title: Value of E-PASS models for predicting postoperative morbidity and mortality in resection of perihilar cholangiocarcinoma and gallbladder carcinoma.
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.
authors.affiliation: Institute for Clinical Research, National Hospital Organization Kumamoto Medical Center, 1-5 Ninomaru, Chuo-ku, Kumamoto 860-0008, Japan; Department of International Medical Cooperation, Graduate School of Medical Sciences Kumamoto University, 1-1-1 Honjo, Chuo-ku, Kumamoto 860-8556, Japan. Electronic address: yoshio@kumamed.jp.
authors.forename: Yoshio
authors.initials: Y
authors.lastname: Haga
authors.affiliation: Department of Surgery, National Hospital Organization Osaka National Hospital, 2-1-14 Hoenzaka, Chuo-ku, Osaka 540-0006, Japan.
authors.forename: Atsushi
authors.initials: A
authors.lastname: Miyamoto
authors.affiliation: Department of Surgery, National Hospital Organization Himeji Medical Center, 68 Honmachi, Himeji, Hyogo 670-8520, Japan.
authors.forename: Yasuo
authors.initials: Y
authors.lastname: Wada
authors.affiliation: Department of Surgery, National Hospital Organization Kyushu Medical Center, 1-8-1 Jigyohama Chuo-ku, Fukuoka 810-8563, Japan.
authors.forename: Yuko
authors.initials: Y
authors.lastname: Takami
authors.affiliation: Department of Surgery, National Hospital Organization Iwakuni Clinical Center, 1-1-1 Atagomachi, Iwakuni, Yamaguchi 740-8510, Japan.
authors.forename: Hitoshi
authors.initials: H
authors.lastname: Takeuchi
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D019540:Area Under Curve; D001650:Bile Duct Neoplasms / Q000401:mortality / Q000473:pathology / Q000601:surgery*; D001662:Biliary Tract Surgical Procedures / Q000009:adverse effects / Q000401:mortality; D003661:Decision Support Techniques; D005260:Female; D005706:Gallbladder Neoplasms / Q000401:mortality / Q000473:pathology / Q000601:surgery*; D006498:Hepatectomy / Q000009:adverse effects / Q000401:mortality; D017052:Hospital Mortality; D006801:Humans; D007564:Japan; D018285:Klatskin Tumor / Q000401:mortality / Q000473:pathology / Q000601:surgery*; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D012372:ROC Curve; D015203:Reproducibility of Results; D018570:Risk Assessment; D012307:Risk Factors; D013997:Time Factors; D016896:Treatment Outcome