Infants with a predicted probability greater than 0.5, based on specific metabolic patterns at birth, had 14.4 times the odds of experiencing sudden infant death syndrome compared to those with lower-risk profiles, according to a recent study.

The case-control study analyzed data from 2,276,578 infants born in California between 2005 and 2011. Researchers examined the association between newborn metabolic markers, measured through routine newborn screening, and sudden infant death syndrome (SIDS). A total of 14 metabolic markers, along with clinical factors like prenatal care adequacy, infant sex, and maternal age, were analyzed to build a predictive model.

The study identified 354 cases of SIDS (0.016%) and matched them to 1,416 controls based on gestational age and birth weight. The average gestational age for infants in the SIDS group was 38.3 weeks, with 62.1% of cases being male.

The final model included 8 metabolic markers, such as alanine, free carnitine, and glutarylcarnitine, which are involved in key pathways like fatty acid oxidation. The area under the receiver operating characteristic curve was 0.75 in the training set and 0.70 in the test set. In the test group, 32 infants were identified with a predicted probability greater than 0.5 for SIDS, of whom 20 (62.5%) had SIDS.

The study, published in JAMA Pediatrics, suggests that metabolic profiles at birth, combined with clinical risk factors, may help identify infants at higher risk for SIDS. Researchers emphasized that while promising, further validation is needed before the model can be used in practice.

This study was supported by the California Preterm Birth Initiative and the NIH. Both Scott P. Oltman, MS, and Laura L. Jelliffe-Pawlowski, PhD, have a patent pending for a newborn metabolic vulnerability model.