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

被引:13
作者
Hajibandeh, Shahab [1 ]
Hajibandeh, Shahin [2 ]
Hughes, Ioan [1 ]
Mitra, Kalyan [1 ]
Saji, Alwin Puthiyakunnel [3 ]
Clayton, Amy [4 ]
Alessandri, Giorgio [1 ]
Duncan, Trish [1 ]
Cornish, Julie [1 ]
Morris, Chris [1 ]
O'Reilly, David [1 ]
Kumar, Nagappan [1 ]
机构
[1] Univ Hosp Wales, Dept Gen Surg, Cardiff, Wales
[2] Royal Stoke Univ Hosp, Dept Gen Surg, Stoke On Trent, England
[3] Cardiff Univ, Sch Med, Cardiff, Wales
[4] Univ Hosp Wales, Dept Radiol, Cardiff, Wales
关键词
laparotomy; mortality; hajibandeh index; ASA status; sarcopenia; SURGICAL RISK CALCULATOR; GENERAL-SURGERY;
D O I
10.1097/SLA.0000000000005897
中图分类号
R61 [外科手术学];
学科分类号
摘要
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.
引用
收藏
页码:501 / 509
页数:9
相关论文
共 31 条
[1]  
American Society of Anesthesiologists Committee on Economics, ASA physical status classification system
[2]   Evaluating and improving current risk prediction tools in emergency laparotomy [J].
Barazanchi, Ahmed ;
Bhat, Sameer ;
Palmer-Neels, Kate ;
Macfater, Wiremu S. ;
Xia, Weisi ;
Zeng, Irene ;
Taneja, Ashish ;
MacCormick, Andrew D. ;
Hill, Andrew G. .
JOURNAL OF TRAUMA AND ACUTE CARE SURGERY, 2020, 89 (02) :382-387
[3]   Predictive Performance of NELA Versus P- POSSUM Mortality Scores: Are We Underestimating the Risk of Mortality Following Emergency Laparotomy? [J].
Barghash, Mohammed ;
Iskandar, Amir ;
Fawzy, Sherif, I ;
Effiom, Derek ;
Huck, Claire ;
Hajibandeh, Shahin ;
Hajibandeh, Shahab ;
Mansour, Moustafa .
CUREUS JOURNAL OF MEDICAL SCIENCE, 2022, 14 (12)
[4]   Surgical Risk Is Not Linear: Derivation and Validation of a Novel, User-friendly, and Machine-learning-based Predictive OpTimal Trees in Emergency Surgery Risk (POTTER) Calculator [J].
Bertsimas, Dimitris ;
Dunn, Jack ;
Velmahos, George C. ;
Kaafarani, Haytham M. A. .
ANNALS OF SURGERY, 2018, 268 (04) :574-583
[5]   Development and Evaluation of the Universal ACS NSQIP Surgical Risk Calculator: A Decision Aid and Informed Consent Tool for Patients and Surgeons [J].
Bilimoria, Karl Y. ;
Liu, Yaoming ;
Paruch, Jennifer L. ;
Zhou, Lynn ;
Kmiecik, Thomas E. ;
Ko, Clifford Y. ;
Cohen, Mark E. .
JOURNAL OF THE AMERICAN COLLEGE OF SURGEONS, 2013, 217 (05) :833-+
[6]  
Collins GS, 2015, J CLIN EPIDEMIOL, V68, P112, DOI [10.7326/M14-0697, 10.1038/bjc.2014.639, 10.1111/eci.12376, 10.1016/j.jclinepi.2014.11.010, 10.7326/M14-0698, 10.1136/bmj.g7594, 10.1186/s12916-014-0241-z, 10.1002/bjs.9736, 10.1016/j.eururo.2014.11.025]
[7]  
data.nela, NELA Risk Calculator
[8]   COMPARING THE AREAS UNDER 2 OR MORE CORRELATED RECEIVER OPERATING CHARACTERISTIC CURVES - A NONPARAMETRIC APPROACH [J].
DELONG, ER ;
DELONG, DM ;
CLARKEPEARSON, DI .
BIOMETRICS, 1988, 44 (03) :837-845
[9]   Validation of the Artificial Intelligence-Based Predictive Optimal Trees in Emergency Surgery Risk (POTTER) Calculator in Emergency General Surgery and Emergency Laparotomy Patients [J].
El Hechi, Majed W. ;
Maurer, Lydia R. ;
Levine, Jordan ;
Zhuo, Daisy ;
El Moheb, Mohamad ;
Velmahos, George C. ;
Dunn, Jack ;
Bertsimas, Dimitris ;
Kaafarani, Haytham M. A. .
JOURNAL OF THE AMERICAN COLLEGE OF SURGEONS, 2021, 232 (06) :912-919
[10]   Hajibandeh Index versus NELA score in predicting mortality following emergency laparotomy: A retrospective Cohort Study [J].
Hajibandeh, Shahab ;
Hajibandeh, Shahin ;
Waterman, Jennifer ;
Miller, Bethany ;
Johnson, Bethan ;
Higgi, Adnan ;
Hale, Jay ;
Pearce, Dafydd ;
Evans, Louis ;
Satyadas, Thomas ;
Mansour, Moustafa ;
Havard, Tim ;
Maw, Andrew .
INTERNATIONAL JOURNAL OF SURGERY, 2022, 102