Spyridon Fortis1, Amy M J O'Shea2, Brice F Beck3, Rajeshwari Nair4, Michihiko Goto5, Peter J Kaboli2, Eli N Perencevich5, Heather S Reisinger2, Mary V Sarrazin2. 1. Center for Comprehensive Access & Delivery Research & Evaluation (CADRE), Iowa City VA Health Care System, Iowa City, IA, USA; Department of Internal Medicine, Division of Pulmonary, Critical Care and Occupation Medicine, University of Iowa Roy J. and Lucille A. Carver College of Medicine, Iowa City, IA, USA. Electronic address: spyridon-fortis@uiowa.edu. 2. Center for Comprehensive Access & Delivery Research & Evaluation (CADRE), Iowa City VA Health Care System, Iowa City, IA, USA; Department of Internal Medicine, Division of General Internal Medicine, University of Iowa Roy J. and Lucille A. Carver College of Medicine, Iowa City, IA, USA. 3. Center for Comprehensive Access & Delivery Research & Evaluation (CADRE), Iowa City VA Health Care System, Iowa City, IA, USA. 4. Center for Comprehensive Access & Delivery Research & Evaluation (CADRE), Iowa City VA Health Care System, Iowa City, IA, USA; Department of Internal Medicine, Division of General Internal Medicine, University of Iowa Roy J. and Lucille A. Carver College of Medicine, Iowa City, IA, USA; Department of Epidemiology, University of Iowa College of Public Health, Iowa City, IA, USA. 5. Center for Comprehensive Access & Delivery Research & Evaluation (CADRE), Iowa City VA Health Care System, Iowa City, IA, USA; Department of Internal Medicine, Division of Infectious Diseases, University of Iowa Roy J. and Lucille A. Carver College of Medicine, Iowa City, IA, USA.
Abstract
PURPOSE: To evaluate the performance of an automated computerized ICU severity scoring derived from the APACHE III. MATERIALS AND METHODS: Within a retrospective cohort of patients admitted to Veterans Health Administration ICUs between 2009 and 2015, we created an automated illness severity score(modified APACHE or mAPACHE), that we extracted from the electronic health records, using the same scoring as the APACHE III excluding the Glasgow Coma Scale, urine output, arterial blood gas components of APACHE III. We assessed the mAPACHE discrimination by using the area under the curve(AUC), and calibration by using the Hosmer-Lemeshow test and calculating the difference between observed and expected mortality across equal-sized risk deciles for death. RESULTS: The ICU and 30-day mortality was 5.07% of 7.82%, respectively (n = 490,955 patients). The AUC of mAPACHE for ICU and 30-day mortality was 0.771 and 0.786, respectively. The Hosmer-Lemeshow test was significant for both ICU and 30-day mortality (p < .001). The absolute difference between observed and expected mortality did not exceed ±1.53% across equal-sized deciles of risk for death. The AUC for ICU mortality was >0.7 in all admission diagnosis categories except in endocrine, respiratory, and sepsis. The AUC for 30-day mortality was >0.7 in every category. CONCLUSION: mAPACHE has adequate performance to predict mortality.
PURPOSE: To evaluate the performance of an automated computerized ICU severity scoring derived from the APACHE III. MATERIALS AND METHODS: Within a retrospective cohort of patients admitted to Veterans Health Administration ICUs between 2009 and 2015, we created an automated illness severity score(modified APACHE or mAPACHE), that we extracted from the electronic health records, using the same scoring as the APACHE III excluding the Glasgow Coma Scale, urine output, arterial blood gas components of APACHE III. We assessed the mAPACHE discrimination by using the area under the curve(AUC), and calibration by using the Hosmer-Lemeshow test and calculating the difference between observed and expected mortality across equal-sized risk deciles for death. RESULTS: The ICU and 30-day mortality was 5.07% of 7.82%, respectively (n = 490,955 patients). The AUC of mAPACHE for ICU and 30-day mortality was 0.771 and 0.786, respectively. The Hosmer-Lemeshow test was significant for both ICU and 30-day mortality (p < .001). The absolute difference between observed and expected mortality did not exceed ±1.53% across equal-sized deciles of risk for death. The AUC for ICU mortality was >0.7 in all admission diagnosis categories except in endocrine, respiratory, and sepsis. The AUC for 30-day mortality was >0.7 in every category. CONCLUSION: mAPACHE has adequate performance to predict mortality.
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Authors: Amol A Verma; Tejasvi Hora; Hae Young Jung; Michael Fralick; Sarah L Malecki; Lauren Lapointe-Shaw; Adina Weinerman; Terence Tang; Janice L Kwan; Jessica J Liu; Shail Rawal; Timothy C Y Chan; Angela M Cheung; Laura C Rosella; Marzyeh Ghassemi; Margaret Herridge; Muhammad Mamdani; Fahad Razak Journal: CMAJ Date: 2021-02-10 Impact factor: 8.262
Authors: Amol A Verma; Tejasvi Hora; Hae Young Jung; Michael Fralick; Sarah L Malecki; Lauren Lapointe-Shaw; Adina Weinerman; Terence Tang; Janice L Kwan; Jessica J Liu; Shail Rawal; Timothy C Y Chan; Angela M Cheung; Laura C Rosella; Marzyeh Ghassemi; Margaret Herridge; Muhammad Mamdani; Fahad Razak Journal: CMAJ Date: 2021-06-07 Impact factor: 8.262