Estimation Of Physiologic Ability And Surgical Stress Research Articles

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.

Validation of the Estimation of Physiologic Ability and Surgical Stress (E‐PASS) Score in Liver Surgery

The estimation of physiologic ability and surgical stress (E-PASS) has been used to produce a numerical estimate of expected mortality and morbidity after elective gastrointestinal surgery. The aim of this study was to validate E-PASS in a selected cohort of patients requiring liver resections (LR). In this retrospective study, E-PASS predictor equations for morbidity and mortality were applied to the prospective data from 243 patients requiring LR. The observed rates were compared with predicted rates using Fisher's exact test. The discriminative capability of E-PASS was evaluated using receiver-operating characteristic (ROC) curve analysis. The observed and predicted overall mortality rates were both 3.3% and the morbidity rates were 31.3 and 26.9%, respectively. There was a significant difference in the comprehensive risk scores for deceased and surviving patients (p = 0.043). However, the scores for patients with or without complications were not significantly different (p = 0.120). Subsequent ROC curve analysis revealed a poor predictive accuracy for morbidity. The E-PASS score seems to effectively predict mortality in this specific group of patients but is a poor predictor of complications. A new modified logistic regression might be required for LR in order to better predict the postoperative outcome.

E-PASS for Predicting Postoperative Risk with Hip Fracture: A Multicenter Study

This multicenter study of 813 consecutive patients with hip fracture was performed to estimate the effectiveness and reproducibility of the Estimation of Physiologic Ability and Surgical Stress (E-PASS) scoring system to assess postoperative risk in patients with hip fracture. E-PASS is comprised of a preoperative risk score, a surgical stress score, and a comprehensive risk score based on the preoperative risk score and surgical stress score. Postoperative complications developed in 163 patients (20.0%); 13 (1.6%) died. Hospital postoperative morbidity and mortality rates increased linearly with the preoperative risk score and comprehensive risk score; the correlation was significant. The severity of postoperative complications and the incidence of higher grades of complications increased significantly with rising preoperative risk score and comprehensive risk score. Each E-PASS score also was related significantly with the length of postoperative hospitalization and costs. These results suggest E-PASS is useful for predicting postoperative risk, estimating costs, and for comparing the outcome in patients having surgical treatment of hip fractures. Level II, prognostic study. See the Guidelines for Authors for a complete description of levels of evidence.

Estimation of Physiologic Ability and Surgical Stress (E-PASS system) in patients with esophageal squamous cell carcinoma undergoing resection

Background The Estimation of Physiologic Ability and Surgical Stress (E-PASS) scoring system was designed on the hypothesis that the balance between the patient’s physiological reverse capacity and the surgical stress of operation was important in the development of postoperative complications. The aim of this study was to evaluate whether the E-PASS scoring system could predict the occurrence of complications after elective esophagectomy for esophageal cancer, including salvage esophagectomy.

T1746 Estimation of Physiologic Ability and Surgical Stress (E-PASS) As a Predictor of Immediate Outcome After Pancreatic Surgery: the Score Needs to Be Adapted!

T1746 Estimation of Physiologic Ability and Surgical Stress (E-PASS) As a Predictor of Immediate Outcome After Pancreatic Surgery: the Score Needs to Be Adapted!

Evaluation of estimation of physiologic ability and surgical stress (E-PASS) to predict the postoperative risk for hip fracture in elder patients

The Estimation of Physiologic Ability and Surgical Stress (E-PASS) scoring system is comprised of a preoperative risk score (PRS), a surgical stress score (SSS), and a comprehensive risk score (CRS) determined by both the PRS and SSS. E-PASS predicts the postoperative risk by quantifying the patient's reserve and surgical stress in general surgery. This study aims to evaluate the usefulness of this scoring system for the hospitalization outcomes in hip fracture. A consecutive series of 419 elderly patients who underwent surgery with osteosynthesis or arthroplasty for hip fracture were prospectively assessed for the E-PASS scoring system, which was compared with their postoperative course. The postoperative morbidity and mortality rates in hospital increased linearly as the PRS and CRS increased, with significant correlation (rho = 0.2, P < 0.01) in both operations. The cost of hospital stay also related significantly to the SSS (r = 0.6, P < 0.0001) and CRS (r = 0.4, P < 0.0001). These results suggest that E-PASS may be useful for predicting postoperative risk and estimating medical expense for surgical cases with hip fracture.

Comparison of Risk-Scoring Methods in Predicting the Immediate Outcome after Elective Open Abdominal Aortic Aneurysm Surgery

Background & Objectives: The aim of this study was to apply three simple risk - scoring systems to prospectively collected data on all elective open Abdominal Aortic Aneurysm (AAA) operations in the Cambridge Academic Vascular Unit over a 6 - year period (January 1998 to January 2004), to compare their predictive values and to evaluate their validity with respect to prediction of mortality and post-operative complications. Methods: 204 patients underwent elective open infra-renal AAA repair. Data were prospectively collected and risk assessment scores were calculated for mortality and morbidity according to the Glasgow Aneurysm Score (GAS), VBHOM (Vascular Biochemistry and Haematology Outcome Models) and Estimation of Physiologic Ability and Surgical Stress (E-PASS). Results: The mortality rate was 6.3% (13/204) and 59% (121/204) experienced a post-operative complication (30-day outcome). For GAS, VBHOM and E-PASS the receiver operating characteristics (ROC) curve analysis for prediction of in-hospital mortality showed area under the curve (AUC) of 0.84 (95% confidence interval [CI], 0.76 to 0.92; p<0.0001), 0.82 (95% CI, 0.68 to 0.95; p=0.0001) and 0.92 (95% CI, 0.87 to 0.97; p<0.0001) respectively. There were also significant correlations between post-operative complications and length of hospital stay and each of the three scores, but the correlation was substantially higher in the case of E-PASS. Conclusions: All three scoring systems accurately predicted the risk of mortality and morbidity in patients undergoing elective open AAA repair. Among these, E-PASS seemed to be the most accurate predictor in this patient population.

Comparison of Risk-scoring Methods in Predicting the Immediate Outcome after Elective Open Abdominal Aortic Aneurysm Surgery

The aim of this study was to apply three simple risk - scoring systems to prospectively collected data on all elective open Abdominal Aortic Aneurysm (AAA) operations in the Cambridge Academic Vascular Unit over a 6 - year period (January 1998 to January 2004), to compare their predictive values and to evaluate their validity with respect to prediction of mortality and post-operative complications. 204 patients underwent elective open infra-renal AAA repair. Data were prospectively collected and risk assessment scores were calculated for mortality and morbidity according to the Glasgow Aneurysm Score (GAS), VBHOM (Vascular Biochemistry and Haematology Outcome Models) and Estimation of Physiologic Ability and Surgical Stress (E-PASS). The mortality rate was 6.3% (13/204) and 59% (121/204) experienced a post-operative complication (30-day outcome). For GAS, VBHOM and E-PASS the receiver operating characteristics (ROC) curve analysis for prediction of in-hospital mortality showed area under the curve (AUC) of 0.84 (95% confidence interval [CI], 0.76 to 0.92; p<0.0001), 0.82 (95% CI, 0.68 to 0.95; p=0.0001) and 0.92 (95% CI, 0.87 to 0.97; p<0.0001) respectively. There were also significant correlations between post-operative complications and length of hospital stay and each of the three scores, but the correlation was substantially higher in the case of E-PASS. All three scoring systems accurately predicted the risk of mortality and morbidity in patients undergoing elective open AAA repair. Among these, E-PASS seemed to be the most accurate predictor in this patient population.

Estimation of physiologic ability and surgical stress (E-PASS) as a predictor of immediate outcome after elective abdominal aortic aneurysm surgery

Background The Estimation of Physiologic Ability and Surgical Stress (E-PASS) score was designed on the premise that the balance between the patient’s physiologic reserve capacity and the surgical stress inflicted at operation was important in the occurrence of postoperative complications. The aim of this study was to assess its value in predicting mortality and morbidity after open elective abdominal aortic aneurysm (AAA) repair. Methods E-PASS data items were collected prospectively in a group of 204 patients undergoing elective open AAA repair over a 6-year period. The operative morbidity and mortality rates were compared with the preoperative risk score (PRS), surgical stress score (SSS) and comprehensive risk score (CRS) of E-PASS. The group comprised 180 (88%) males and the median age was 73 (range 44 to 86) years. Results There were 13 (6%) deaths and 121 (59%) experienced a postoperative complication. As the PRS, SSS and CRS increased, the incidence of postoperative morbidity and mortality significantly increased ( P < .0001). Overall mean CRS was .52 (±.27). Mean CRS in the groups of patients who survived and died were .49 (±.24) and .98 (±26), respectively. PRS, SSS, and CRS all had extremely good predictive power for both mortality and morbidity as demonstrated by high areas under the receiver operator curve (range .799 to .953). CRS also showed a strong statistically significant association with the severity of postoperative complication ( P < .0001) and length of hospital stay ( P < .0001). Conclusions The E-PASS model appears to be a promising method of predicting death and the development of postoperative complications in patients undergoing elective open AAA surgery. It requires further validation in arterial surgery at different geographical locations.

Usefulness of an Estimation of Physiologic Ability and Surgical Stress (E‐PASS) Scoring System to Predict the Incidence of Postoperative Complications in Gastrointestinal Surgery

Surgical intervention induces various host responses to maintain homeostasis. When postoperative inflammation is intense and persists for a long time, postoperative complications may occur, sometimes developing into multiple organ failure. Therefore, it is very important to assess surgical stress and predict the risk of morbidity and mortality. Using a new scoring system, an estimation of physiologic ability and surgical stress (E-PASS) scoring system, surgical stress following gastrointestinal surgery was evaluated to assess the feasibility of this scoring system. This system comprises a preoperative risk score (PRS), a surgical stress score (SSS), and a comprehensive risk score (CRS) that is calculated from both the PRS and the SSS. The relationship of the E-PASS score to the incidence of morbidity and mortality was examined. The relationship between the E-PASS score and a sequential organ failure (SOFA) score was also evaluated. The CRS had a significant positive correlation between not only the incidence but also the grade of postoperative complications. Total maximum SOFA score in patients with a CRS of more than 1 was significantly higher than that in patients with a CRS of less than 1. In conclusion, the E-PASS scoring system will be useful for predicting and recognizing the risk of postoperative complications. This scoring system is brief, simple, and reproducible and can be useful in all types of hospitals.

Laparoscopic liver resection of hepatocellular carcinoma

Background We have continued to develop laparoscopic hepatectomy as a means of surgical therapy for hepatocellular carcinoma (HCC). Methods We evaluated the degree of invasiveness and analyzed the outcomes of laparoscopic hepatectomy compared with open hepatectomy for HCC. Results There were notable differences with respect to blood loss and operating time compared with open hepatectomy cases. Patients started walking and eating significantly earlier in the laparoscopic hepatectomy group, and these more rapid recoveries allowed shorter hospitalizations. On the Estimation of Physiologic Ability and Surgical Stress (E-PASS) scoring system, there was no difference in preoperative risk. However, a significant difference was seen in the surgical stress and comprehensive risk scores between the open hepatectomy and laparoscopic hepatectomy groups. Concerning the survival rate and disease-free survival rate, there were no significant differences between procedures. Conclusions Laparoscopic hepatectomy avoids some of the disadvantages of open hepatectomy and is beneficial for patient quality of life (QOL) as a minimally invasive procedure if the operative indications are appropriately based on preoperative liver function and the location and size of HCC.

大腿骨近位部骨折の骨接合術における術前危険度評価システムの検討

The estimation of physiologic ability and surgical stress (E-PASS) scoring system is comprised of a preoperative risk score (PRS), surgical stress score (SSS), and comprehensive risk score (CRS) determined by both the PRS and SSS. E-PASS predicts postsurgical risks by quantification of the patient's reserve and surgical stress, and was previously reported in relation to postoperative complications and the costs of hospital stay in elective gastrointestinal operations.We evaluated the usefulness of this scoring system for 119 consecutive patients who underwent surgery with osteosynthesis for proximal femoral fractures. The postoperative morbidity rates linearly increased as the PRS and CRS increased, and correlated significantly with both the PRS (ρ=0.4, P<0.01)and CRS (ρ=0.4, P=0.02). The costs of hospital stay also related significantly to the PRS (r=0.2, P=0.01) and CRS (r=0.27, P=0.006). These results suggest that E-PASS may be useful for predicting postsurgical risk, estimating medical expenses, and comparing surgical quality for surgical cases of proximal femoral fractures.

E-PASS (The Estimation of Physiologic Ability and Surgical Stress) Scoring System Helps the Prediction of Postoperative Morbidity and Mortality in Thoracic Surgery

Objective: When a new scoring system, ‘E-PASS’, standing for the Estimation of Physiologic Ability and Surgical Stress that predicts the postoperative surgical risk by quantification of the patient’s reserve and surgical stress applied to a population of general thoracic surgery patients, it should be investigated if this system could help us or not. Methods: The comprehensive risk score (CRS) of the E-PASS and the clinical course were evaluated retrospectively in 282 consecutive patients with primary lung cancer (group A), and in 458 patients who underwent elective thoracic operations (group B). Results: The morbidity and mortality rates in both group A and group B increased as the CRS increased. The CRS correlated significantly with the morbidity score, length of stay and cost of hospitalization. Conclusions: E-PASS scoring system may be useful in surgical decision-making and evaluating quality of care in patients who are tolerable for lung resection.

Estimation of physiologic ability and surgical stress (E-PASS) for a surgical audit in elective digestive surgery

Background This study was undertaken to establish an equation to estimate mortality with the use of the prediction scoring system designated as the Estimation of Physiologic Ability and Surgical Stress (E-PASS), and to evaluate the system's usefulness in defining quality of care by comparing it with the Physiologic and Operative Severity Score for the enUmeration for Mortality and morbidity (POSSUM) and Portsmouth-possum (P-POSSUM) scoring systems previously generated for surgical audit. Methods Patients (n = 5212; group A) who underwent elective gastrointestinal surgery were analyzed to establish equations for estimated 30-day and in-hospital mortality rates. The usefulness of E-PASS was evaluated in another series of 1934 patients (group B) who underwent elective digestive surgery in 6 national hospitals. The ratio of observed to estimated mortality rates (OE ratio) of each hospital was defined as a measure of quality. Results In group A, 30-day and in-hospital mortality rates increased as the Comprehensive Risk Score (CRS) increased, providing equations for estimated mortality rates. There was an excellent correlation between the estimated and observed mortality rates in individual diseases: R = 0.958, N = 6, P = .0027 for in-hospital mortality; R = 0.937, N = 6, P = .0059 for 30-day mortality. In all patients of group B, the E-PASS system estimated the 30-day mortality rates by 0.63-fold (linear analysis), whereas the POSSUM score was 11.0-fold (exponential analysis). The E-PASS system estimated the in-hospital mortality rates by 1.2-fold (linear analysis), whereas the P-POSSUM score was 4.5-fold (linear analysis). The OE ratios for 30-day mortality among the 6 hospitals defined by E-PASS correlated well with those defined by POSSUM: R = 0.996, N = 6, P<.0001. Similarly, the OE ratios for in-hospital mortality defined by E-PASS were also highly correlated with those defined by P-POSSUM:( R = 0.929, N = 6, P = .0075. Conclusions The E-PASS scoring system may be useful in defining surgical quality and may be more accurate than existing systems in evaluating elective digestive surgery.