Advances in surgical techniques and medical support. Predictive value of E-PASS and POSSUM systems for postoperative risk assessment of spinal surgery

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1 J Neurosurg Spine 20:75 82, 2014 AANS, 2014 Predictive value of E-PASS and POSSUM systems for postoperative risk assessment of spinal surgery Clinical article *Jun Hirose, M.D., Ph.D., 1,2 Takuya Taniwaki, M.D., Ph.D., 1 Toru Fujimoto, M.D., Ph.D., 1 Tatsuya Okada, M.D., Ph.D., 1 Takayuki Nakamura, M.D., 1 Nobukazu Okamoto, M.D., Ph.D., 1 Koichiro Usuku, M.D., Ph.D., 2 and Hiroshi Mizuta, M.D., Ph.D. 1 Departments of 1 Orthopaedic Surgery and 2 Medical Information Science and Administration Planning, Kumamoto University Hospital, Kumamoto, Japan Object. The Estimation of Physiological Ability and Surgical Stress (E-PASS) and Physiological and Operative Severity Score for the enumeration of Mortality and Morbidity (POSSUM) systems are surgical risk scoring systems that take into account both the patient s preoperative condition and intraoperative variables. While they predict postoperative morbidity and mortality rates for several types of surgery, spinal surgeries are currently not included. The authors assessed the usefulness of E-PASS and POSSUM algorithms and compared the predictive ability of both systems in patients with spinal disorders considered for surgery. Methods. The E-PASS system includes a preoperative risk score, a surgical stress score, and a comprehensive risk score that is determined by both the preoperative risk score and surgical stress score. The POSSUM system is composed of a physiological score and an operative severity score; its total score is based on both the physiological score and operative severity score. The authors calculated the E-PASS and POSSUM scores for 601 consecutive patients who had undergone spinal surgery and investigated the relationship between the individual scores of both systems and the incidence of postoperative complications. They also assessed the correctness of the predicted morbidity rate of both systems. Results. Postoperative complications developed in 64 patients (10.6%); there were no in-hospital deaths. All E- PASS scores (p 0.001) and the operative severity score and total score of the POSSUM (p < 0.03) were significantly higher in patients with postoperative complications than in those without postoperative complications. The morbidity rates correlated linearly and significantly with all E-PASS scores (p 0.001); their coefficients (preoperative risk score, r = 0.179; surgical stress score, r = 0.131; and comprehensive risk score, r = 0.198) were higher than those for the POSSUM scores (physiological score, r = 0.059; operative severity score, r = 0.111; and total score, r = 0.091). The area under the receiver operating characteristic curve for the predicted morbidity rate was for the E-PASS and for the POSSUM system. Conclusions. As E-PASS predicted morbidity more correctly than POSSUM, it is useful for estimating the postoperative risk of patients considered for spinal surgery. ( Key Words spinal surgery outcome postoperative morbidity risk score Advances in surgical techniques and medical support strategies decrease surgical risks. Surgical outcomes and the quality of care are commonly measured using crude mortality and morbidity rates, and surgical audits are now widely implemented to predict surgical risks for general surgery. 5,6,19,27,29 Abbreviations used in this paper: AUC = area under the ROC curve; E-PASS = Estimation of Physiological Ability and Surgical Stress; PMR = predicted morbidity rate; POSSUM = Physiological and Operative Severity Score for the enumeration of Mortality and Morbidity; ROC = receiver operating characteristic. * Drs. Hirose and Taniwaki contributed equally to this work. J Neurosurg: Spine / Volume 20 / January 2014 The Estimation of Physiological Ability and Surgical Stress (E-PASS) score is based on multiple regression analysis of patients treated by elective gastrointestinal surgery. 6 It predicts mortality and morbidity rates in digestive, 7,24 thoracic, 40 vascular, 35,36 pancreatic, 11,12 hepatic, 25 and hip fracture surgery. 14,15 The Physiological and Operative Severity Score for the enumeration of Mortality and Morbidity (POSSUM) system includes physiological and operative assessments and multivariate discriminant analysis This article contains some figures that are displayed in color on line but in black-and-white in the print edition. 75

2 J. Hirose et al. to predict 30-day morbidity and mortality rates. 5 It is the most-tested system for assessing outcomes by risk-adjusted analysis, 17 and it is applied in patients considered for vascular, 39 orthopedic, 20 and colorectal 37 surgery. While these practical scoring systems take into account both the patient s preoperative condition and intraoperative variables to predict postoperative complications, they are currently not applied to patients with spinal disorders. We compared the usefulness of E-PASS and POSSUM algorithms to investigate the predictive power of both systems for patients with spinal diseases considered for surgery. Methods Patients and Treatments This study received institutional review board approval from Kumamoto University and conformed with the Declaration of Helsinki. We retrospectively evaluated 601 consecutive patients who underwent spinal surgery between January 2005 and December 2009 at Kumamoto University Hospital. The surgical procedures included laminoplasty and anterior fusion to treat cervical disorders (169 patients); posterior fusion for thoracic disorders (16 patients); laminectomy, posterior fusion, and discectomy for lumbar disorders (259 patients); resection of spinal tumors (117 patients); spinal fusion for scoliosis (27 patients); and curettage or spinal fusion for pyogenic spondylitis (13 patients). The same 4 surgeons performed all operations and they used nearly uniform operative techniques. Calculations Underlying the Scoring Systems The POSSUM system consists of a physiological score and an operative severity score; its total score is based on both the physiological score and operative severity score (Appendix 1). The E-PASS system is composed of a preoperative risk score, a surgical stress score, and a comprehensive risk score that is determined by both the preoperative risk score and surgical stress score (Appendix 2). The predicted morbidity rate (PMR) is based on E-PASS 13 and POSSUM 5 scores. We established the physiological and operative parameters shown in Table 1 by using information contained in medical records, preoperative nursing check notes, and computerized and filed laboratory results. All physiological and operative parameters were available for all patients. We calculated the E-PASS and POSSUM scores and the PMR for each system and examined the relationship between individual scores obtained for each system and the incidence of postoperative complications in patients who had received medical or interventional treatment. Statistical Analysis Using the Mann-Whitney U-test for continuous variables, we determined the significance of differences in the examined data. These included intra- and postoperative parameters and the E-PASS and POSSUM scores of patients with and without postoperative complications. The correlation between different continuous variables TABLE 1: Variables considered in each model* Parameters E-PASS POSSUM physiological age, severe heart disease, severe pulmonary disease, diabetes mellitus, performance status index, ASA classification operative blood loss, body weight, operative time, extent of skin incision of the E-PASS and POSSUM scores and the incidence of postoperative complications was quantified using the ranked Spearman correlation coefficient. We generated a standard receiver operating characteristic (ROC) curve for each PMR obtained with the E-PASS and POSSUM system, plotting sensitivity versus specificity. The area under the ROC curve (AUC) was used to evaluate the discriminatory ability of each system to detect postoperative morbidity. Differences of p < 0.05 were considered statistically significant. All statistical tests were done using the SPSS v16 software package (SPSS Inc.). Results age, cardiac signs, respiratory history, systolic blood pressure, pulse rate, GCS score, hemoglobin, white blood cell count, serum urea, serum sodium, serum potassium, electrocardiogram op severity, reop, blood loss, peritoneal soiling, malignancy, urgency of op * ASA = American Society of Anesthesiologists; GCS = Glasgow Coma Scale. Patient Characteristics and Clinical Outcomes Of the 601 patients, 327 were male and 274 were female, and their mean age was 58.7 years (range 7 88 years) (Table 2). As shown in Table 3, postoperative complications (for example, peripheral nerve disorder, delirium, urinary tract infection, wound infection, liquorrhea, epidural hematoma formation, pneumonia, and deep vein thrombosis) developed in 64 patients (10.6%). There were no in-hospital deaths. Relationship Between Postoperative Complications and E-PASS and POSSUM Scores All E-PASS scores were significantly higher in patients with postoperative complications than in those without postoperative complications. The operative severity and total scores, but not the physiological score, of the POSSUM system were significantly higher in patients with postoperative complications than in those without postoperative complications (Table 2). There was a linear and significant correlation with the preoperative risk score (r = 0.179, p < 0.001), surgical stress score (r = 0.131, p = 0.001), and comprehensive risk score (r = 0.198, p < 0.001) of E-PASS (Fig. 1). The coefficients of physiological score (r = 0.059, p = 0.075), operative severity score (r = 0.111, p = 0.003), and to- 76 J Neurosurg: Spine / Volume 20 / January 2014

3 E-PASS and POSSUM for spinal surgery risk assessment TABLE 2: Clinical data on patients with spinal disorders* Morbidity Variable Total Present Absent p Value no. of patients M/F ratio 327:274 37:27 290: age in yrs 58.7 ± ± ± postop days 21.4 ± ± ± 12.2 <0.001 E-PASS PRS ± ± ± <0.001 SSS ± ± ± CRS ± ± ± <0.001 POSSUM PS 22.1 ± ± ± OSS 9.0 ± ± ± TS 31.1 ± ± ± * CRS = comprehensive risk score; OSS = operative severity score; PRS = preoperative risk score; PS = physiological score; SSS = surgical stress score; TS = total score. According to either the chi-square test or Mann-Whitney U-test. Values are presented as the mean ± SD. tal score (r= 0.091, p = 0.013) of POSSUM were lower than the preoperative risk score, surgical stress score, and comprehensive risk score (Fig. 2). The ROC curves of each model for the detection of postoperative complications are shown in Fig. 3. The AUC of PMR for E-PASS was (95% CI ) and higher than for POSSUM (0.588; 95% CI ). Discussion We analyzed the relationship between postoperative morbidity and E-PASS and POSSUM scores and compared the 2 systems for their ability to predict surgical risk in patients considered for various types of spinal surgery. All E-PASS scores were significantly higher in patients with postoperative complications than in those without postoperative complications. All E-PASS scores TABLE 3: Postoperative morbidity in 64 patients (10.6%) treated by spinal surgery Type of Morbidity No. of Patients Rate per 100 neurological renal psychiatric infection liquorrhea hematoma pulmonary digestive cardiovascular others total 65* * One patient presented with multiple complications. J Neurosurg: Spine / Volume 20 / January 2014 were also correlated with the incidence of postoperative complications. In contrast, POSSUM scores exhibited weaker correlations. The AUC of the ROC curves for the frequency of postoperative complications and the PMR were higher for E-PASS than POSSUM. The POSSUM system over-predicts postoperative morbidity and mortality rates, although it is the most widely used system for surgical patients. 17 The Portsmouth predictor modification of POSSUM (P-POS- SUM), 29 developed to correct for the overprediction by POSSUM of hospital mortality rates especially in lowrisk patients, is a better fit with the observed results. 34,38 Also, in spinal surgery, P-POSSUM, but not POSSUM, has been reported as a good predictor of mortality, 4,10,31 although at the time of these assessments the methodology of POSSUM and P-POSSUM was similar 2,16,21,39 and no Portsmouth morbidity model has been published to date. We applied the POSSUM scoring system to predict postoperative complications in our series. In their assessment of the POSSUM system in orthopedic surgery, Mohamed et al. 20 used modified operative severity scoring to assess the quality of care with respect to 30-day morbidity and mortality rates. Chen et al. 4 used the West Australian Categorisation of Operative Severity instead of the original classification of operative severity in the POSSUM system for neurosurgical operations and showed that the former had greater predictive ability than the original classification; we used their classification in our series of 601 patients who underwent spinal surgery. We found that E-PASS predicted morbidity more correctly than POSSUM; it yielded more accurate predictions and possessed good calibration power. Other investigators have reported that E-PASS was more accurate than POSSUM for the preoperative prediction of 30-day and in-hospital morbidity and mortality rates in patients with digestive disease 7,8 and hip fracture. 13 Haga and colleagues, 8 who produced algorithms for predicting 30-day 77

4 J. Hirose et al. Fig. 1. Relationship between postoperative morbidity and E-PASS scores. A: Preoperative risk score (PRS). B: Surgical stress score (SSS). C: Comprehensive risk score (CRS). and in-hospital mortality rates by using the comprehensive risk score of E-PASS, documented an excellent correlation between predicted and observed mortality rates in patients treated by elective gastrointestinal surgery. We previously developed algorithms for predicting in-hospital morbidity and mortality rates by using the preoperative risk score of E-PASS, 13 because this score facilitates predicting the postoperative course of patients considered for surgery and because we found in other studies that the surgical stress score of E-PASS showed no correlation with surgical outcomes in patients with hip fracture In those investigations we calculated the PMR by using the preoperative risk score for hip fracture. In spinal surgery, the surgical stress score correlated with the incidence of complications and the comprehensive risk score showed a higher coefficient than the preoperative risk score. An algorithm for determining the comprehensive risk score must be able to predict postoperative Fig. 2. Relationship between postoperative morbidity and POSSUM scores. A: Physiological score (PS). B: Operative severity score (OS). C: Total score (TS). risks more accurately because the predictive power of the preoperative risk score is adequate. However, the correlation coefficients were low. Also, the AUC of PMR for E- PASS was relatively low even though it was higher than it was for POSSUM. Additional studies may be needed to modify the E-PASS scores to evaluate more accurately the postoperative course for spinal surgery. Our study has some limitations. First, because it was retrospective in nature, the study may have underestimated the actual rate of complications due to selection bias and unequal groups in terms of risk factors. 3,22 To minimize these effects, we only considered demographic variables, surgical details, and complications that would be uniformly reported for all patients. Second, our study included various surgical procedures performed to address a multitude of spinal disorders. Of the 601 patients, 553 (92%) presented with degenerative spinal disease, chronic vertebral compression fractures, or primary spinal tumors, and 583 (97%) underwent elective surgery. We found no significant 78 J Neurosurg: Spine / Volume 20 / January 2014

5 E-PASS and POSSUM for spinal surgery risk assessment spinal surgery. We documented that the E-PASS is more accurate than the POSSUM system for predicting postoperative complications. An accurate evaluation of the potential morbidities elicited by spinal procedures is necessary for treatment planning, for acquiring patient informed consent, and for reviewing risk management and the quality of care. Information technology and the availability of electronic patient records should make risk score calculations possible with a click of the mouse. To determine E-PASS scores, routine clinical and intraoperative data are needed. These data combined with the estimated blood loss and the operative time will facilitate estimation of the patient risk before surgery. Furthermore, calculation of the surgical stress score and comprehensive risk score immediately after surgery using actual blood loss and operative time data may help to determine the risk for perioperative morbidity and allow the timely initiation of appropriate treatments. The E-PASS system provides good calibration power, is clinically useful for the accurate prediction of surgical risks in patients considered for spinal surgery, and can be used to assess hospital morbidity rates, to stratify surgical risks, and as a useful audit tool. Fig. 3. Receiver operating characteristic (ROC) curves of each model for the detection of postoperative complications. difference in the morbidity rate among our patients with different diseases (p = 0.070, data not shown), although higher rates were reported in patients surgically treated for spinal cord injury 18 and spinal metastasis. 28 Because only a small number of these diseases was included in the current study, we are in the process of carrying out prospective multicenter investigations on larger study populations at higher risk for postoperative complications to validate the predictive ability of the E-PASS system for specific spinal diseases and surgical procedures. Third, the end point of our study was discharge from the hospital. Because the average length of postoperative hospitalization was 21.4 days for all patients and 19.1 days for patients without complications, we did not calculate the 30-day morbidity rate, although POSSUM was developed to predict 30-day morbidity and mortality rates. Complications such as surgical site infection that may have occurred after discharge were not considered in the current study; these issues must be addressed in investigations that involve longer postoperative follow-up periods. Finally, none of the patients in the current series died; 92% of the patients presented with degenerative spinal disease, compression fractures, or primary spinal tumors, and 97% of the 601 patients underwent elective surgery. Although the mortality rate of elective surgery for spinal disorders is very low, 18,22,23,32,33 it increases sharply in patients who undergo surgery for spinal cord injury 18 and spinal metastasis 28 and in patients with diseases that necessitate surgery. 9 Because in-hospital mortality continues to be a serious problem, further studies on patients with specific categorized diseases are needed. Conclusions Our study provides evidence for a significant positive association between E-PASS scores and morbidity after J Neurosurg: Spine / Volume 20 / January 2014 Disclosure The authors report no conflict of interest concerning the materials or methods used in this study or the findings specified in this paper. Author contributions to the study and manuscript preparation include the following. Conception and design: Hirose. Acquisition of data: Taniwaki, Fujimoto, Okada, Nakamura, Okamoto. Analysis and interpretation of data: Taniwaki. Drafting the article: Hirose. Critically revising the article: all authors. Reviewed submitted version of manuscript: all authors. Approved the final version of the manuscript on behalf of all authors: Hirose. Statistical analysis: Hirose, Taniwaki, Usuku. Study supervision: Mizuta. References 1. Alberti KG, Zimmet PZ: Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation. Diabet Med 15: , Brooks MJ, Sutton R, Sarin S: Comparison of Surgical Risk Score, POSSUM and p-possum in higher-risk surgical patients. Br J Surg 92: , Campbell PG, Malone J, Yadla S, Chitale R, Nasser R, Maltenfort MG, et al: Comparison of ICD-9-based, retrospective, and prospective assessments of perioperative complications: assessment of accuracy in reporting. Clinical article. J Neurosurg Spine 14:16 22, Chen W, Fong JW, Lind CR, Knuckey NW: P-POSSUM scoring system for mortality prediction in general neurosurgery. 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Eur Surg Res 36: , 2004 Manuscript submitted July 13, Accepted September 24, Portions of this work were presented in poster form at the 2012 Annual Meeting of the American Academy of Orthopaedic Surgeons, San Francisco, CA, February 7 11, Please include this information when citing this paper: published online November 8, 2013; DOI: / SPINE Address correspondence to: Jun Hirose, M.D., Ph.D., Department of Orthopaedic Surgery, Kumamoto University Hospital, Honjo, Chuoku, Kumamoto , Japan. hirojun-mk@ umin.ac.jp. 80 J Neurosurg: Spine / Volume 20 / January 2014

7 E-PASS and POSSUM for spinal surgery risk assessment Appendix Table 1: Clinical variables* Appendix 1: Algorithms of the POSSUM System 5,30 Score Variable physiological age (yrs) cardiac signs no failure on cardiac drugs or edema, warfarin raised JVP steroids CXR normal borderline cardiomegaly cardiomegaly respiratory signs normal SOB exertion SOB stairs SOB rest CXR normal mild COAD moderate COAD other changes systolic blood pressure (mm Hg) , , pulse rate (beats/min) , , 39 GCS score serum urea (mmol/l) serum Na (mmol/l) serum K (mmol/l) , , , 6 hemoglobin (g/dl) , , , 18.1 WBC ( /L) , , 3 ECG normal atrial fibrillation (rate 60 90) other changes operative magnitude minor intermediate major major+ no. of ops w/in 30 days 1 2 >2 intraop blood loss (ml) contamination none incised wound minor contamination or necrotic tissue gross contamination or necrotic tissue presence of malignancy none primary only node metastases distant metastases timing of op elective emergency (<48 hrs): resuscitation possible emergency (<6 hrs): immediate op * COAD = chronic obstructive airway disease; CXR = chest x-ray; ECG = electrocardiograph; GCS = Glasgow Coma Scale; JVP = jugular venous pressure; SOB = shortness of breath; WBC = white blood cell count. When 2 sets of data are present for a single variable, it is because one is higher and the other is lower than the data of Score 1. Surgery of minor magnitude includes carpal tunnel or ulnar neurolysis; moderate surgery includes bur holes for subdural hemorrhage, depressed skull fracture, discectomy, intracranial pressure monitor insertion, laminectomy, Ommaya reservoir insertion, or spinal hardware removal; major surgery includes craniectomy, craniotomy, cranioplasty, deep brain stimulation, external ventricular drain insertion, shunt procedure, spinal fusion, stereotactic biopsy, transoral procedure, or other instrumented spinal surgery; and major+ surgery includes treatment of an aneurysm, arteriovenous malformation, intramedullary tumor, or skull base resection. 4 Predictive Equations of the POSSUM System Predicted morbidity rate for 30 days: Ln R1/1 R1 = (0.16 physiological score) + (0.19 operative severity score), where R1 = predicted risk of morbidity. Appendix 2: Algorithms of the E-PASS System Algorithms for Calculating the E-PASS Scores 6 Preoperative risk score (PRS) = X X X X X X 6, where X 1 is the patient age, X 2 the presence (1) or absence (0) of severe heart disease, X 3 the presence (1) or absence (0) of severe pulmonary disease, X 4 the presence (1) or absence (0) of diabetes mellitus, X 5 the performance status index (0 4), and X 6 the American Society of Anesthesiologists (ASA) physiological status classification (1 5). J Neurosurg: Spine / Volume 20 / January 2014 Surgical stress score (SSS) = X X X 3, where X 1 is the amount of blood loss per kilogram body weight (g/kg), X 2 the operative time (hours), and X 3 the extent of skin incision (0, minor incision without laparotomy and/ or thoracotomy; 1, laparotomy or thoracotomy alone; and 2, both laparotomy and thoracotomy). Comprehensive risk score (CRS) = (PRS) (SSS). Severe heart disease was defined as heart failure corresponding to Class III or IV of the New York Heart Association (NYHA) classification or severe arrhythmia requiring mechanical support. Severe pulmonary disease was defined as any condition with a percentage vital capacity (%VC) of less than 60% and/or a forced expiratory volume 1.0% (FEV1.0%) of less than 50%, or an arterial blood oxygen level of less than 60 mm Hg without oxygen being supplied to patients in whom pulmonary function could not be measured. 15 Diabetes mellitus was based on WHO criteria. 1 The 81

8 J. Hirose et al. performance status index was defined according to Eastern Cooperative Oncology Group criteria 26 as follows: Grade 0 = fully active and able to perform all pre-disease activities without restriction; Grade 1 = restricted strenuous physical activity but ambulatory and able to carry out work of a light or sedentary nature (for example, light house and office work); Grade 2 = ambulatory and capable of all self-care but unable to carry out any work activities for up to or more than 50% of waking hours; Grade 3 = capable of only limited self-care and confined to bed or chair for more than 50% of waking hours; and Grade 4 = completely disabled, unable to perform any self-care, and totally confined to bed or chair. The ASA classification is as previously described: 27 Class 1 = normally healthy, Class 2 = mild systemic disease, Class 3 = severe systemic disease that is not incapacitating, Class 4 = incapacitating systemic disease that is a constant threat to life, and Class 5 = moribund, not expected to survive for 24 hours with or without surgery. Predicted Equations of the E-PASS System 13 In-hospital morbidity rates for hip fracture surgery (%): Y = (PRS) (PRS) J Neurosurg: Spine / Volume 20 / January 2014