Document Type : original article
Authors
1 School of Medicine, Arak University of Medical Sciences, Arak, Iran
2 Associate Professor of Pediatric, School of Medicine, Arak University of Medical Sciences, Arak, Iran.
3 Assistant professor of neonatal, School of Medicine, Arak University of Medical Sciences, Arak, Iran.
4 Assistant Professor of Biostatistics, School of Medicine, Arak University of Medical Sciences, Arak, Iran.
5 Bachelor of Public Health, Arak University of Medical Sciences
Abstract
Background: Survival of infants admitted to the NICU does not depend exclusively on birth weight and gestational age, but on other perinatal factors and physiological conditions of individual infants, especially the severity of their illness. Therefore, scoring systems are needed to assess the risk of adverse outcomes for each premature infant. In this study, the accuracy of Crib-II was investigated to predict the mortality of premature babies admitted to the NICU.
Materials and methods:140 babies admitted to the NICU, meeting the selection criteria (gestational age less than 32 weeks or weight less than 1500 grams) were included in the study. The required data for the Crib-II tool (gender, gestational age, birth weight, initial temperature of the baby, base excess) were collected and analyzed using SPSS software version 23.
Results: In this study,45%(63 infants) were female and55%(77 infants) were male, with a mortality rate of 30.7%. The average gestational age is 30.17±2.14 weeks, the average birth weight is 1856.52±583.18 grams, the average initial rectal temperature is 36.92±0.52 °C, the average base excess is -8.54±7.09 mmol/L, the average Crib-II score is 5.15±4.43, and the area under the rock curve with a cut point of 6.5 was 0.96. Also, the sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, and negative likelihood ratio were 96%, 93%, 98%, 95%, 97%, 46.5, 0.07, respectively.
Conclusion: Based on our observations in this study, the Crib-II index has a high value in predicting the mortality of premature babies. It was able to correctly predict 96% of the deaths of premature babies, which indicates the high value of this index.
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