Intraperitoneal contamination index (Hajibandeh index) predicts nature of peritoneal contamination and risk of postoperative mortality in patients with acute abdominal pathology: a prospective multicentre cohort study

Hajibandeh, Shahab; Shah, Jigar; Hajibandeh, Shahin; Murali, Sreedutt; Stephanos, Mina; Ibrahim, Sherif; Asqalan, A; Mithany, R; Wickramasekara, Nuwan; Mansour, Moustafa

doi:10.1007/s00384-020-03822-5

Cited by 7 publications

(5 citation statements)

References 11 publications

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“…The HI used in the HAS model is a strong predictor of intraperitoneal contamination, which is already available prior to operation. 17 On the other hand, the NELA score does not take into account the frailty of the patient, 24 and we have previously shown that its predictive performance in patients aged above 80 may not be as accurate as its performance in younger patients. 9 The inclusion of sarcopenia and ASA together in the HAS model can potentially resolve this issue.…”

Section: Discussionmentioning

confidence: 99%

“…The NELA risk score requires preoperative knowledge about intraperitoneal contamination and intraoperative blood loss, which are not necessarily available until the operation is done. The HI used in the HAS model is a strong predictor of intraperitoneal contamination, which is already available prior to operation 17 . On the other hand, the NELA score does not take into account the frailty of the patient, 24 and we have previously shown that its predictive performance in patients aged above 80 may not be as accurate as its performance in younger patients 9 .…”

Section: Discussionmentioning

confidence: 99%

“…The HI was calculated using the formula shown in Supplementary File 1, Supplemental Digital Content 1, http://links.lww.com/SLA/E609. It includes preoperative levels of CRP, neutrophils, and lactate as nominators and preoperative levels of albumin and lymphocytes as denominators 9,17 …”

Section: Methodsmentioning

confidence: 99%

“…It includes preoperative levels of CRP, neutrophils, and lactate as nominators and preoperative levels of albumin and lymphocytes as denominators. 9,17…”

Section: Potential Predictors and Definitionsmentioning

confidence: 99%

“…We learned from previous studies that the modern predictors of mortality in patients undergoing EL include age over 80, 12,13 sarcopenia, 14 frailty, 15,16 American Society of Anesthesiologists (ASA) status, 12,13 need for bowel resection, 12 and presence of intraperitoneal contamination 13 . In addition to the above predictors, the Hajibandeh Index (HI), derived from combined levels of C-reactive protein (CRP), lactate, neutrophils, lymphocytes, and albumin, is a strong predictor of mortality in patients undergoing EL 9,17 . A risk prediction model derived from the above predictors may potentially be the best tool with excellent discriminative power for predicting the risk of postoperative mortality in patients undergoing EL.…”

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confidence: 99%

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

Hajibandeh

Hughes

et al. 2023

Annals of Surgery

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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.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

“…It includes preoperative levels of CRP, neutrophils, and lactate as nominators and preoperative levels of albumin and lymphocytes as denominators. 9,17…”

Section: Potential Predictors and Definitionsmentioning

confidence: 99%