Comparison between the Ability of Glasgow Coma Scale and Full Outline of Unresponsiveness Score to Predict the Mortality and Discharge Rate of Pediatric Intensive Care Unit Patients

authors:

avatar Ali Khajeh 1 , avatar Afshin Fayyazi 2 , avatar Ghasem Miri-Aliabad 3 , avatar Hasan Askari 4 , * , avatar Noormohammad Noori 5 , avatar Behrouz Khajeh 6


how to cite: Khajeh A , Fayyazi A , Miri-Aliabad G , Askari H , Noori N , et al. Comparison between the Ability of Glasgow Coma Scale and Full Outline of Unresponsiveness Score to Predict the Mortality and Discharge Rate of Pediatric Intensive Care Unit Patients. Iran J Pediatr. 2014;24(5): 603-608. 

Abstract

Objective: Prediction of survival and mortality rates in costly environments such as the intensive care unit (ICU) is of great importance for the assessment of new treatments, resource consumption control, and improvement of quality control. This study aimed to determine the ability to predict mortality and discharge rate of patients using the FOUR score in the pediatric ICU (PICU) of Ali Ibn Abitalib Hospital, Zahedan and compare the results with those of Glasgow Coma Scale (GCS). Methods: This prospective study was conducted on 200 patients admitted to the PICU. Convenience purposive sampling was used. Research data was collected using the Full Outline of Unresponsiveness  (FOUR) score and GCS using questionnaires. Obtained data was analyzed with SPSS 16 using descriptive statistics and correlation analyses. Findings: Of the 200 children admitted to the PICU, 71.5% and 28.5% were discharged and died, respectively. The inter-rater reliability for the FOUR score was good to excellent (weighted κ: eye, 0.72; respiration, 0.82; brainstem, 0.74; motor, 0.78), In terms of mortality and discharge prediction, logistic regression analyses (FOUR score = OR: 0.13; 95% CI: 0.06–0.29; P<0.001; GCS=OR: 2.49; 95% CI: 1.44–4.32; P<0.001) showed that the FOUR score is a good predictor for in-hospital mortality. Conclusion: Results indicated that the FOUR score is more capable than GCS in predicting the mortality and discharge of patients admitted to the PICU.
 

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