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Abstract
ANALYSIS OF FOUR SCORE AND GCS SCORE ACCURACY IN PREDICTING THE FIRST SEVEN-DAY MORTALITY ON ADULT PATIENTS WITH HEAD INJURY IN dr. SAIFUL ANWAR GENERAL HOSPITAL, MALANG
Puguh Santoso*, Titin Andri Wihastuti, and Tina Handayani Nasution
ABSTRACT
Background: Head injury is one of the most common causes of death recorded in intra hospitals. Head injuries can cause death, disability, reducing a person's productivity. Moreover, it involves the productive age group and becomes big socio-economic burdens. Purpose: To analyze the FOUR score and GCS score as mortality predictors of the first 7-days of adult patients at Regional General Hospital of Dr. Saiful Anwar, Malang. Method: This research is an analytic observational research using cross sectional approach. The population in this study is all adult patients with head injuries who came to Saiful Anwar’s Emergency Room (IGD). Sample selection uses purposive sampling with the number of sample accounted as many as 75 respondents. Univariate analysis is used to determine the description of each variable, and testing coefficient of contingency is employed to determine the relation between variables. To know difference of effectiveness of GCS score and FOUR score in detecting the mortality of head injured patients, the analysis by ROC (Receiver Operator Characteristic) comparative method is then utilized to obtain the AUC (Area Under Curve) value determining cut-off point, sensitivity, and specificity on each GCS Score and FOUR Score. Result: The result of bivariate test identifies the relationship between GCS variable and mortality occurrence of p = (0.000) with r = 0.536. The relationship between the FOUR Score variable and the mortality event was p = 0.000 with r = 0.649. The AUC score of the GCS Score is 0.683 (IK95% 0.541 ? 0.825). Furthermore, the AUC value of the FOUR score is 0.785 (IK95% 0.639 -0.932). Conclusion: FOUR Score and GCS score can be predictors of mortality in adult patients with head injury after seven days, which statistically FOUR Score is better in predicting mortality event.
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