Computer interpreted fetal monitoring data. Discriminant analysis or perinatal data as a model for prediction of neurologic status at one year of age.

Intrapartum fetal monitoring may be useful in discriminating short-term and long-term infant outcomes. In order to develop a model for the classification of infants for measures of outcome and to evaluate the discriminatory value of selected perinatal data, 61 data files, which included computer interpreted fetal electroencephalogram and fetal heart rate, one and five minute Apoar scores, results of neonatal neurologic examination, and results of neurologic examination at one year of age, were submitted to computerized discriminant function analysis. For the classification of infants for neurologic status at one year, using FEEG patterns alone, 64% of the 42 normal infnats and 63% of the 19 abnormal infants were correctly classified. Using intrapartum FEEG and FHR patterns simultaneously, 69% of the 42 normal infants and 63% of the 19 abnormal infants were correctly classified. Combining intrapartum data with postpartum data, including one minute and five minute Apgar scores and neonatal neurologic examinations, 81% of the 42 normal infants and 79% of the 19 abnormal infants could be correctly classified. These results suggest that brain damage may already be present before birth, during labor, and that the risk of abnormal neurologic outcome at one year can be detected for a large percentage of infants using computer interpreted monitoring data during labor.