identify and reverse upper extremity position–related neurapraxia under general anesthesia has been reported by multiple authors.8–14 Investigating the risk factors associated with position-related neurapraxia under general anesthesia may lead to better understanding of perioperative peripheral nerve injury.
The prone surrender (superman) position has been associated with a significantly greater incidence of intraoperative upper extremity position–related neurapraxia compared with other intraoperative positions during spine surgery.8 The relatively greater incidence of position-related neurapraxia in the prone surrender position is primarily attributable to mechanical factors such as stretch or compression of peripheral nerves. However, in addition to the mechanical factors, intraoperative arterial blood pressure changes may influence nerve conduction and contribute to neurapraxia. In experimental animal models, the effects of compression of the ulnar nerve were enhanced by previous ischemia.15
The purpose of this retrospective analysis of spine surgeries performed under general anesthesia with SSEP monitoring was to determine the relationship between intraoperative arterial blood pressure and intraoperative upper extremity position–related neurapraxia in the prone surrender position.
After obtaining the approval of the IRB at Temple University, we retrospectively reviewed a computerized database of adult spine surgeries performed at Temple University Hospital from November 5, 1998, to June 13, 2007. This time period was selected because spine surgeries performed during this period were monitored by the same neurophysiology team. We believe that monitoring by the same team improved consistency of SSEP monitoring and reporting protocols. The same neuromonitoring montage combination was used in all cases included in the study. The start and end date for data collected are the earliest and latest dates available for the period covered by this neurophysiology team. Inclusion criteria were age ≥ 16 years, spine surgery, SSEP monitoring, and prone surrender superman position. Exclusion criteria were operative positions other than prone surrender position.
The prone surrender (also known as prone superman) position involves having the patient prone with the head in a neutral position, shoulders abducted <90°, and forearms on arm boards parallel to the patient’s longitudinal axis and placed above the shoulders with flexed elbows. The forearms are usually pronated (occasionally in neutral position) and padded.
Patients selected according to the inclusion and exclusion criteria were divided into 2 groups; the case group, which comprised patients who developed intraoperative upper extremity position–related neurapraxia, and the control group, which comprised patients who did not develop intraoperative upper extremity position–related neurapraxia. Upper extremity position–related neurapraxia was defined as a significant upper extremity SSEP change that returned to baseline values before the end of the case and after an intervention to the affected upper extremity by the anesthesiologist. Significant SSEP changes that returned to baseline after increasing mean arterial blood pressure (MAP), decreasing anesthetic depth, or interventions by the surgical team were not considered position related and thus were excluded from the study database.
The following demographic variables were obtained for each patient: age, gender, ASA physical status, date of surgery, weight, height, and body mass index (BMI). BMI was calculated using the following formula: weight in kilograms/height in meters squared.
Preoperative data collected included history of chronic hypertension, diabetes mellitus, peripheral vascular disease, anemia, the use of anti-inflammatory medications, systolic blood pressure (SBP), diastolic blood pressure (DBP), MAP, the presence of uncontrolled hypertension on the day of surgery (DOS), blood glucose level, and hemoglobin level. Uncontrolled hypertension on the DOS was defined as a preoperative SBP ≥140 mm Hg or DBP ≥90 mm Hg in patients with a history of chronic hypertension. Anemia was defined as a preoperative hemoglobin level <12 g/dL in females and <13 g/dL in males. The MAP was calculated using the following formula: MAP = DBP + 1/3 pulse pressure.
Intraoperative data collected included surgical procedure, anatomical location of the procedure, upper extremity nerves stimulated during SSEP monitoring, duration of surgery, average minimum alveolar concentration of inhaled anesthetic, SBP, DBP, MAP, blood glucose level, hemoglobin level, core body temperature, and intraoperative fluid management data. Intraoperative SBP and DBP were recorded as baseline values and then every 5 minutes until the end of the case. Intraoperative MAP was calculated from intraoperative SBP and DBP data obtained at 5-minute intervals. Intraoperative blood pressure measurements were retrieved from paper records by a single senior investigator. Intraoperative blood glucose and hemoglobin levels were obtained from serial arterial blood gas analysis performed during the case and recorded at 15-minute intervals when the data were available. Intraoperative fluid management data were retrieved as total IV volume administered and included crystalloids, colloids, and number of units of packed red blood cells transfused; estimated blood loss also was noted. Intraoperative data were retrieved from the anesthesia record and the neurophysiology report.
For each of the patients who developed intraoperative position-related neurapraxia (case group), we recorded time of onset and duration of position-related neurapraxia. After obtaining the onset and duration of neurapraxia, intraoperative data retrieved for each patient in the case group were truncated at the time of the resolution of neurapraxia. This change was applied to the following intraoperative values: SBP, DBP, MAP, blood glucose, hemoglobin, and core body temperature. Frequency and laterality of the position-related neurapraxia were also noted. If position-related neurapraxia occurred more than once in the same patient, the first incident of position-related neurapraxia was considered the primary outcome, and the intraoperative data sheet was truncated at the time of resolution of the first incident of position-related neurapraxia. Intraoperative data specific for case group were retrieved from the anesthesia record and the neurophysiology report.
Standard SSEP monitoring and practice protocols during the time period under review included the following.
Patients were monitored with 2 Explorer 8 Channel IOM systems, software version 5.71, Model 755 (Bio-Logic Systems Corp., Mundelein, IL). Stainless-steel 12-mm subdermal needle electrodes (Medtronic Xomed, Jacksonville, FL) were used for stimulation. Subdermal needle electrodes (Rochester Electro-Medical, Inc., Tampa, FL) were used for recording. The routine monitoring protocol for the institution specifically included evaluating upper extremity SSEPs for changes related to positioning.
The monitoring protocol primarily followed the cervicomedullary SSEPs in the Fpz-Crv5 montage for assessment of peripheral changes. When a significant change was identified, the neurophysiologist checked for anesthetic, temperature, and arterial blood pressure changes. Global physiologic and anesthetic changes typically manifest as bilateral changes in the cortical responses and warrant a high level of concern if these changes are correlating with low arterial blood pressure compared with the patient’s baseline, indicating reduced brain perfusion. Timing was also key in differentiating between global cortical and position-related upper extremity SSEP changes. If significant bilateral cortical changes occurred acutely, anesthetic depth, temperature, and arterial blood pressure were examined as potential causes, and adjustments made to verify or exclude as an etiologic factor. It is also important to note that upper extremity SSEPs contralateral to the changing response served as a control in the great majority of cases.
The median nerve was stimulated at the wrist. Access limitation to the median nerve at the wrist prompted stimulation of the ulnar nerve at the wrist or at the ulnar notch for monitoring. When a preexisting deficit was identified in 1 nerve, both the median and ulnar nerves SSEPs were monitored to maximize sensitivity. Stimuli were 200 to 300 microseconds constant current square pulses with amplitudes ranging from 5 to 50 mA presented to alternate limbs, each at a rate of 4.9/s (range, 1.9–5.1 stimuli/s). If upper extremity edema was present, stimulus levels were increased to improve stimulus efficacy (typically 2–10 mA increase). The longer pulse widths, slower rates, and greater stimulus levels were sometimes needed for patients with diabetic neuropathy or other peripheral neuropathies. The stimulus rate was chosen to be out of phase with room electrical noise. Sweep duration was 50 milliseconds (occasionally 100 milliseconds). Upper extremity testing was performed approximately every 30 minutes. The montage combination of choice was Fpz-C3’, Fpz-C4’, C3’-C4’, and Fpz-Crv5. Linked Erb’s point recordings were occasionally used. Impedances were checked at baseline and were typically well balanced (<5 kΩ each with <2 kΩ imbalance).
Upper extremity SSEPs were evaluated for changes by measuring the cervicomedullary and cortical peak latencies and amplitudes (N13/N14 and N20 to the next down-going peak) and comparing them with baseline measurements, which were acquired after the patient was positioned and before the use of electrocautery. A change in SSEP was considered significant if the signal amplitude decreased by ≥50% and/or latency increased by ≥10%. When a significant change indicating position-related neurapraxia was confirmed, the anesthesiologist was informed, an intervention was implemented in the affected upper extremity, and SSEPs were promptly re-evaluated. Re-evaluation was consistently performed within 10 minutes of a significant change and intervention. If the SSEP change persisted after an intervention, the anesthesiologist used another intervention and SSEPs were promptly re-evaluated. Subsequent testing followed more frequently than every 30 minutes (typically <15 minutes) until stable recovery was identified. Interventions used by the anesthesiologist at the affected upper extremity upon confirmation of position-related neurapraxia were decreasing shoulder abduction, correcting extreme elbow flexion and extension, moving the affected forearm from prone to neutral position, removing restrictive arm band and tape, modification of elbow padding position, and application of padding if appropriate.
All cases were performed under general anesthesia. IV anesthesia combined with a volatile anesthetic agent was the most common technique. IV anesthesia consisted of propofol infusion with opioid supplementation. Sufentanil infusion or intermittent fentanyl bolusing were the most common techniques for opioid administration. Nitrous oxide was avoided during neuromonitoring because of its effect on SSEP signals. Muscle relaxant was used to facilitate intubation at the start of the case. Neuromuscular blockade was not maintained during the period of neuromonitoring to avoid interference with electromyography monitoring, which was commonly used with SSEP. Motor-evoked potentials were occasionally used and also precluded neuromuscular blockade.
The primary outcome sought was the time to intraoperative position-related neurapraxia as detected by SSEP changes. To adjust for confounding demographic variables among case and control groups and increase precision, we used propensity matching to derive 2 matched study groups. Propensity matching was performed with replacement based on age, gender, BMI, ASA physical status classification, and year of surgery. A 6-nearest neighbor matching method was used with a propensity score generated from 5 demographic variables. Data analysis was performed on preoperative and intraoperative variables using the matched groups.
Demographic and preoperative descriptive summary statistics are presented as mean values with SD for continuous variables and frequencies with percentages for categorical variables. For comparisons between the case and the control groups for demographic and preoperative data, we used a 2-tailed unpaired t test for continuous variables and the Chi-square test for categorical values.
Univariate Cox regression models were used to examine the associations between risk factors and intraoperative upper extremity position–related neurapraxia in the prone surrender position. Univariate Cox regression models with time-varying covariates were used to explore the associations between intraoperative variables and intraoperative position-related neurapraxia. On the basis of the results of these Cox regression models, we further conducted cut-point analyses to investigate the relationship between intraoperative MAP and intraoperative position-related neurapraxia. We constructed Cox regression models to investigate the relationship between the total duration of time spent with MAP <55, <60, <65, <70, <75, and <80 mm Hg and position-related neurapraxia. We also constructed Cox regression models to investigate the relationship between the total duration of time spent with MAP >80, >70, and >60 mm Hg and position-related neurapraxia. Total duration was defined as the cumulative duration of time throughout the entire case with MAP corresponding to the threshold investigated. The amount of time was analyzed and categorized on a 5-minute basis. Kaplan-Meier survival analysis for time to the onset of intraoperative position-related neurapraxia was performed on significant variables, and neurapraxia-free probability distributions were compared using the log-rank test. We tested the proportional hazards assumptions for Cox regression during the univariate analysis. It is confirmed that the assumption of proportional hazards holds for all significant variables in the univariate analysis. Statistical significance for the univariate Cox regression analysis was defined as P value <0.05.
Risk factors significantly associated with intraoperative neurapraxia in the univariate Cox regression models were included in the multivariate Cox regression models. For MAP variables, only the final results of the cut-point MAP analyses were included in the multivariate Cox regression models to provide a clinically meaningful association between MAP and neurapraxia. Risk factors that retained statistical association with neurapraxia when other established risk factors for neurapraxia were included in the multivariate Cox regression model were considered independent risk factors. Negatively correlating MAP variables were included in separate multivariate models. Finally, we examined the potential interaction effects between significant variables in the multivariate Cox regression models.
Bonferroni multiple-comparison correction was used to interpret the final result of multivariate analysis. Statistical significance used to derive the multivariate Cox regression analysis conclusion was defined as 0.05/n (n = number of variables included in the multivariate analysis). On the basis of the results of the univariate analysis, 3 variables were included in the multivariate analysis. Statistical significance for multivariate analysis after Bonferroni correction was defined as P value <0.017 (0.05/3). We reported the uncorrected P values and confidence intervals but interpreted them from the perspective of a Bonferroni correction. All analyses were performed by using the SAS 9.3 (SAS Institute, Cary, NC) and Stata 13.0 (StataCorp, College Station, TX).
Two hundred seven adult patients met the selection criteria in the study. After performing propensity matching, the case group included 32 patients, whereas the matched control group included 120 patients. Because of the limited pool of patients that met the selection criteria (n = 207), not all cases were matched with unique controls. Demographic and preoperative measures between the 2 groups are presented in Table 1. There were no significant differences in demographic and preoperative variables between patients in the case and matched control group. Intraoperative data for the 2 groups are presented in Table 2. There were no obvious differences between the 2 groups in terms of mean intraoperative variables.
Procedure, neuromonitoring, anesthesia, and intraoperative fluid management data are presented in Table 3. There were no significant differences between the 2 groups with regard to type and level of spine surgery, nerves stimulated during SSEP monitoring, minimum alveolar concentration of volatile agent, colloids, packed red blood cells transfusion, and estimated blood loss. Compared with patients in the control group, patients in the case group had significantly longer duration of surgery (P = 0.034) and received a significantly greater volume of crystalloids (P = 0.022). Details of neurapraxia in the case group are presented in Table 4. The mean duration of position-related neurapraxia was 29 minutes (range, 2–212 minutes; SD: 44). The mean onset time of position-related neurapraxia from the beginning of surgery was 283 minutes (range, 79–700 minutes; SD: 142). The mean duration of surgery was 490 minutes (range, 245–885 minutes; SD: 172). Of the 32 patients who had position-related upper extremity neurapraxia, 29 patients had unilateral neurapraxia (91%), whereas 3 patients had bilateral neurapraxia (9%). Position-related neurapraxia occurred once in 28 patients (88%) and twice in 4 patients (12%).
The results of the univariate Cox regression analysis of risk factors for intraoperative upper extremity position–related neurapraxia are presented in Table 5. Kaplan-Meier survival curves comparing time to intraoperative position-related neurapraxia for significant factors identified in the univariate analysis are presented in Figure 1. For MAP variables, only the results of the cut-point analysis were included in the Kaplan-Meier survival analysis.
The results of the multivariate Cox regression analysis of risk factors associated with intraoperative upper extremity position–related neurapraxia in the prone surrender position are presented in Table 6. Intraoperative MAP <55 mm Hg for a total duration of ≥5 minutes was confirmed as an independent risk factor associated with a greater incidence of upper extremity position–related neurapraxia compared with a duration of <5 minutes with MAP <55 mm Hg (hazard ratio, 3.43; confidence interval, 1.445–8.148; P = 0.0052). Intraoperative MAP >80 mm Hg for a total duration of >55 minutes was confirmed as an independent predictor associated with a lower incidence of neurapraxia compared with a total duration of ≤55 minutes with MAP >80 mm Hg (hazard ratio, 0.341; confidence interval, 0.163–0.717; P = 0.0045). The ulnar nerve was not confirmed as an independent risk factor associated with intraoperative position-related neurapraxia compared with the median nerve.
In this study, we identified changes in intraoperative MAP as independent predictors associated with upper extremity position–related neurapraxia in the prone surrender position under general anesthesia. This study included patients undergoing similar procedures in the same high-risk operative position for position-related upper extremity neurapraxia.8 Analysis was performed on a matched data set to adjust for confounding demographic variables and increase precision. As stated in Methods section, intraoperative recorded data for each patient in the case group were truncated at the time of the resolution of neurapraxia. This was done to ensure that all recorded intraoperative variables included in the statistical analysis of risk factors for the case group were obtained before and during the occurrence of neurapraxia. This adjustment was pivotal to the precision and validity of outcome analysis because recorded measurements of variables succeeding neurapraxia cannot possibly be a contributing risk factor. If position-related neurapraxia occurred more than once during the case (occurred in 4 of the 32 cases), the first incident of position-related neurapraxia was considered the primary outcome. This was done to avoid the confounding effect of ischemia associated with the primary incident on the second event as evidenced from experimental animal models indicating lack of complete reperfusion after an episode of peripheral nerve ischemia.16,17 Hypertension, diabetes mellitus, and the use of volatile agents have been shown to affect the quality of neuromonitoring signals.18 In this study, outcome analysis was performed on matched case and control groups with no significant difference between the 2 study group with regard to the incidence of chronic hypertension, uncontrolled hypertension on the DOS, diabetes mellitus, and the average concentration of volatile agents.
The ulnar nerve is the most common nerve injured in the perioperative setting.4,5 In the closed claims analysis of perioperative neuropathy, ulnar nerve injury constituted 28% of all nerve injury malpractice claims associated with anesthesia.5 Swenson et al.19 used SSEP monitoring to determine the relative sensitivity of the ulnar, median, and radial nerves to limb ischemia under general anesthesia in the supine position. The investigators concluded that the ulnar nerve is more sensitive to ischemia compared with median and radial nerves. On the basis of the results of this study, the ulnar nerve was not confirmed as an independent risk factor associated with intraoperative position-related upper extremity neurapraxia in the prone surrender position compared with the median nerve.
Aside from direct trauma leading to axonal injury, the common pathway for nerve injury is nerve tissue ischemia.20 Blood flow to the peripheral nerve is dependent on perfusion pressure. Perfusion pressure represents the difference between the MAP and local tissue pressure. Thus, external compression may increase the local tissue pressure and reduce the perfusion pressure in the peripheral nerve, leading to ischemia and injury. Stretch of the peripheral nerve may increase intraneural pressure and compress intraneural blood vessels leading to reduced tissue perfusion.21,22 Stretching peripheral nerves beyond 5% to 15% of normal resting length is known to cause ischemia and alter nerve function.23–27 Stretching of peripheral nerves may occur when patients are placed in positions they would not tolerate when unanesthetized.
In the presence of mechanical risk factors, such as compression or stretch, the MAP becomes a critical and modifiable determinant of blood flow to peripheral nerves. Because peripheral nerves lack vascular autoregulation, low MAP may lead to ischemia.28,29 The presence of ischemia, even for short durations, enhanced the effect of compression on the ulnar nerve in experimental animals.15 Prolonged hypotension has been associated with ulnar nerve injury.30 In experimental animal models, acute hypotension was associated with a decrease in blood flow in the peripheral nerve.31 At MAPs < 85 mm Hg, there was a marked decrease in peripheral nerve blood flow.27
However, it should be noted that a significant and sustained reduction in blood flow to the peripheral nerve is required to affect the impulse conduction because normally blood flow exceeds the metabolic requirements of the peripheral nerve by a significant margin.21,32 Acute nerve ischemia leads to focal and generalized impairment of impulse conduction across the nerve that can be detected within 5 to 15 minutes of ischemia.33,34 This study showed that intraoperative MAP <55 mm Hg for a total duration of ≥5 minutes was an independent risk factor associated with intraoperative upper extremity position–related neurapraxia in the prone surrender position. Conversely, greater MAP can prevent or reduce the likelihood of neurapraxia by maintaining perfusion pressure above the ischemic threshold. In experimental animal models, high blood flow in the sciatic nerve was observed between MAPs of 80 and 110 mm Hg.25 In this study, MAP >80 mm Hg for a total duration of >55 minutes was an independent predictor associated with a lower incidence of upper extremity neurapraxia in the prone surrender position.
The occurrence of position-related neurapraxia in the prone surrender position is most likely attributable to increased stretch of the brachial plexus and individual peripheral nerves.8 Shoulder girdle depression, shoulder abduction >90°, and lateral rotation of the arm can lead to overstretching of the brachial plexus.35 In human cadaver models, flexion of the elbow caused significant elongation of the ulnar nerve, leading to an increase in intraneural pressure.36,37 Compression of peripheral nerves may also contribute to neurapraxia in the prone position. In the prone surrender position, the forearm is usually pronated increasing direct pressure on the ulnar nerve in the cubital fossa.38 The head of the humerus may act as a fulcrum compressing the neurovascular bundle, especially during abduction and external rotation of the arm.39 The brachial plexus may be compressed between the clavicle and the first rib as the weight of a patient is supported by gel rolls or a Wilson frame. In addition to stretching of the brachial plexus or individual nerves, there may be simultaneous compression at the point of contact with prominent bony structures. Magnetic resonance imaging of the ulnar nerve and the cubital tunnel in human cadavers showed that the ulnar nerve is progressively stretched (up to 18%) over the medial epicondyle with incremental flexion of the elbow.36,40
Limitations of this study include the retrospective nature of the analysis and possible variability in positioning individual patients. In this study, we identified an association between intraoperative arterial blood pressure changes and intraoperative pathophysiologic changes in the peripheral nerve under general anesthesia and not the occurrence of clinical perioperative nerve injury. Although identification of the affected nerve was easily obtained by SSEP monitoring, we could not identify the exact location of compromise along the signal path of that peripheral nerve. Limitations of the neuromonitoring protocols during the study period include limited use of the Erb point and motor-evoked potentials and using primarily cervicomedullary SSEPs via the Fpz-Crv5 montage. Another limitation of this study is that median and ulnar nerve SSEPs were not collected in every patient. These limitations preclude definitive conclusions being drawn but do allow better understanding of intraoperative position-related neurapraxia.
The results identified in this study should be interpreted with caution. Intraoperative MAP targets during surgery in the prone surrender position should be individualized for each patient in relation to preoperative MAP values rather than using a single MAP threshold for all patients.
This study identified changes in intraoperative MAP as independent predictors associated with intraoperative upper extremity position–related neurapraxia in the prone surrender position under general anesthesia. Intraoperative MAP <55 mm Hg for a total duration of ≥5 minutes was an independent risk factor associated with greater incidence of intraoperative upper extremity position–related neurapraxia. Intraoperative MAP >80 mm Hg for a total duration of >55 minutes was an independent predictor associated with a lower incidence of intraoperative upper extremity position–related neurapraxia. Determining the relationship between intraoperative arterial blood pressure and peripheral nerve function under general anesthesia in high-risk operative positions allows greater insight into interventions for preventing or reversing intraoperative position-related upper extremity neurapraxia.
Name: Ihab Kamel, MD.
Contribution: This author helped design the study, conduct the study, analyze the data, and write the manuscript.
Attestation: Ihab Kamel has seen the original study data, reviewed the analysis of the data, approved the final manuscript, and is the author responsible for archiving the study files.
Name: Huaqing Zhao, PhD.
Contribution: This author helped analyze the data and write the manuscript.
Attestation: Huaqing Zhao has seen the original study data, performed the statistical analyses, and approved the final manuscript.
Name: Stephen A. Koch, BS, CNIM.
Contribution: This author helped design the study, conduct the study, and write the manuscript.
Attestation: Stephen A. Koch has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.
Name: Neil Brister, MD, PhD.
Contribution: This author helped design the study, conduct the study, and write the manuscript.
Attestation: Neil Brister has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.
Name: Rodger E. Barnette, MD, FCCM.
Contribution: This author helped design the study and write the manuscript.
Attestation: Rodger E. Barnette has seen the original study data, reviewed the analysis of the data, and approved the final manuscript.
This manuscript was handled by: Sorin J. Brull, MD.
The authors thank Woodrow Wendling, MD, PhD, Emeritus Professor of Anesthesiology, Temple University School of Medicine, Philadelphia, Pennsylvania, for valuable editorial comments and guidance. The authors also thank Ellen Hauck, DO, PhD, Associate Professor of Anesthesiology, Temple University School of Medicine, Philadelphia, Pennsylvania, for valuable editorial comments.
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