Literature DB >> 26747226

The impact of chronic liver disease on the risk assessment of ACS NSQIP morbidity and mortality after hepatic resection.

Victor M Zaydfudim1, Matthew J Kerwin2, Florence E Turrentine3, Todd W Bauer2, Reid B Adams2, George J Stukenborg4.   

Abstract

BACKGROUND: The American College of Surgeons (ACS) National Surgical Quality Improvement Program (NSQIP) risk-adjustment model for patients who require hepatic resection does not include metrics of underlying chronic liver disease. The applicability of the current risk adjustment model is under debate. This study aims to assess the impact of chronic liver disease on the ACS NSQIP estimates of postoperative morbidity and mortality. STUDY
DESIGN: This retrospective cohort study included all cases of hepatic resection at our quaternary referral institution between 2006 and 2013. Metrics of chronic liver disease were abstracted and linked with the ACS NSQIP risk-adjustment model estimated probabilities of morbidity and mortality for each case. Sequential general linear models were used to estimate differences in ACS NSQIP probabilities of morbidity and mortality associated with measures of underlying chronic liver disease.
RESULTS: A total of 522 hepatic resections were performed during the study period. The patient cohort included 91 patients with fibrosis (17%) and 38 patients with cirrhosis (7%). The mean ACS NSQIP estimated probability of morbidity was 0.24 ± 0.11 and probability of mortality was 0.02 ± 0.02. Fibrosis was associated with increased probability of morbidity (0.26 ± 0.11; P = .019); cirrhosis was also associated with increased probability of morbidity (0.27 ± 0.10; P = .059). Parenchymal liver disease was not associated with increased probability of mortality (all P ≥ .62). Increased probabilities of mortality were associated with diagnosis and extent of resection (both P < .001).
CONCLUSIONS: In patients selected for hepatectomy, metrics of chronic liver disease were associated with differences in ACS NSQIP estimated probability of morbidity. Incorporation of metrics of chronic liver disease into the ACS NSQIP targeted hepatectomy modules should improve estimates of risk after hepatic resection.
Copyright © 2016 Elsevier Inc. All rights reserved.

Entities:  

Mesh:

Year:  2015        PMID: 26747226     DOI: 10.1016/j.surg.2015.11.020

Source DB:  PubMed          Journal:  Surgery        ISSN: 0039-6060            Impact factor:   3.982


  5 in total

1.  The impact of cirrhosis and MELD score on postoperative morbidity and mortality among patients selected for liver resection.

Authors:  Victor M Zaydfudim; Florence E Turrentine; Mark E Smolkin; Todd B Bauer; Reid B Adams; Timothy L McMurry
Journal:  Am J Surg       Date:  2020-01-20       Impact factor: 2.565

2.  Predicting morbidity of liver resection.

Authors:  Sudharsan Madhavan; Vishal G Shelat; Su-Lin Soong; Winston W L Woon; Terence Huey; Yiong H Chan; Sameer P Junnarkar
Journal:  Langenbecks Arch Surg       Date:  2018-02-07       Impact factor: 3.445

3.  Liver resections between 2014 and 2020 in the Lausanne University Hospital, Switzerland.

Authors:  Kosuke Kobayashi; Emilie Uldry; Nicolas Demartines; Nermin Halkic
Journal:  Glob Health Med       Date:  2020-10-31

4.  Correlation Between Portal Pressure and Indocyanine Green Retention Rate is Unaffected by the Cause of Cirrhosis: A Prospective Study.

Authors:  Kosuke Kobayashi; Emilie Uldry; Takashi Kokudo; Alessandra Cristaudi; Yoshikuni Kawaguchi; Chikara Shirata; Takamune Yamaguchi; Olivier Dormond; Rafael Duran; Kiyoshi Hasegawa; Nicolas Demartines; Nermin Halkic
Journal:  World J Surg       Date:  2021-04-23       Impact factor: 3.352

Review 5.  Assessment of Preoperative Liver Function for Surgical Decision Making in Patients with Hepatocellular Carcinoma.

Authors:  Takashi Kokudo; Kiyoshi Hasegawa; Chikara Shirata; Meguri Tanimoto; Takeaki Ishizawa; Junichi Kaneko; Nobuhisa Akamatsu; Junichi Arita; Nicolas Demartines; Emilie Uldry; Norihiro Kokudo; Nermin Halkic
Journal:  Liver Cancer       Date:  2019-07-26       Impact factor: 11.740

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.