Discriminant function of perinatal risk that predicts early neonatal morbidity: its validity and reliability

Abstract

Background. This study aimed to identify significant perinatal risk factors associated with neonatal morbidity to construct a scoring system to aid in distinguishing between healthy and ill neonates. Validity and reliability of the scoring system were determined. Methods. We conducted a screening test and used logistic regression to analyze data from a cohort of 387 neonates and to determine the relationship between risk factors and morbidity. Twenty nine factors of perinatal risk were studied. Logistic regression and discriminant analysis were performed to assess risk for morbidity. This system was developed and validated prospectively on 238 new neonates. Results. Risk factors that demonstrated association with morbidity by logistic regression were chronic maternal illness, premature rupture of membranes (PROM), amniotic fluid, low Apgar score at 5 min, obstetric trauma, hypertension, neonatal resuscitation, breathing pattern at 6 h after delivery, birth weight, and gestational age. Discriminant function obtained from discriminant analysis had sensitivity of 68% and specificity of 93%, while positive and negative predictive values were 88 and 86%, respectively. Area below receiver operating characteristic (ROC) curve was 0.86 (standard error [SE]: 0.02). In the validity study, these values were maintained without significant differences. Kappa statistic between two physicians was calculated at 0.84 ( p<0.001). Conclusions. Evidence indicated that discriminant function is a useful tool to assess initial neonatal risk, allowing pediatricians to predict morbidity prior to discharge of neonates.