Alexander R Darbyshire1, Ina Kostakis2, Philip H Pucher3, David Prytherch2, Stuart J Mercer3. 1. Department of General Surgery, Portsmouth Hospitals University NHS Trust, Southwick Hill Road, Portsmouth, PO6 3LY, UK. alexander.darbyshire@nhs.net. 2. Centre for Healthcare Modelling and Informatics, University of Portsmouth, Buckingham Building, Lion Terrace, Portsmouth, PO1 3HE, UK. 3. Department of General Surgery, Portsmouth Hospitals University NHS Trust, Southwick Hill Road, Portsmouth, PO6 3LY, UK.
Abstract
BACKGROUND: Risk stratification has become a key part of the care processes for patients having emergency bowel surgery. This study aimed to determine if operative approach influences risk-model performance, and risk-adjusted mortality rates in the United Kingdom. METHODS: A prospectively planned analysis was conducted using National Emergency Laparotomy Audit (NELA) data from December 2013 to November 2018. The risk-models investigated were P-POSSUM and the NELA Score, with model performance assessed in terms of discrimination and calibration. Risk-adjusted mortality was assessed using Standardised Mortality Ratios (SMR). Analysis was performed for the total cohort, and cases performed open, laparoscopically and converted to open. Sub-analysis was performed for cases with ≤ 20% predicted mortality. RESULTS: Data were available for 116 396 patients with P-POSSUM predicted mortality, and 46 935 patients with the NELA score. Both models displayed excellent discrimination with little variation between operative approaches (c-statistic: P-POSSUM 0.801-0.836; NELA Score 0.811-0.862). The NELA score was well calibrated across all deciles of risk, but P-POSSUM over-predicted risk beyond 20% mortality. Calibration plots for operative approach demonstrated that both models increasingly over-predicted mortality for laparoscopy, relative to open and converted to open surgery. SMRs calculated using both models consistently demonstrated that risk-adjusted mortality with laparoscopy was a third lower than open surgery. CONCLUSION: Risk-adjusted mortality for emergency bowel surgery is lower for laparoscopy than open surgery, with P-POSSUM and NELA score both over-predicting mortality for laparoscopy. Operative approach should be considered in the development of future risk-models that rely on operative data.
BACKGROUND: Risk stratification has become a key part of the care processes for patients having emergency bowel surgery. This study aimed to determine if operative approach influences risk-model performance, and risk-adjusted mortality rates in the United Kingdom. METHODS: A prospectively planned analysis was conducted using National Emergency Laparotomy Audit (NELA) data from December 2013 to November 2018. The risk-models investigated were P-POSSUM and the NELA Score, with model performance assessed in terms of discrimination and calibration. Risk-adjusted mortality was assessed using Standardised Mortality Ratios (SMR). Analysis was performed for the total cohort, and cases performed open, laparoscopically and converted to open. Sub-analysis was performed for cases with ≤ 20% predicted mortality. RESULTS: Data were available for 116 396 patients with P-POSSUM predicted mortality, and 46 935 patients with the NELA score. Both models displayed excellent discrimination with little variation between operative approaches (c-statistic: P-POSSUM 0.801-0.836; NELA Score 0.811-0.862). The NELA score was well calibrated across all deciles of risk, but P-POSSUM over-predicted risk beyond 20% mortality. Calibration plots for operative approach demonstrated that both models increasingly over-predicted mortality for laparoscopy, relative to open and converted to open surgery. SMRs calculated using both models consistently demonstrated that risk-adjusted mortality with laparoscopy was a third lower than open surgery. CONCLUSION: Risk-adjusted mortality for emergency bowel surgery is lower for laparoscopy than open surgery, with P-POSSUM and NELA score both over-predicting mortality for laparoscopy. Operative approach should be considered in the development of future risk-models that rely on operative data.