Estimation Of Physiologic Ability And Surgical Stress Scores Research Articles

Estimation of Physiologic Ability and Surgical Stress (E-PASS) predicts postoperative complications after radical cystectomy.

This study evaluates the effectiveness of the Estimation of Physiologic Ability and Surgical Stress (E-PASS) scoring system in predicting postoperative complications following radical cystectomy (RC). In this single-center retrospective study, we analyzed data from patients who underwent open RC for muscle-invasive bladder cancer by a single surgeon between 2008 and 2023. Cases involving cystectomy for non-urothelial carcinoma or urinary diversion other than ileal conduit were excluded. We recorded patient demographics, body mass index (BMI), history of abdominal/retroperitoneal surgery, ASA score, performance status (PS), and pre-existing conditions, such as hypertension (HT), coronary artery disease (CAD), diabetes mellitus (DM), and chronic kidney disease (CKD). Intraoperative data included surgery duration, blood loss, and need for blood transfusion. Post-operative complications were classified using the Clavien-Dindo system. E-PASS score was calculated using the Preoperative Risk Score (PRS), Surgical Stress Score (SSS), and Comprehensive Risk Score (CRS). The study included 252 patients. Patients who experienced postoperative complications had higher age, BMI, prior surgical history, ASA score, PS, and rates of CAD, HT, DM, and CKD compared to those who did not. Surgery duration, blood loss, blood transfusion requirement, and E-PASS scores (PRS, SSS, CRS) were also higher in this group. The ROC curve for CRS revealed a predictive cutoff of 0.4911 (AUC = 0.905, p < 0.001). Independent risk factors for postoperative complications included high BMI (p = 0.031), longer surgery duration (p < 0.001), HT (p = 0.042), CKD (p = 0.017), and CRS > 0.4911 (p < 0.001). E-PASS system effectively predicts postoperative complications in RC patients.

Efficiency of the estimation of physiologic ability and surgical stress (E-PASS) score in predicting postoperative complications after robot-assisted radical prostatectomy.

Robot-Assisted Radical Prostatectomy (RARP) is increasingly becoming the standard surgical treatment for prostate cancer. While some risk factors for postoperative complications of RARP have been identified, no scoring model that incorporates both preoperative physical status of the patient and intraoperative risk factors has been developed. The Estimation of Physiologic Ability and Surgical Stress (E-PASS) score was initially described to predict postoperative complications after gastrointestinal surgical procedures. This study aims to assess the effectiveness of the E-PASS score in predicting postoperative complications of RARP. A retrospective evaluation was conducted on 204 patients who underwent RARP between 2019 and 2022. Demographic data, parameters indicating patients' preoperative physical condition, and intraoperative risk factors were analyzed. The E-PASS score and subscores were calculated for each patient. Of the patients, 164 (80.4%) were discharged without any postoperative complications (Group 1), and 40 (19.6%) experienced various degrees of complications (Group 2). Patients in Group 2 had higher rates of previous abdominal surgery, elevated Eastern Cooperative Oncology Group (ECOG) performance scores, longer surgical durations, and higher E-PASS scores. To assess the effectiveness of the Comprehensive Risk Score (CRS) as a predictive factor for postoperative complications, a receiver operating characteristic (ROC) curve was constructed with a 95% confidence interval (CI), and a cut-off value was established. The cut-off value for CRS was determined to be -0.0345 (area under the curve [AUC]=0.783, CI: 0.713-0.853; p<0.001). Patients with a CRS higher than the cut-off value had a 16.4 times higher rate of postoperative complications after RARP (95% CI: 5.58-48.5). The E-PASS scoring model successfully predicts postoperative complications in patients undergoing RARP by using preoperative data about the physical status of the patient and surgical risk factors. The E-PASS score and its subscores could be utilized as objective criteria to determine the risk of postoperative complications before and immediately after surgery.

The use of the E-PASS scoring system in determining complication development in patients with isolated acetabular fractures

The decision to treat acetabular fractures is occasionally deferred or foregone in patients perceived to be unfit for surgery. The previously validated estimation of physiologic ability and surgical stress (E-PASS) score has been shown to predict outcome in a variety of fractures, and consists of a preoperative risk score (PRS), a surgical stress score (SSS), and a comprehensive risk score (CRS). To correlate E-PASS and its components with postoperative complication to quantify risk for individual surgical and patient factors in acetabular fracture management. A retrospective review of patient records was performed for all patients with acetabular fractures surgically treated between January 2013 and June 2018 in a level 1 Trauma Centre. Patients with multiple injuries and/or malignancies were excluded. E-PASS scores were determined with standard demographic data and subscores were correlated with complication development. Of the included 106 patients (mean age 61years, range 17-93), complications were reported in 37 (34.9%) patients and 3 (2.8%) died. Hospital postoperative morbidity and mortality rates increased significantly with the PRS and CRS. The SSS did not correlate significantly with frequency of complications. Age was found to be the only significant independent risk factor (p value=0.031, OR=1.03 per year of age). Latent patient factors have a clear influence on adverse outcomes in contrast to controllable factors such as surgical stress indicating an important role for perioperative care in reducing postoperative complications. Integrated orthogeriatric care with assessment of comorbidities, prevention or early recognition, and treatment of perioperative complications is essential.

Mortality and Morbidity Prediction for Older Patients Undergoing Emergency Abdominal Surgery—Comparison of the POSSUM, E-PASS Score, and SASA Score

Several postoperative outcome scoring systems have been developed and validated, combining both pre- and intraoperative factors. Among others are The Portsmouth Physiological and Operative Severity Score for the enUmeration of Mortality and Morbidity (P-POSSUM), the Estimation of Physiologic Ability and Surgical Stress (E-PASS), and the Surgical Apgar Score combined with the American Society of Anesthesiologists (SASA) physical status classification. The aim of this study is to compare the above scoring systems in the prediction of 30-day postoperative mortality and major morbidity in older patients undergoing emergency abdominal surgery. Patients ≥ 65 years were enrolled into the study. Pre- and intraoperative variables were used to calculate the scores and the ROC curve; logistic regression analysis was performed. The study sample comprised 427 older patients with a median age of 77 (range 65–100) years. The most frequent surgical indications were cholecystitis, followed by ileus, complication of colorectal cancer, complicated diverticulitis, and appendicitis. Decreasing SASA and increasing E-PASS and POSSUM/P-POSSUM scores were significantly associated with both 30-day postoperative major complications and death. Multivariate analyses identified all the scores as independent variables to predict postoperative outcomes. The areas under the ROC curve were 0.66–0.81 for predicting mortality and 0.67–0.79 for predicting morbidity (p < 0.01). All the scores were confirmed to be predictive of 30-day postoperative morbidity and mortality. The SASA and the E-PASS scores demonstrated the highest discriminatory ability. However, SASA was found to combine effectiveness and simplicity. Based on this study, we therefore recommend SASA for postoperative risk evaluation in older patients undergoing emergency abdominal surgery.

Clinical study of E-PASS system for peri-operative morbidity of spinal surgery for degenerative scoliosis

Objective To evaluate the feasibility of the Estimation of Physiologic Ability and Surgical Stress (E-PASS) system to predict peri-operative risk in degenerative scoliosis patients scheduled for spinal surgery. Methods Clinical data of 227 cases with degenerative scoliosis (Male∶Female=57∶170, Mean age=66.2±7.7 years), who accepted the operation of instrumentation and fusion in our hospital from January 2013 to July 2017, were retrospectively reviewed according to the E-PASS system, including peri-operative complications. Both hospital stayand post-operative hospital staywere compared between the groups with and withoutthe complications using t test. All E-PASS scores, including Preoperative Risk Score (PRS), Surgical Stress Score (SSS) and Comprehensive Risk Score (CRS), were analyzed between the two groups using Mann-Whitney Utest.The relationship between complications and PRS, SSS and CRS were analyzed using Spearmancorrelation analysis. The predictiveaccuracy of PRS, SSS and CRS were analyzed using the area under the receiver operating characteristic (ROC) curve (AUC). Results There were a total of 47 patients (20.7%) suffering peri-operative complications, including 27 cases (11.9%) with complications at surgical sites and 23 cases (10.1%) with complications at non-surgical sites. Both hospital stay (t=-4.722, P<0.001)and post-operative hospital stay (t= -4.867, P<0.001) were increased because of the complications. All E-PASS scores, including PRS (P=0.005), SSS (P=0.003) and CRS (P<0.001) were significantly higher in patients with peri-operative complications and they were linearly correlated with the overall incidence of the complications(ρ=0.185-0.259). In particular, PRS was correlated with complications at non-surgical sites (ρ=0.162) and SSS with surgical site complications(ρ=0.162). The area under the receiver operating characteristic curve (AUC) for PRS and SSS was higher in patients with complications at non-surgical and surgical sites (AUC=0.655 and 0.650), respectively.The AUC for CRS exhibited good predictive power for both types of complications (AUC=0.662 and 0.631). Conclusion The peri-operative morbidity of spinal surgery for degenerative scoliosis was relatively higher. The E-PASS system could correctly predict the morbidity. Key words: Adult; Lumbar vertebrae; Intervertebral disc degeneration; Scoliosis; Spinal fusion; Intraoperative complications; Postoperative complications

Frailty and postoperative complications in older Chinese adults undergoing major thoracic and abdominal surgery.

Purpose: To determine the association between frailty and postoperative complications in elderly Chinese patients and to determine whether addition of frailty assessment improves the predictive ability of the American Society of Anesthesiologists (ASA) score, Physiological and Operative Severity Score for the Enumeration of Mortality and Morbidity (POSSUM), and Estimation of Physiologic Ability and Surgical Stress (E-PASS) score.Patients and methods: A prospective cohort study was conducted in a tertiary hospital. Elderly patients undergoing major thoracic or abdominal surgery were included. Frailty phenotype and ASA, POSSUM, and E-PASS scores were assessed. Demographic, preoperative, and surgical variables were extracted from medical records. Primary outcome measure was in-hospital Clavien-Dindo ≥ grade II complications. Multiple logistic regression was used to examine the association between frailty and complications. Receiver operating characteristic curves were used to explore the predictive ability of frailty.Results: Prevalence of frailty was 26.12%. Significant differences were observed between the frail and non-frail groups with respect to age, Activities of Daily Living, Charlson Comorbidity Index, respiratory function, presence of malignancy, serum albumin, prealbumin, and hemoglobin levels (P<0.05). ASA, POSSUM, and E-PASS scores were higher in the frail group. After adjusting for all covariates, frailty was significantly associated with postoperative complications in hospital [odds ratio: 16.59, 95% CI: 4.56–60.40, P<0.001]. The area under the curve (AUC) for frailty was 0.762 (95% CI: 0.703–0.814). The AUC for ASA, POSSUM, and E-PASS for prediction of complications was 0.751 (95% CI: 0.692–0.804), 0.762 (95% CI: 0.704–0.814), and 0.824 (95% CI: 0.771–0.870), respectively. Addition of frailty assessment increased the AUC to 0.858 (95% CI: 0.808–0.899), 0.842 (95% CI: 0.790–0.885), and 0.854 (95% CI: 0.803–0.896), respectively.Conclusion: Frailty is an effective predictor of postoperative complications in elderly Chinese patients undergoing major thoracic and abdominal surgery. Frailty assessment can improve the predictive ability of current surgical risk assessment tools. Frailty phenotype should be considered perioperatively. Frailty assessment could also expand the scope for nurses to evaluate patients for safety management.

Estimation of Physiologic Ability and Surgical Stress (E-PASS) versus modified E-PASS for prediction of postoperative complications in elderly patients who undergo gastrectomy for gastric cancer.

Improvements in operative technique and perioperative management have resulted in increasing numbers of elderly patients undergoing gastrectomy for gastric cancer (GC). We evaluated the accuracy of Estimation of Physiologic Ability and Surgical Stress (E-PASS) and modified (m)E-PASS scores in predicting postoperative complications in elderly patients with GC. We retrospectively analyzed short-term outcomes in 413 patients who underwent gastrectomy for GC between 2005 and 2014. They were divided into two groups: Group N comprised 341 non-elderly patients <80years of age and Group E comprised 72 elderly patients ≥80years of age. We calculated the E-PASS and mE-PASS scores and evaluated the correlation between the comprehensive risk score (CRS) and occurrence of postoperative complications. Morbidity rates were 25.5% in Group N and 31.9% in Group E. In Group N, the CRS values of both the E-PASS (P<0.0001) and mE-PASS (P<0.0001) scores were significantly higher in patients with complications than in those without complications. In Group E, although the E-PASS CRS was significantly higher in patients with complications than in patients without complications (P=0.01), the mE-PASS CRS fixed (CRSf) score was not significantly correlated with the occurrence of postoperative complications (P=0.08). Both E-PASS and mE-PASS can be used to predict the occurrence of postoperative complications in GC patients undergoing gastrectomy. However, the E-PASS CRS is more accurate for elderly patients because variations in intraoperative parameters such as operation time, blood loss, and extent of skin incision have a strong influence on the occurrence of postoperative complications.

Validity of E-PASS System for Postoperative Morbidity of Spinal Surgery

A single-center retrospective cohort study. To evaluate the ability of the Estimation of Physiologic Ability and Surgical Stress (E-PASS) system to predict postoperative risk in patients scheduled for spinal surgery. The E-PASS system is a surgical audit to predict postoperative morbidity and mortality in general surgery. It is currently not applied in patients with spinal disorders. The E-PASS system is comprised of a preoperative risk score (PRS), a surgical stress score (SSS), and a comprehensive risk score (CRS). The latter reflects both the PRS and SSS. We calculated the E-PASS scores for 275 consecutive patients who underwent spinal surgery and evaluated the relationship between the incidence of postoperative complications and each score of the E-PASS system and their ability to predict postoperative morbidity. Postoperative complications developed in 31 patients (11.3%). All E-PASS scores were significantly higher in patients with postoperative complications and they were linearly correlated with the overall incidence of postoperative complications. In particular, PRS was correlated with complications at nonsurgical sites and SSS with surgical site complications. The area under the receiver operating characteristic curve (AUC) for PRS and SSS was higher in patients with complications at nonsurgical and surgical sites, respectively. The AUC for CRS exhibited good predictive power for both types of complication. The E-PASS system correctly predicted morbidity. The predictive ability of CRS was good for overall morbidity. The E-PASS system is useful for the accurate prediction of the risk for in-hospital morbidity in individual patients scheduled for spinal surgery.

Evaluation of the utility of the Estimation of Physiologic Ability and Surgical Stress score for predicting post-operative morbidity after orthopaedic surgery.

The purpose of this study was to investigate the utility of the Estimation of Physiologic Ability and Surgical Stress (E-PASS) scoring system for predicting post-operative morbidity. We included 1,883 patients (mean age, 52.1 years) who underwent orthopaedic surgery. The post-operative complications were classified as surgical site and non-surgical site complications, and the relationship between the E-PASS scores and post-operative morbidity was investigated. The incidence of post-operative complications (n = 274) significantly increased with an increase in E-PASS scores (p < 0.001). The areas under the curve for the comprehensive risk score of the E-PASS scoring system for overall and non-surgical site complications were 0.777 and 0.794, respectively. The E-PASS scoring system showed some utility in predicting post-operative morbidity after general orthopaedic surgery. However, creating a new risk score that is more suitable for orthopaedic surgery will be challenging.

Evaluation of the POSSUM, P-POSSUM and E-PASS scores in the surgical treatment of hilar cholangiocarcinoma.

BackgroundThe Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity (POSSUM) model, its Portsmouth (P-POSSUM) modification and the Estimation of physiologic ability and surgical stress (E-PASS) are three surgical risk scoring systems used extensively to predict postoperative morbidity and mortality in general surgery. The aim was to undertake the first study of the predictive value of these models in patients undergoing surgical treatment of hilar cholangiocarcinoma.MethodsA retrospective analysis was performed on data collected prospectively over a 10-year interval from January 2003 to December 2012. The morbidity and mortality risks were calculated using the POSSUM, P-POSSUM and E-PASS equations.ResultsOne hundred patients underwent surgical treatment of hilar cholangiocarcinoma. Complications were seen in 52 of 100 patients (52.0%). There were 10 postoperative in-hospital deaths (10.0%). Of 31 preoperative and intraoperative variables studied, operative type (P = 0.000), preoperative serum albumin (P = 0.003) and aspartate aminotransferase (P = 0.029) were found to be factors multivariate associated with postoperative complications. Intraoperative blood loss (P = 0.015), Bismuth-Corlette classification (P = 0.033) and preoperative hemoglobin (P = 0.041) were independent factors multivariate associated with in-hospital death. The POSSUM system predicted morbidity risk effectively with no significant lack of fit (P = 0.488) and an area under the ROC curve (AUC) of 0.843. POSSUM, P-POSSUM and E-PASS scores showed no significant lack of fit in calculating the mortality risk (P >0.05) and all yielded an AUC value exceeding 0.8. POSSUM had significantly more accuracy in predicting morbidity after major and major plus operations (O:E (observed/expected) ratio 0.98 and AUC 0.901) than after minor and moderate operations (O:E ratio 1.13 and AUC 0.759).ConclusionsPOSSUM, P-POSSUM and E-PASS scores effectively predict morbidity and mortality in surgical treatment of hilar cholangiocarcinoma. However, improvements are still needed in the future because none of these scoring systems yielded an AUC value exceeding 0.9 for operations with all different levels of severity. Only POSSUM had more accuracy in predicting postoperative morbidity after operations with higher severity.Trial registrationThis study was undertaken after obtaining approval from the ethics committee of School of Medicine, Shanghai Jiao Tong University with a trial registration number of http://09411960800.

Using the E-PASS scoring system to estimate the risk of emergency abdominal surgery in patients with acute gastrointestinal disease

The Estimation of Physiologic Ability and Surgical Stress (E-PASS) scoring system, which quantifies a patient's reserve and surgical stress, is used to predict morbidity and mortality in patients before elective gastrointestinal surgery. We conducted this study to clarify whether the E-PASS scoring system is useful for assessing the risks of emergency abdominal surgery. The subjects of this retrospective study were 51 patients who underwent emergency gastrointestinal surgery at a public general hospital. The main outcomes were the E-PASS scores and the postoperative course, defined by mortality and morbidity. Postoperative complications developed in 15 of the 51 patients (29.4%). The E-PASS score was significantly higher in the patients with postoperative complications than in those without (0.61 ± 0.31 vs 0.20 ± 0.35, respectively; n = 36). The morbidity rates were significantly lower in the patients with a value less than 0.5 than in those with a value more than 0.5 (17.1% and 56.3%, respectively; P < 0.01). There were 7 operative deaths among the 16 patients with a high score, versus none among the 9 patients with a low score (P < 0.01). Three patients underwent laparoscopic-assisted bowel resection with a good postoperative course, with scores of less than 0.5. The E-PASS scoring system is useful for surgical decision making and evaluating whether patients will tolerate emergency gastrointestinal surgery. Minimally invasive therapy would assist in lowering the risk of complications.

Can the physiologic ability and surgical stress (E-PASS) scoring system predict operative morbidity after distal pancreatectomy?

Mortality rates after pancreatic resection are now lower than 5% in high-volume centers; however, morbidity remains high. This stresses the importance of identifying accurate predictors of operative morbidity after pancreatic resection. The Estimation of Physiologic Ability and Surgical Stress (E-PASS) scoring system was developed for a comparative audit of general surgical patients. Our previous study confirmed its usefulness for predicting morbidity after pancreaticoduodenectomy. In the present study, we evaluated whether the E-PASS scoring system can predict the occurrence of complications after distal pancreatectomy (DP). The subjects were 46 patients who underwent DP for pancreatic disease. We studied correlations between the incidence of postoperative complications and the preoperative risk score (PRS), surgical stress score (SSS), and comprehensive risk score (CRS) of the E-PASS scoring system. A collective total of 20 postoperative complications developed in 13 (28.3%) of the 46 patients. All E-PASS scores, particularly PRS and CRS, were significantly higher in the patients with postoperative complications than in those without complications. The complication rate increased with increasing PRS, SSS, and CRS scores. The E-PASS scoring system is useful for predicting morbidity after DP.

Reply to Letter to the Editor: New Equations for Predicting Postoperative Risk in Patients with Hip Fracture

I appreciate Dr. Moppett's comments regarding the article by Hirose et al. [2]. In response to his concerns, first, this study was performed to establish and evaluate equations for estimating morbidity and mortality rates in candidates for hip fracture surgery using the Estimation of Physiologic Ability and Surgical Stress (E-PASS) scoring system, and to compare the predictive quality of the E-PASS and POSSUM systems. To accomplish these purposes, all patients with and without complications were studied to develop and evaluate the equations and to compare the predictive quality of inhospital mortality between the E-PASS and P-POSSUM systems. I limited the subjects only in the calculations of predicted 30-day morbidity and mortality rates to compare the predictive quality of the E-PASS and O-POSSUM because O-POSSUM assesses 30-day morbidity and mortality [4]. The E-PASS scoring system can be used preoperatively to predict the occurrence of postoperative morbidity or mortality, and retrospective findings concerning complications are necessary to evaluate the quality of E-PASS. Regarding the second question regarding the statistical assessment of goodness of fit, I used the Hosmer-Lemeshow test for the equations of E-PASS and POSSUM systems. The E-PASS scores showed good concordance with inhospital morbidity (chi square test, p = 0.65), inhospital mortality (p = 0.40), 30-day morbidity (p = 0.35), and 30-day mortality (p = 0.48). The POSSUM scores also were meaningful but showed less concordance with inhospital mortality (p = 0.30), 30-day morbidity (p = 0.11), and 30-day mortality (p = 0.24). Regarding the third point about the rationale for the comparisons with E-PASS and POSSUM, I recognize the POSSUM scoring for predicting 30-day mortality was not particularly useful in the population for hip fracture surgery [5]. However, the POSSUM systems are useful in hip fracture surgery for predicting inhospital morbidity [1] and 30-day morbidity and mortality [6]. Furthermore, the POSSUM and E-PASS systems need not only preoperative evaluation but also surgical factors for calculating their scores. Therefore, I compared these two scoring systems despite the narrow ranges of their surgical stress scores in a population with hip fractures. I agree that the preoperative scoring system, the Nottingham Hip Fracture Score (NHFS) described by Maxwell et al. [3], reasonably predicts 30-day mortality. In contrast, the equations using the E-PASS score developed by Hirose et al. [2] are focused mainly on predicting inhospital risk. Additional studies to evaluate and compare these established risk scoring systems may provide better predictive tools for this population, depending on purpose.

Letter to the Editor: New Equations for Predicting Postoperative Risk in Patients with Hip Fracture

To the Editor: We read with interest the recent article “New Equations for Predicting Postoperative Risk in Patients with Hip Fracture” by Hirose et al. [4] and their previous relevant reports [5, 6]. In their series of studies, they reportedly validated the effectiveness of the Estimation of Physiologic Ability and Surgical Stress (E-PASS) scoring system to predict postoperative risk in patients with hip fracture based on significant correlations between E-PASS scores and hospitalization outcomes. However, we consider the correlation coefficients in their studies [4–6] low (the majority of which were less than 0.2). The degree of the correlation of two variables is determined by the absolute value of either Pearson’s correlation coefficient r or ranked Spearman correlation coefficient ρ. Commonly, |r| > 0.7 or |ρ| > 0.7 indicates a strong correlation, |r| or |ρ| between 0.3 and 0.7 indicates a moderate correlation, and |r| < 0.3 or |ρ| < 0.3 indicates a weak correlation [2]. Thus, although statistically significant, most correlations in their studies were weak. We wonder if one variable can be effective for predicting the other when they are weakly related. In addition, the square of Pearson’s correlation coefficient (r2) may provide an easier interpretation, which represents the proportion of the variation of one variable “explained” by the other [2]; for example, the strongest correlation in one [5] of the articles: surgical stress score (SSS) and costs of postoperative hospitalization (r = 0.44), which correlated significantly (p < 0.0001). However, only approximately 19% (r2 = 0.44 × 0.44%) of the variation of costs can be “explained” by SSS. Considering the even smaller parts of variation of costs “explained” by preoperative risk score and comprehensive risk score (1.4% = 0.12 × 0.12%, 5.3% = 0.23 × 0.23%, respectively), the conclusion that E-PASS was useful for estimating costs should be interpreted with caution. The E-PASS scoring system originally was established to predict adverse postoperative effects in patients undergoing elective gastrointestinal surgery [3]. Although it has been verified to be effective in other types of surgery, such as elective repair of abdominal aortic aneurysms [7] and thoracic surgery [8], it was a poor predictor of complications in patients requiring liver resection [1], and the authors recommended a new modified logistic regression to better predict the postoperative outcome. Therefore, the E-PASS scoring system is not applicable to every surgery without adjustment. Because the majority of the correlations between each E-PASS score and hospitalization outcomes were weak in the serial studies of Hirose et al., we suggest this system may not be a useful predictor for patients with hip fractures, and the E-PASS system might need to be modified for better evaluation.

Reply to Letter to the Editor: New Equations for Predicting Postoperative Risk in Patients with Hip Fracture

I appreciate the interest and comments from Drs. Zhou ZhiJie and Fan ShunWu regarding the article, New Equations for Predicting Postoperative Risk in Patients with Hip Fracture [7] and two previous studies [8, 9]. In several studies, the Estimation of Physiologic Ability and Surgical Stress (E-PASS) scoring system correlated with the incidence of postoperative morbidity and mortality and the severity of potential postoperative complications [8, 9]. It also correlated with the length and cost of hospitalization [9]. However, the correlation coefficients in the studies were low. I recognize the correlation coefficient less than 0.2 means weak correlation. Moreover, the E-PASS score is a poor predictor of complications in patients requiring liver resection although the mortality is effectively predicted [1]. Therefore, the predictive ability of the E-PASS scores was confirmed [7]. First, equations were established to predict the morbidity and mortality rates in candidates for hip fracture surgery using the E-PASS system, and then the equations were compared with the Physiological and Operative Severity Score for enUmeration of Mortality and Morbidity (POSSUM) systems. POSSUM systems are the best available for assessing outcomes by risk adjustment analysis in various types of surgery [4, 6, 10], and their usefulness for hip fracture surgery also has been reported [2, 3]. Hirose et al. [7] showed the E-PASS more correctly predicted the actual morbidity and mortality rates than the POSSUM system. The observed to estimated ratios for morbidity and mortality as a risk-adjusted quality measure were 1.06 and 0.71 calculated by the developed equations, respectively. The predicted rates for inhospital and 30-day morbidity and mortality calculated by POSSUM systems were overestimated by 2.6-fold to 6.7-fold compared with those by E-PASS. Based on these results, it was concluded that the E-PASS score was effective and reproducible as an audit tool to predict the postoperative course of patients considered for hip fracture surgery. The E-PASS scoring system is comprised of a preoperative risk score (PRS), a surgical stress score (SSS), and a comprehensive risk score (CRS) that is determined by the PRS and SSS. In hip fracture surgery, the E-PASS scores have some inconsequential parameters such as the extent of the skin incision, which means a laparotomy and/or thoracotomy for calculating the SSS, because this scoring system was developed originally for gastrointestinal surgery [5]. Therefore, additional studies are being done to modify the E-PASS scores to evaluate more accurately the postoperative course for hip fracture. As few scoring systems are still practical to predict postoperative risk in patients with hip fractures, I recommend the E-PASS system and presume their predictive values will be evaluated in many institutions.

Prediction of Postoperative Ambulatory Status 1 Year After Hip Fracture Surgery

Hirose J, Ide J, Yakushiji T, Abe Y, Nishida K, Maeda S, Anraku Y, Usuku K, Mizuta H. Prediction of postoperative ambulatory status 1 year after hip fracture surgery. Objectives To assess the validity of Estimation of Physiologic Ability and Surgical Stress (E-PASS) for predicting the postoperative risk and ambulatory status long-term follow-up after hip fracture surgery and to establish an algorithm for predicting their ambulatory status. Design Cohort study. Setting Twelve hospitals belonging to the regional network for hip fracture in Japan. Participants The study population was composed of 421 patients; 268 underwent surgery between April 2004 and March 2006 (group A), and 153 were treated surgically between April 2006 and March 2007 (group B). All were operated at 3 surgical hospitals and, subsequently, transferred to 9 rehabilitation centers. Interventions Not applicable. Main Outcome Measures We evaluated various factors, including their E-PASS scores to determine whether there was a correlation with the patients' mortality rate and their ability to walk at discharge and 1 year after surgery (group A). Using multiple regression analysis, we then developed algorithms to predict the ability of elderly patients to walk after hip fracture surgery. We applied the algorithms to group B patients and compared their actual and predicted ambulatory status. Results In group A patients, the postoperative walking ability and mortality rate were highly correlated with their E-PASS scores and dementia status. In group B, our algorithms exhibited good correlations between the predicted and actual walking ability at both time points (ρ=0.6, P<.001). Conclusions In candidates for hip fracture surgery, the E-PASS scores exhibited a good correlation with the patients' functional and survival prognoses, and the algorithm including E-PASS scores and dementia status can accurately estimate the ambulatory status at discharge and 1 year after surgery.

New Equations for Predicting Postoperative Risk in Patients with Hip Fracture

Predicting the postoperative course of patients with hip fractures would be helpful for surgical planning and risk management. We therefore established equations to predict the morbidity and mortality rates in candidates for hip fracture surgery using the Estimation of Physiologic Ability and Surgical Stress (E-PASS) risk-scoring system. First we evaluated the correlation between the E-PASS scores and postoperative morbidity and mortality rates in all 722 patients surgically treated for hip fractures during the study period (Group A). Next we established equations to predict morbidity and mortality rates. We then applied these equations to all 633 patients with hip fractures treated at seven other hospitals (Group B) and compared the predicted and actual morbidity and mortality rates to assess the predictive ability of the E-PASS and Physiological and Operative Severity Score for the enUmeration of Mortality and Morbidity (POSSUM) systems. The ratio of actual to predicted morbidity and mortality rates was closer to 1.0 with the E-PASS than the POSSUM system. Our data suggest the E-PASS scoring system is useful for defining postoperative risk and its underlying algorithm accurately predicts morbidity and mortality rates in patients with hip fractures before surgery. This information then can be used to manage their condition and potentially improve treatment outcomes. Level II, prognostic study. See the Guidelines for Authors for a complete description of levels of evidence.

Is an estimation of physiologic ability and surgical stress able to predict operative morbidity after pancreaticoduodenectomy?

Mortality rates after pancreaticoduodenectomy (PD) are below 4% in high volume centers, although morbidity rates still remain high. Therefore, it is important to clarify a predictor associated with operative morbidity after PD. The estimation of physiologic ability and surgical stress (E-PASS) score has been developed for comparative audit in general surgical patients. To evaluate whether E-PASS scoring system could predict the occurrence of complications after PD. We performed retrospective analysis of 69 patients (42.0% pancreatic cancer, 31.9% bile duct cancer, and others) who underwent PD using the E-PASS as a predictor of morbidity. Correlations between the incidence rates of postoperative complications and the preoperative risk score (PRS), surgical stress score (SSS) and comprehensive risk score (CRS) of the E-PASS scoring system were evaluated. Of the 69 patients 30 (43.5%) experienced a total of 54 postoperative complications. All E-PASS scores, especially PRS and CRS were significantly higher in the patients with postoperative complications than in the patients without complication. The complication rate gradually increased as the PRS, SSS and CRS score increased. Under receiver operating characteristic analysis, if a cut-off point of CRS was 0.75, sensitivity and specificity for the prediction of operative morbidity after PD was 80.0 and 79.5%, respectively. Neoadjuvant chemotherapy and intraoperative radiation therapy (IORT) did not influenced on operative morbidity after PD. E-PASS scoring system is useful to evaluate for morbidity after PD. Neoadjuvant chemotherapy and IORT could be adapted without significant extra risk for surgical complication.