Routine versus difficult cholecystectomy: using predictive analytics to assess patient outcomes.
Journal
HPB : the official journal of the International Hepato Pancreato Biliary Association
ISSN: 1477-2574
Titre abrégé: HPB (Oxford)
Pays: England
ID NLM: 100900921
Informations de publication
Date de publication:
01 2019
01 2019
Historique:
received:
21
02
2018
revised:
18
06
2018
accepted:
21
06
2018
pubmed:
28
7
2018
medline:
14
4
2020
entrez:
28
7
2018
Statut:
ppublish
Résumé
The American College of Surgeons National Surgical Quality Improvement Program Patients who underwent cholecystectomy between 2008 and 2016 and were deemed too high risk for acute care general surgery (GS) and had surgery performed by the Division of Hepatopancreatobiliary Surgery (HPB) were identified. Outcomes of the HPB cholecystectomies were matched against cholecystectomies performed by GS. New predictive models for postoperative outcomes were constructed. Area under the curve was used to assess predictive accuracy for both models and internal validation was performed using bootstrap logistic regression. A total of 169/934 (18%) cholecystectomies were identified as too high risk for GS. These 169 patients were matched with 126 patients who had cholecystectomy performed by GS. For GS and HPB cholecystectomies, the proposed model demonstrated better discriminative ability compared to the SRC based on ROC curves (proposed model: 0.589-0.982; SRC: 0.570-0.836) for each of the predicted outcomes. For patients undergoing cholecystectomy, customized models are superior for predicting individual perioperative risk and allow more accurate, patient-specific delivery of care.
Sections du résumé
BACKGROUND
The American College of Surgeons National Surgical Quality Improvement Program
METHODS
Patients who underwent cholecystectomy between 2008 and 2016 and were deemed too high risk for acute care general surgery (GS) and had surgery performed by the Division of Hepatopancreatobiliary Surgery (HPB) were identified. Outcomes of the HPB cholecystectomies were matched against cholecystectomies performed by GS. New predictive models for postoperative outcomes were constructed. Area under the curve was used to assess predictive accuracy for both models and internal validation was performed using bootstrap logistic regression.
RESULTS
A total of 169/934 (18%) cholecystectomies were identified as too high risk for GS. These 169 patients were matched with 126 patients who had cholecystectomy performed by GS. For GS and HPB cholecystectomies, the proposed model demonstrated better discriminative ability compared to the SRC based on ROC curves (proposed model: 0.589-0.982; SRC: 0.570-0.836) for each of the predicted outcomes.
CONCLUSION
For patients undergoing cholecystectomy, customized models are superior for predicting individual perioperative risk and allow more accurate, patient-specific delivery of care.
Identifiants
pubmed: 30049644
pii: S1365-182X(18)32668-6
doi: 10.1016/j.hpb.2018.06.1805
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
77-86Informations de copyright
Copyright © 2018 International Hepato-Pancreato-Biliary Association Inc. Published by Elsevier Ltd. All rights reserved.