• Annals of surgery · Jan 2023

    Validation of the AI-based Predictive OpTimal Trees in Emergency Surgery Risk (POTTER) Calculator in Patients 65 Years and Older.

    • Lydia R Maurer, Prahan Chetlur, Daisy Zhuo, Majed El Hechi, George C Velmahos, Jack Dunn, Dimitris Bertsimas, and KaafaraniHaytham M AHMADepartment of Surgery, Massachusetts General Hospital, Boston, Massachusetts.Division of Trauma, Emergency Surgery, and Surgical Critical Care, Massachusetts General Hospital, Boston, Massachusetts..
    • Department of Surgery, Massachusetts General Hospital, Boston, Massachusetts.
    • Ann. Surg. 2023 Jan 1; 277 (1): e8e15e8-e15.

    ObjectiveWe sought to assess the performance of the Predictive OpTimal Trees in Emergency Surgery Risk (POTTER) tool in elderly emergency surgery (ES) patients.Summary Background DataThe POTTER tool was derived using a novel Artificial Intelligence (AI)-methodology called optimal classification trees and validated for prediction of ES outcomes. POTTER outperforms all existent risk-prediction models and is available as an interactive smartphone application. Predicting outcomes in elderly patients has been historically challenging and POTTER has not yet been tested in this population.MethodsAll patients ≥65 years who underwent ES in the ACS-NSQIP 2017 database were included. POTTER's performance for 30-day mortality and 18 postoperative complications (eg, respiratory or renal failure) was assessed using c-statistic methodology, with planned sub-analyses for patients 65 to 74, 75 to 84, and 85+ years.ResultsA total of 29,366 patients were included, with mean age 77, 55.8% females, and 62% who underwent emergency general surgery. POTTER predicted mortality accurately in all patients over 65 (c-statistic 0.80). Its best performance was in patients 65 to 74 years (c-statistic 0.84), and its worst in patients ≥85 years (c-statistic 0.71). POTTER had the best discrimination for predicting septic shock (c-statistic 0.90), respiratory failure requiring mechanical ventilation for ≥48 hours (c-statistic 0.86), and acute renal failure (c-statistic 0.85).ConclusionsPOTTER is a novel, interpretable, and highly accurate predictor of in-hospital mortality in elderly ES patients up to age 85 years. POTTER could prove useful for bedside counseling and for benchmarking of ES care.Copyright © 2020 Wolters Kluwer Health, Inc. All rights reserved.

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