Pre-operative risk stratification is a key part of the care pathway for emergency bowel surgery, as it facilitates the identification of high-risk patients. Several novel risk scores have recently been published that are designed to identify patients who are frail or significantly unwell. They can also be calculated pre-operatively from routinely collected clinical data. This study aimed to investigate the ability of these scores to predict 30-day mortality after emergency bowel surgery. A single centre cohort study was performed using our local data from the National Emergency Laparotomy Audit database. Further data were then extracted from electronic hospital records (n = 1508). The National Early Warning Score, Laboratory Decision Tree Early Warning Score and Hospital Frailty Risk Score were then calculated. The most abnormal National or Laboratory Decision Tree Early Warning Score in the 24 or 72 hours before surgery were used in analysis. Individual scores were reasonable predictors of mortality (c-statistic 0.699–0.740) but all poorly calibrated. A National Early Warning Score ≥ 4 was associated with a high overall mortality rate (> 10%). A logistic regression model was developed using age, National Early Warning Score, Laboratory Decision Tree Early Warning Score and Hospital Frailty Risk Score as predictor variables, and its performance compared with other established risk models. The model demonstrated good discrimination and calibration (c-statistic 0.827) but was marginally outperformed by the National Emergency Laparotomy Audit score (c-statistic 0.861). All other models compared performed less well (c-statistics 0.734–0.808). Pre-operative patient vital signs, blood tests and markers of frailty can be used to accurately predict the risk of 30-day mortality after emergency bowel surgery.
|Early online date||1 Feb 2023|
|Publication status||Early online - 1 Feb 2023|
- early warning score