Comparison of risk-scoring systems in the prediction of outcome after liver resection

Ulyett, S., Shahtahmassebi, G. ORCID: 0000-0002-0630-2750, Aroori, S., Bowles, M.J., Briggs, C.D., Wiggans, M.G., Minto, G. and Stell, D.A., 2017. Comparison of risk-scoring systems in the prediction of outcome after liver resection. Perioperative Medicine, 6 (1), p. 22. ISSN 2047-0525

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Abstract

Background:
Risk prediction techniques commonly used in liver surgery include the American Society of Anesthesiologists (ASA) grading, Charlson Comorbidity Index (CCI) and cardiopulmonary exercise tests (CPET). This study compares the utility of these techniques along with the number of segments resected as predictive tools in liver surgery.
Methods:
A review of a unit database of patients undergoing liver resection between February 2008 and January 2015 was undertaken. Patient demographics, ASA, CCI and CPET variables were recorded along with resection size. Clavien-Dindo grade III–V complications were used as a composite outcome in analyses. Association between predictive variables and outcome was assessed by univariate and multivariate techniques.
Results:
One hundred and seventy-two resections in 168 patients were identified. Grade III–V complications occurred after 42 (24.4%) liver resections. In univariate analysis of CPET variables, ventilatory equivalents for CO2 (VEqCO2) was associated with outcome. CCI score, but not ASA grade, was also associated with outcome. In multivariate analysis, the odds ratio of developing grade III–V complications for incremental increases in VEqCO2, CCI and number of liver segments resected were 1.09, 1.49 and 2.94, respectively.
Conclusions:
Of the techniques evaluated, resection size provides the simplest and most discriminating predictor of significant complications following liver surgery.

Item Type: Journal article
Publication Title: Perioperative Medicine
Creators: Ulyett, S., Shahtahmassebi, G., Aroori, S., Bowles, M.J., Briggs, C.D., Wiggans, M.G., Minto, G. and Stell, D.A.
Publisher: BioMed Central
Date: 2017
Volume: 6
Number: 1
ISSN: 2047-0525
Identifiers:
NumberType
10.1186/s13741-017-0073-4DOI
73Publisher Item Identifier
Divisions: Schools > School of Science and Technology
Record created by: Linda Sullivan
Date Added: 18 Jan 2018 12:38
Last Modified: 18 Jan 2018 12:38
URI: https://irep.ntu.ac.uk/id/eprint/32478

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