Extent of resection and underlying liver disease influence the accuracy of the preoperative risk assessment with the ACS NSQIP Risk Calculator.
Complications
Liver Surgery
Outcome Research
Postoperative outcomes
Risk Assessment
Journal
Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
ISSN: 1873-4626
Titre abrégé: J Gastrointest Surg
Pays: Netherlands
ID NLM: 9706084
Informations de publication
Date de publication:
25 Sep 2024
25 Sep 2024
Historique:
received:
29
06
2024
revised:
16
09
2024
accepted:
21
09
2024
medline:
28
9
2024
pubmed:
28
9
2024
entrez:
27
9
2024
Statut:
aheadofprint
Résumé
Depending on the extent of liver resection and the underlying liver disease, liver surgery is associated with a significant risk for postoperative complications. Therefore, adequate patient selection is crucial. The aim of this study was to assess the accuracy of the American College of Surgeons risk calculator (ACS-RC) taking into account liver parenchyma quality and type of liver resection. From 01/2019 to 03/2023 patients undergoing open or minimally invasive liver resection for benign or malignant indications at the University Hospital Basel were included. Brier score and feature importance analysis (FIA) were performed to investigate the accuracy of the ACS-RC. 376 patients were included, 214 (57%) underwent partial hepatectomy, 89 (24%) hemi-hepatectomy and 73 (19%) trisegmentectomy. Most patients had underlying liver diseases, 143 (38%) patients with fibrosis, 75 (20%) with steatosis and 61 (16%) with cirrhosis. The ACS-RC adequately predicted surgical site infection (Brier score 0.035), urinary tract infection (Brier score 0.038) and death (Brier score 0.046), moderate accuracy was achieved for serious complications (Brier score 0.216) and overall complications (Brier score 0.180). Compared to the overall cohort, the prediction was limited in patients with cirrhosis, fibrosis and steatosis as well as for patients undergoing hemi-hepatectomies and trisegmentectomies. Including liver parenchyma quality led to improved prediction accuracy. The ACS-RC is a reliable tool to estimate 30-day postoperative morbidity, especially for patients with healthy liver parenchyma undergoing partial liver resections. However, accurate perioperative risk prediction should adjust for underlying liver disease and extended liver resections.
Sections du résumé
BACKGROUND
BACKGROUND
Depending on the extent of liver resection and the underlying liver disease, liver surgery is associated with a significant risk for postoperative complications. Therefore, adequate patient selection is crucial. The aim of this study was to assess the accuracy of the American College of Surgeons risk calculator (ACS-RC) taking into account liver parenchyma quality and type of liver resection.
STUDY DESIGN
METHODS
From 01/2019 to 03/2023 patients undergoing open or minimally invasive liver resection for benign or malignant indications at the University Hospital Basel were included. Brier score and feature importance analysis (FIA) were performed to investigate the accuracy of the ACS-RC.
RESULTS
RESULTS
376 patients were included, 214 (57%) underwent partial hepatectomy, 89 (24%) hemi-hepatectomy and 73 (19%) trisegmentectomy. Most patients had underlying liver diseases, 143 (38%) patients with fibrosis, 75 (20%) with steatosis and 61 (16%) with cirrhosis. The ACS-RC adequately predicted surgical site infection (Brier score 0.035), urinary tract infection (Brier score 0.038) and death (Brier score 0.046), moderate accuracy was achieved for serious complications (Brier score 0.216) and overall complications (Brier score 0.180). Compared to the overall cohort, the prediction was limited in patients with cirrhosis, fibrosis and steatosis as well as for patients undergoing hemi-hepatectomies and trisegmentectomies. Including liver parenchyma quality led to improved prediction accuracy.
CONCLUSION
CONCLUSIONS
The ACS-RC is a reliable tool to estimate 30-day postoperative morbidity, especially for patients with healthy liver parenchyma undergoing partial liver resections. However, accurate perioperative risk prediction should adjust for underlying liver disease and extended liver resections.
Identifiants
pubmed: 39332481
pii: S1091-255X(24)00637-1
doi: 10.1016/j.gassur.2024.09.021
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.