Theerapon Sukmark1, Nuttha Lumlertgul2, Kearkiat Praditpornsilpa3, Kriang Tungsanga3, Somchai Eiam-Ong3, Nattachai Srisawat4. 1. Thungsong Hospital, Nakhon Si Thammarat, Thailand. 2. Division of Nephrology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, King Chulalongkorn Memorial Hospital, Bangkok, Thailand; Excellence Center for Critical Care Nephrology, King Chulalongkorn Memorial Hospital, Bangkok, Thailand; Research Unit in Critical Care Nephrology, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand. 3. Division of Nephrology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, King Chulalongkorn Memorial Hospital, Bangkok, Thailand. 4. Division of Nephrology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, King Chulalongkorn Memorial Hospital, Bangkok, Thailand; Excellence Center for Critical Care Nephrology, King Chulalongkorn Memorial Hospital, Bangkok, Thailand; Research Unit in Critical Care Nephrology, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand; Academic of Science, Royal Society of Thailand, Bangkok, Thailand; Tropical Medicine Cluster, Chulalongkorn University, Bangkok, Thailand; Center for Critical Care Nephrology, The CRISMA Center, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, United States. Electronic address: drnattachai@yahoo.com.
Abstract
PURPOSE: To create a simplified ICU scoring system to predict mortality in critically ill patients that can be feasibly applied in resource limited setting with good performance of predicting hospital mortality. MATERIALS AND METHODS: A retrospective study from prospective cohort was created consisting of adult patients who were admitted to an ICU of 17 centers across Thailand from 2013 to 2015. A development cohort (n = 3503) and a validation cohort (n = 1909) were randomly selected from the available enrollment data. RESULTS: In the development cohort, the predictors of the simplified score 6 variable model were low Glasgow coma score (GCS), low mean arterial pressure or need vasopressor, positive net-fluid balance, tachypnea, thrombocytopenia, and high blood urea nitrogen. In the validation study of THAI-ICU, AUC (95%CI) was 0.81(0.78-0.83). At the optimum cutoff value of 9; the sensitivity, specificity, positive likelihood ratio were 72%, 73%, and 2.72 respectively. The Hosmer-Lemeshow - C statistic was 13.5 (p = .2) and the Brier score 95% CI was 0.16 (0.15, 0.17). CONCLUSIONS: The THAI-ICU score is a new simplified severity score for predicting hospital mortality. The simplicity of the score will increase the possibility to apply in resource limited settings.
PURPOSE: To create a simplified ICU scoring system to predict mortality in critically illpatients that can be feasibly applied in resource limited setting with good performance of predicting hospital mortality. MATERIALS AND METHODS: A retrospective study from prospective cohort was created consisting of adult patients who were admitted to an ICU of 17 centers across Thailand from 2013 to 2015. A development cohort (n = 3503) and a validation cohort (n = 1909) were randomly selected from the available enrollment data. RESULTS: In the development cohort, the predictors of the simplified score 6 variable model were low Glasgow coma score (GCS), low mean arterial pressure or need vasopressor, positive net-fluid balance, tachypnea, thrombocytopenia, and high blood ureanitrogen. In the validation study of THAI-ICU, AUC (95%CI) was 0.81(0.78-0.83). At the optimum cutoff value of 9; the sensitivity, specificity, positive likelihood ratio were 72%, 73%, and 2.72 respectively. The Hosmer-Lemeshow - C statistic was 13.5 (p = .2) and the Brier score 95% CI was 0.16 (0.15, 0.17). CONCLUSIONS: The THAI-ICU score is a new simplified severity score for predicting hospital mortality. The simplicity of the score will increase the possibility to apply in resource limited settings.
Authors: Brian J Douthit; Rachel L Walden; Kenrick Cato; Cynthia P Coviak; Christopher Cruz; Fabio D'Agostino; Thompson Forbes; Grace Gao; Theresa A Kapetanovic; Mikyoung A Lee; Lisiane Pruinelli; Mary A Schultz; Ann Wieben; Alvin D Jeffery Journal: Appl Clin Inform Date: 2022-02-09 Impact factor: 2.342