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Development of the Combined Assessment of Risk Encountered in Surgery (CARES) surgical risk calculator for prediction of postsurgical mortality and need for intensive care unit admission risk: a single-center retrospective study

INTRODUCTION: Accurate surgical risk prediction is paramount in clinical shared decision making. Existing risk calculators have limited value in local practice due to lack of validation, complexities and inclusion of non-routine variables. OBJECTIVE: We aim to develop a simple, locally derived and v...

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Autores principales: Chan, Diana Xin Hui, Sim, Yilin Eileen, Chan, Yiong Huak, Poopalalingam, Ruban, Abdullah, Hairil Rizal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5875658/
https://www.ncbi.nlm.nih.gov/pubmed/29574442
http://dx.doi.org/10.1136/bmjopen-2017-019427
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author Chan, Diana Xin Hui
Sim, Yilin Eileen
Chan, Yiong Huak
Poopalalingam, Ruban
Abdullah, Hairil Rizal
author_facet Chan, Diana Xin Hui
Sim, Yilin Eileen
Chan, Yiong Huak
Poopalalingam, Ruban
Abdullah, Hairil Rizal
author_sort Chan, Diana Xin Hui
collection PubMed
description INTRODUCTION: Accurate surgical risk prediction is paramount in clinical shared decision making. Existing risk calculators have limited value in local practice due to lack of validation, complexities and inclusion of non-routine variables. OBJECTIVE: We aim to develop a simple, locally derived and validated surgical risk calculator predicting 30-day postsurgical mortality and need for intensive care unit (ICU) stay (>24 hours) based on routinely collected preoperative variables. We postulate that accuracy of a clinical history-based scoring tool could be improved by including readily available investigations, such as haemoglobin level and red cell distribution width. METHODOLOGY: Electronic medical records of 90 785 patients, who underwent non-cardiac and non-neuro surgery between 1 January 2012 and 31 October 2016 in Singapore General Hospital, were retrospectively analysed. Patient demographics, comorbidities, laboratory results, surgical priority and surgical risk were collected. Outcome measures were death within 30 days after surgery and ICU admission. After excluding patients with missing data, the final data set consisted of 79 914 cases, which was divided randomly into derivation (70%) and validation cohort (30%). Multivariable logistic regression analysis was used to construct a single model predicting both outcomes using Odds Ratio (OR) of the risk variables. The ORs were then assigned ranks, which were subsequently used to construct the calculator. RESULTS: Observed mortality was 0.6%. The Combined Assessment of Risk Encountered in Surgery (CARES) surgical risk calculator, consisting of nine variables, was constructed. The area under the receiver operating curve (AUROC) in the derivation and validation cohorts for mortality were 0.934 (0.917–0.950) and 0.934 (0.912–0.956), respectively, while the AUROC for ICU admission was 0.863 (0.848–0.878) and 0.837 (0.808–0.868), respectively. CARES also performed better than the American Society of Anaesthesiologists-Physical Status classification in terms of AUROC comparison. CONCLUSION: The development of the CARES surgical risk calculator allows for a simplified yet accurate prediction of both postoperative mortality and need for ICU admission after surgery.
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spelling pubmed-58756582018-04-02 Development of the Combined Assessment of Risk Encountered in Surgery (CARES) surgical risk calculator for prediction of postsurgical mortality and need for intensive care unit admission risk: a single-center retrospective study Chan, Diana Xin Hui Sim, Yilin Eileen Chan, Yiong Huak Poopalalingam, Ruban Abdullah, Hairil Rizal BMJ Open Health Services Research INTRODUCTION: Accurate surgical risk prediction is paramount in clinical shared decision making. Existing risk calculators have limited value in local practice due to lack of validation, complexities and inclusion of non-routine variables. OBJECTIVE: We aim to develop a simple, locally derived and validated surgical risk calculator predicting 30-day postsurgical mortality and need for intensive care unit (ICU) stay (>24 hours) based on routinely collected preoperative variables. We postulate that accuracy of a clinical history-based scoring tool could be improved by including readily available investigations, such as haemoglobin level and red cell distribution width. METHODOLOGY: Electronic medical records of 90 785 patients, who underwent non-cardiac and non-neuro surgery between 1 January 2012 and 31 October 2016 in Singapore General Hospital, were retrospectively analysed. Patient demographics, comorbidities, laboratory results, surgical priority and surgical risk were collected. Outcome measures were death within 30 days after surgery and ICU admission. After excluding patients with missing data, the final data set consisted of 79 914 cases, which was divided randomly into derivation (70%) and validation cohort (30%). Multivariable logistic regression analysis was used to construct a single model predicting both outcomes using Odds Ratio (OR) of the risk variables. The ORs were then assigned ranks, which were subsequently used to construct the calculator. RESULTS: Observed mortality was 0.6%. The Combined Assessment of Risk Encountered in Surgery (CARES) surgical risk calculator, consisting of nine variables, was constructed. The area under the receiver operating curve (AUROC) in the derivation and validation cohorts for mortality were 0.934 (0.917–0.950) and 0.934 (0.912–0.956), respectively, while the AUROC for ICU admission was 0.863 (0.848–0.878) and 0.837 (0.808–0.868), respectively. CARES also performed better than the American Society of Anaesthesiologists-Physical Status classification in terms of AUROC comparison. CONCLUSION: The development of the CARES surgical risk calculator allows for a simplified yet accurate prediction of both postoperative mortality and need for ICU admission after surgery. BMJ Publishing Group 2018-03-23 /pmc/articles/PMC5875658/ /pubmed/29574442 http://dx.doi.org/10.1136/bmjopen-2017-019427 Text en © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted. This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
spellingShingle Health Services Research
Chan, Diana Xin Hui
Sim, Yilin Eileen
Chan, Yiong Huak
Poopalalingam, Ruban
Abdullah, Hairil Rizal
Development of the Combined Assessment of Risk Encountered in Surgery (CARES) surgical risk calculator for prediction of postsurgical mortality and need for intensive care unit admission risk: a single-center retrospective study
title Development of the Combined Assessment of Risk Encountered in Surgery (CARES) surgical risk calculator for prediction of postsurgical mortality and need for intensive care unit admission risk: a single-center retrospective study
title_full Development of the Combined Assessment of Risk Encountered in Surgery (CARES) surgical risk calculator for prediction of postsurgical mortality and need for intensive care unit admission risk: a single-center retrospective study
title_fullStr Development of the Combined Assessment of Risk Encountered in Surgery (CARES) surgical risk calculator for prediction of postsurgical mortality and need for intensive care unit admission risk: a single-center retrospective study
title_full_unstemmed Development of the Combined Assessment of Risk Encountered in Surgery (CARES) surgical risk calculator for prediction of postsurgical mortality and need for intensive care unit admission risk: a single-center retrospective study
title_short Development of the Combined Assessment of Risk Encountered in Surgery (CARES) surgical risk calculator for prediction of postsurgical mortality and need for intensive care unit admission risk: a single-center retrospective study
title_sort development of the combined assessment of risk encountered in surgery (cares) surgical risk calculator for prediction of postsurgical mortality and need for intensive care unit admission risk: a single-center retrospective study
topic Health Services Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5875658/
https://www.ncbi.nlm.nih.gov/pubmed/29574442
http://dx.doi.org/10.1136/bmjopen-2017-019427
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