Development and Validation of HAS (Hajibandeh Index, ASA Status, Sarcopenia) - A Novel Model for Predicting Mortality After Emergency Laparotomy

Author:

Hajibandeh Shahab1ORCID,Hajibandeh Shahin2ORCID,Hughes Ioan1,Mitra Kalyan1,Puthiyakunnel Saji Alwin3,Clayton Amy4,Alessandri Giorgio1,Duncan Trish1,Cornish Julie1,Morris Chris1,O’Reilly David1,Kumar Nagappan1

Affiliation:

1. Department of General Surgery, University Hospital of Wales, Cardiff, UK

2. Department of General Surgery, Royal Stoke University Hospital, Stoke-on-Trent, UK

3. School of Medicine, Cardiff University, Cardiff, UK

4. Department of Radiology, University Hospital of Wales, Cardiff, UK

Abstract

Objectives: To develop and validate a predictive model to predict the risk of postoperative mortality after emergency laparotomy taking into account the following variables: age, age ≥ 80, ASA status, clinical frailty score, sarcopenia, Hajibandeh Index (HI), bowel resection, and intraperitoneal contamination. Summary Background Data: The discriminative powers of the currently available predictive tools range between adequate and strong; none has demonstrated excellent discrimination yet. Methods: The TRIPOD and STROCSS statement standards were followed to protocol and conduct a retrospective cohort study of adult patients who underwent emergency laparotomy due to non-traumatic acute abdominal pathology between 2017 and 2022. Multivariable binary logistic regression analysis was used to develop and validate the model via two protocols (Protocol A and B). The model performance was evaluated in terms of discrimination (ROC curve analysis), calibration (calibration diagram and Hosmer-Lemeshow test), and classification (classification table). Results: One thousand forty-three patients were included (statistical power = 94%). Multivariable analysis kept HI (Protocol-A: P=0.0004; Protocol-B: P=0.0017), ASA status (Protocol-A: P=0.0068; Protocol-B: P=0.0007), and sarcopenia (Protocol-A: P<0.0001; Protocol-B: P<0.0001) as final predictors of 30-day postoperative mortality in both protocols; hence the model was called HAS (HI, ASA status, sarcopenia). The HAS demonstrated excellent discrimination (AUC: 0.96, P<0.0001), excellent calibration (P<0.0001), and excellent classification (95%) via both protocols. Conclusions: The HAS is the first model demonstrating excellent discrimination, calibration, and classification in predicting the risk of 30-day mortality following emergency laparotomy. The HAS model seems promising and is worth attention for external validation using the calculator provided. HAS mortality risk calculator https://app.airrange.io/#/element/xr3b_E6yLor9R2c8KXViSAeOSK.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Surgery

Reference29 articles.

1. Mannheim peritonitis index – prediction of risk of death from peritonitis: construction of a statistical and validation of an empirically based index;Wacha;Theoretical Surg,1987

2. Development and evaluation of the universal ACS NSQIP surgical risk calculator: a decision aid and informed consent tool for patients and surgeons;Bilimoria;J Am Coll Surg,2013

3. POSSUM and Portsmouth POSSUM for predicting mortality. Physiological and operative severity score for the enUmeration of mortality and morbidity;Prytherch;Br J Surg,1998

4. Mortality risk scoring in emergency general surgery: are we using the best tool?;Thahir;J Perioper Pract,2021

5. Predictive performance of NELA versus P-POSSUM mortality scores: are we underestimating the risk of mortality following emergency laparotomy?;Barghash;Cureus,2022

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3