Dunja Kokotovic1, Thea Helene Degett2,3, Sarah Ekeloef2, Jakob Burcharth2. 1. Department of Gastrointestinal Surgery, Copenhagen University Hospital-Herlev and Gentofte, Copenhagen, Denmark. dunja.kokotovic@hotmail.com. 2. Department of Surgery, Zealand University Hospital, Køge, Denmark. 3. Survivorship and Inequality in Cancer, Danish Cancer Society Research Center, Copenhagen, Denmark.
Abstract
PURPOSE: Postoperative pulmonary complications (PPCs) occur in up to 30% of patients undergoing surgery and are a significant contributor to the overall risk of surgery. A preoperative risk prediction tool for postoperative pulmonary complications could succour clinical identification of patients at increased risk and support clinical decision making. This original study aimed to externally validate a risk model for predicting postoperative pulmonary complications (ARISCAT) in a cohort of patients undergoing major emergency abdominal surgery at a Danish University Hospital. METHODS: ARISCAT was validated prospectively in a cohort of patients undergoing major emergency abdominal surgery between March 2017 and January 2019. Predicted PPCs by ARISCAT were compared with observed PPCs. ARISCAT was validated with calibration, discrimination and accuracy and in adherence to the TRIPOD statement. RESULTS: The study included a total of 585 patients with a median age of 70 years. The majority of patients underwent emergency laparotomy without bowel resection. The predicted PPC frequency by ARISCAT was 24.9%, while the observed frequency of PPCs in the cohort was 36.1%. The slope of the calibration plot was 0.9546, the y axis interception was 0.1269 and the plot was well fitted to a linear slope. The Hosmer Lemeshow goodness-of-fit analysis showed good calibration (p > 0.25). ARISCAT showed good discrimination with AUC 0.83 (95% CI 0.79-0.86) on a receiver-operating characteristics curve and the accuracy was also good with a Brier score of 0.19. CONCLUSIONS: ARISCAT was a promising tool to predict PPCs in a high-risk surgical population undergoing major emergency abdominal surgery.
PURPOSE: Postoperative pulmonary complications (PPCs) occur in up to 30% of patients undergoing surgery and are a significant contributor to the overall risk of surgery. A preoperative risk prediction tool for postoperative pulmonary complications could succour clinical identification of patients at increased risk and support clinical decision making. This original study aimed to externally validate a risk model for predicting postoperative pulmonary complications (ARISCAT) in a cohort of patients undergoing major emergency abdominal surgery at a Danish University Hospital. METHODS: ARISCAT was validated prospectively in a cohort of patients undergoing major emergency abdominal surgery between March 2017 and January 2019. Predicted PPCs by ARISCAT were compared with observed PPCs. ARISCAT was validated with calibration, discrimination and accuracy and in adherence to the TRIPOD statement. RESULTS: The study included a total of 585 patients with a median age of 70 years. The majority of patients underwent emergency laparotomy without bowel resection. The predicted PPC frequency by ARISCAT was 24.9%, while the observed frequency of PPCs in the cohort was 36.1%. The slope of the calibration plot was 0.9546, the y axis interception was 0.1269 and the plot was well fitted to a linear slope. The Hosmer Lemeshow goodness-of-fit analysis showed good calibration (p > 0.25). ARISCAT showed good discrimination with AUC 0.83 (95% CI 0.79-0.86) on a receiver-operating characteristics curve and the accuracy was also good with a Brier score of 0.19. CONCLUSIONS: ARISCAT was a promising tool to predict PPCs in a high-risk surgical population undergoing major emergency abdominal surgery.
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