Literature DB >> 27017167

Value of E-PASS models for predicting postoperative morbidity and mortality in resection of perihilar cholangiocarcinoma and gallbladder carcinoma.

Yoshio Haga1, Atsushi Miyamoto2, Yasuo Wada3, Yuko Takami4, Hitoshi Takeuchi5.   

Abstract

BACKGROUND: It has previously been reported that a general risk model, Estimation of Physiologic Ability and Surgical Stress (E-PASS), and its modified version, mE-PASS, had a high predictive power for postoperative mortality and morbidity in a variety of gastrointestinal surgeries. This study evaluated their utilities in proximal biliary carcinoma resection.
METHODS: E-PASS variables were collected in patients undergoing resection of perihilar cholangiocarcinoma and gallbladder carcinoma in Japanese referral hospitals.
RESULTS: Analysis of 125 patients with gallbladder cancer and 97 patients with perihilar cholangiocarcinoma (n = 222). Fifty-six patients (25%) underwent liver resection with either hemihepatectomy or extended hemihepatectomy. The E-PASS models showed a high discrimination power to predict in-hospital mortality; areas under the receiver operating characteristic curve (95% confidence intervals) were 0.85 (0.76-0.94) for E-PASS and 0.82 (0.73-0.91) for mE-PASS. The predicted mortality rates correlated with the severity of postoperative complications (Spearman's rank correlation coefficient: ρ = 0.51, P < 0.001 for E-PASS; ρ = 0.47, P < 0.001 for mE-PASS).
CONCLUSIONS: The E-PASS models examined herein may accurately predict postoperative morbidity and mortality in proximal biliary carcinoma resection. These models will be useful for surgical decision-making, informed consent, and risk adjustments in surgical audits.
Copyright © 2015 International Hepato-Pancreato-Biliary Association Inc. Published by Elsevier Ltd. All rights reserved.

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Year:  2015        PMID: 27017167      PMCID: PMC4814599          DOI: 10.1016/j.hpb.2015.09.001

Source DB:  PubMed          Journal:  HPB (Oxford)        ISSN: 1365-182X            Impact factor:   3.647


  24 in total

1.  Evaluation of an Estimation of Physiologic Ability and Surgical Stress (E-PASS) scoring system to predict postoperative risk: a multicenter prospective study.

Authors:  Y Haga; S Ikei; Y Wada; H Takeuchi; H Sameshima; O Kimura; T Furuya
Journal:  Surg Today       Date:  2001       Impact factor: 2.549

2.  POSSUM: a scoring system for surgical audit.

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Journal:  Br J Surg       Date:  1991-03       Impact factor: 6.939

3.  POSSUM and Portsmouth POSSUM for predicting mortality. Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity.

Authors:  D R Prytherch; M S Whiteley; B Higgins; P C Weaver; W G Prout; S J Powell
Journal:  Br J Surg       Date:  1998-09       Impact factor: 6.939

4.  Protein-sparing therapy after major abdominal surgery: lack of clinical effects. Protein-Sparing Therapy Study Group.

Authors:  G B Doglietto; L Gallitelli; F Pacelli; R Bellantone; M Malerba; A Sgadari; F Crucitti
Journal:  Ann Surg       Date:  1996-04       Impact factor: 12.969

5.  Estimation of Physiologic Ability and Surgical Stress (E-PASS) as a new prediction scoring system for postoperative morbidity and mortality following elective gastrointestinal surgery.

Authors:  Y Haga; S Ikei; M Ogawa
Journal:  Surg Today       Date:  1999       Impact factor: 2.549

6.  Systemic inflammatory response syndrome and organ dysfunction following gastrointestinal surgery.

Authors:  Y Haga; T Beppu; K Doi; F Nozawa; N Mugita; S Ikei; M Ogawa
Journal:  Crit Care Med       Date:  1997-12       Impact factor: 7.598

7.  Estimation of surgical costs using a prediction scoring system: estimation of physiologic ability and surgical stress.

Authors:  Yoshio Haga; Yasuo Wada; Hitoshi Takeuchi; Hirofumi Sameshima; Osamu Kimura; Takumi Furuya
Journal:  Arch Surg       Date:  2002-04

8.  Cholangiocarcinoma. A spectrum of intrahepatic, perihilar, and distal tumors.

Authors:  A Nakeeb; H A Pitt; T A Sohn; J Coleman; R A Abrams; S Piantadosi; R H Hruban; K D Lillemoe; C J Yeo; J L Cameron
Journal:  Ann Surg       Date:  1996-10       Impact factor: 12.969

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

Authors:  Yoshio Haga; Y Wada; H Takeuchi; O Kimura; T Furuya; H Sameshima; Masashi Ishikawa
Journal:  Surgery       Date:  2004-06       Impact factor: 3.982

10.  Intrahepatic cholangioenteric anastomosis in carcinoma of the hilus of the liver.

Authors:  H Bismuth; M B Corlette
Journal:  Surg Gynecol Obstet       Date:  1975-02
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  4 in total

1.  Estimation of physiologic ability and surgical stress (E-PASS) scoring system could provide preoperative advice on whether to undergo laparoscopic surgery for colorectal cancer patients with a high physiological risk.

Authors:  Ao Zhang; Tingting Liu; Kaiyuan Zheng; Ningbo Liu; Fei Huang; Weidong Li; Tong Liu; Weihua Fu
Journal:  Medicine (Baltimore)       Date:  2017-08       Impact factor: 1.889

2.  Usefulness of the estimation of physiologic ability and surgical stress (E-PASS) system for prediction of complication and prognosis in hepatocellular carcinoma patients after hepatectomy.

Authors:  Yili Dai; Guoqiao Chen; Yongle Chen; Zhaoqi Shi; Junhai Pan; Xiaoxiao Fan; Hui Lin
Journal:  Transl Cancer Res       Date:  2022-08       Impact factor: 0.496

3.  Cumulative damage effect of jaundice may be an effective predictor of complications in patients undergoing radical resection of Bismuth type II or above hilar cholangiocarcinoma.

Authors:  Le Luo; Yutong Yao; Haotian Liao; Jiwei Huang; Mingheng Liao; Jinju Wang; Kefei Yuan; Yong Zeng
Journal:  Ann Transl Med       Date:  2021-05

4.  Assessment of postoperative complications using E-PASS and APACHE II in patients undergoing oral and maxillofacial surgery.

Authors:  Kiyohide Ishihata; Yasuyuki Kakihana; Takuya Yoshimura; Juri Murakami; Soichiro Toyodome; Hiroshi Hijioka; Etsuro Nozoe; Norifumi Nakamura
Journal:  Patient Saf Surg       Date:  2018-04-05
  4 in total

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