ArticleJournal of minimal access surgery2024
Evaluation of ACS-NSQIP and CR-POSSUM risk calculators for the prediction of mortality after colorectal surgery: A retrospective cohort study.
Article in Journal of minimal access surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07325656 (Comparison of Scoring Systems for Predicting Morbidity and Mortality in Patients Undergoing Surgery for Gastrointestinal Malignancies), which is not on this map. Not yet cited in PubMed.
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Comparison of Scoring Systems for Predicting Morbidity and Mortality in Patients Undergoing Surgery for Gastrointestinal Malignancies
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4 authors.
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Abstract
backgroundSeveral risk calculating tools have been introduced into clinical practice to provide patients and clinicians with objective, individualised estimates of procedure-related unfavourable outcomes. The currently available risk calculators (RCs) have been developed by well-endowed health systems in Europe and the USA. Applicability of these RCs in low-middle income country (LMIC) settings with wide disparities in patient population, surgical practice and healthcare infrastructure has not been adequately examined. PATIENTS AND
methodsThrough this single tertiary care, LMIC-centre, retrospective cohort study, we investigated the accuracy of the two most widely validated RCs - American College of Surgeons-National Surgical Quality Improvement Program (ACS-NSQIP) RC and ColoRectal Physiological and Operative Severity Score for the Enumeration of Mortality and Morbidity (CR-POSSUM) - for the prediction of mortality in patients undergoing elective and emergency colorectal surgery (CRS) from March 2013 to March 2020. Online RCs were used to predict mortality and other outcomes. Accuracy was assessed by Brier score and C statistic.
resultsOf 105 patients, 69 (65.71%) underwent elective and 36 (34.28%) underwent emergency CRS. The 30-day overall mortality was 12 - elective 1 (1.4%) and emergency 11 (30.5%). ACS-NSQIP RC performed better for the prediction of overall ( C statistic 0.939, Brier score 0.065) and emergency ( C statistic 0.840, Brier score 0.152) mortality. However, for elective CRS mortality, Brier scores were similar for both models (0.014), whereas C statistic (0.934 vs. 0.890) value was better for ACS-NSQIP.
conclusionsBoth ACS-NSQIP and CR-POSSUM were accurate for the prediction of CRS mortality. However, compared to CR-POSSUM, ACS-NSQIP performed better. The overall performance of both models is indicative of their wider applicability in LMIC centres also.
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