Prediction of Mortality in the Medical Intensive Care Unit with Serial Full Outline of Unresponsiveness Score in Elderly Patients.

BACKGROUND: Advanced age is one of the key risk factors for mortality and morbidity in intensive care units. The full outline of unresponsiveness (FOUR) score has been developed and introduced to address the limitations of the Glasgow Coma Scale (GCS). The current study aimed to evaluate the ability of the FOUR score in predicting the outcomes (survivors, nonsurvivors). MATERIALS AND METHODS: This observational study of 168 consecutive elderly patients admitted to medical intensive care during the 14 months carried out prospectively. FOUR score in the 24, 48, and 72 hours of admission, and demographic characteristics of all elderly patients were calculated, then recorded. The receiver operating characteristic (ROC) curve, logistic regression, and Hosmer-Lemeshow test were used (95% confidence interval) for statistical analysis. RESULTS: FOUR scores in 24, 48, and 72 hours between survivors and nonsurvivors (p <0.0001, p <0.0001, and p <0.0001, respectively) were statistically different. The discrimination power of FOUR score 24 hours of admission was excellent [area under ROC (AUC): 85.7% [standard error (SE)]: 2.8%]; it was acceptable for 48 and 72 hours of admission [AUC: 76.3% (SE: 3.6%), AUC: 75/0% (SE: 3.8%), respectively]. The FOUR score of 24 and 48 hours (x2 = 10.06, p = 0.261, x2 = 6.82, p = 0.448, respectively) showed acceptable calibration. CONCLUSIONS: The FOUR score is a suitable scoring system for prognostication of outcomes in critically ill elderly patients. The FOUR score 24 hours of admission was superior in terms of discrimination power than 48 and 72 hours, but better calibration power belonged to FOUR score 48 hours. HOW TO CITE THIS ARTICLE: Ramazani J, Hosseini M. Prediction of Mortality in the Medical Intensive Care Unit with Serial Full Outline of Unresponsiveness Score in Elderly Patients. Indian J Crit Care Med 2022;26(1):94-99.

Prediction of ICU mortality in critically ill children : Comparison of SOFA, GCS, and FOUR score.

INTRODUCTION: The SOFA (Sequential Organ Failure Assessment), GCS (Glasgow Coma Scale), and FOUR (Full Outline of UnResponsiveness) scores are the most commonly used scoring systems to predict the risk of mortality and morbidity in intensive care units (ICUs). The aim of the current study was to compare the predictive ability of these three models for predicting medical/surgical ICU mortality in critically ill children. METHODS: In the current observational and prospective study, a total of 90 consecutive patients, age ≤18 years, admitted to medical and surgical ICUs, were enrolled. The SOFA, GCS, FOUR score and demographic characteristics of all children were recorded on the first day of admission. For statistical analyses, a receiver operator characteristic (ROC) curve, the Hosmer-Lemeshow goodness of fit test, and logistic regression were used (95% confidence interval). RESULTS: The SOFA, GCS, and FOUR scores between survivors and nonsurvivors were statistically different (p = 0.002, p < 0.001, p = 0.004, respectively). The discrimination power for SOFA, GCS, and FOUR score was moderate (area under ROC [AUC] curve: 75.1%; standard error [SE]: 6.0%, 72.9% [SE: 7.2%], 78.7% [SE: 6.6%], respectively). The only well-calibrated model was GCS (x2 = 2.76, p = 0.59). CONCLUSIONS: The performance of the three predictive models SOFA, GCS, and FOUR score for predicting outcomes in children admitted to medical and surgical ICUs was good. The discrimination was moderate for all three models, and calibration was good just for GCS. GCS was superior in predicting outcome in critically ill children; however, further studies are needed to validate these scores in the pediatric population.

Comparison of full outline of unresponsiveness score and Glasgow Coma Scale in Medical Intensive Care Unit.

Context: The Glasgow Coma Scale (GCS) is the most commonly used scale, and Full Outline of Unresponsiveness (FOUR) score is new validated coma scale as an alternative to GCS in the evaluation of the level of consciousness. Aim: The aim of the current study was to evaluate FOUR score and GCS ability in predicting the outcomes (Survivors, nonsurvivors) in Medical Intensive Care Unit (MICU). Setting and Design: This was an observational and prospective study of 300 consecutive patients admitted to the MICU during a 14 months' period. Materials and Methods: FOUR score, GCS score, and demographic characteristics of all patients were recorded in the first admission 24 h. Statistical Analysis Used: A receiver operator characteristic (ROC) curve, Hosmer-Lemeshow test, and Logistic regression were used in the statistical analysis (95% confidence interval). Results: Data analysis showed a significant statistical difference in FOUR score and GCS score between survivors and nonsurvivors (P < 0.0001, P < 0.0001; respectively). The discrimination power was good for both FOUR score and GCS (area under ROC curve: 87.3% (standard error [SE]: 2.1%), 82.6% [SE: 2.3%]; respectively). The acceptable calibration was seen just for FOUR score (χ2 = 8.059, P = 0.428). Conclusions: Both FOUR score and GCS are valuable scales for predicting outcomes in patients are admitted to the MICU; however, the FOUR score showed better discrimination and calibration than GCS, so it is superior to GCS in predicting outcomes in this patients population.

Comparison of acute physiology and chronic health evaluation II and Glasgow Coma Score in predicting the outcomes of Post Anesthesia Care Unit's patients.

CONTEXT: Acute physiology and chronic health evaluation II (APACHE II) is one of the most general classification systems of disease severity in Intensive Care Units and Glasgow Coma Score (GCS) is one of the most specific ones. AIMS: The aim of the current study was to assess APACHE II and GCS ability in predicting the outcomes (survivors, non-survivors) in the Post Anesthesia Care Unit's (PACU). SETTINGS AND DESIGN: This was an observational and prospective study of 150 consecutive patients admitted in the PACU during 6-month period. MATERIALS AND METHODS: Demographic information recorded on a checklist, also information about severity of disease calculated based on APACHE II scoring system in the first admission 24 h and GCS scale. STATISTICAL ANALYSIS USED: Logistic regression, Hosmer-Lemeshow test and receiver operator characteristic (ROC) curves were used in statistical analysis (95% confidence interval). RESULTS: Data analysis showed a significant statistical difference between outcomes and both APACHE II and Glasgow Coma Score (GCS) (P < 0.0001). The ROC-curve analysis suggested that the predictive ability of GCS is slightly better than APACHE II in this study. For GCS the area under the ROC curve was 86.1% (standard error [SE]: 3.8%), and for APACHE II it was 85.7% (SE: 3.5%), also the Hosmer-Lemeshow statistic revealed better calibration for GCS (χ(2) = 5.177, P = 0.521), than APACHE II (χ(2) = 10.203, P = 0.251). CONCLUSIONS: The survivors had significantly lower APACHE II and higher GCS compared with non-survivors, also GCS showed more predictive accuracy than APACHE II in prognosticating the outcomes in PACU.