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Early Newborn Metabolic Patterning and Sudden Infant Death Syndrome

医学 婴儿猝死综合征 胎龄 儿科 人口 新生儿筛查 队列 逻辑回归 队列研究 出生体重 内科学 怀孕 环境卫生 遗传学 生物
作者
Scott P. Oltman,Elizabeth E. Rogers,Rebecca J. Baer,Ribka Amsalu,Gretchen Bandoli,Christina Chambers,Hyunkeun Cho,John M. Dagle,Kayla L. Karvonen,Stephen F. Kingsmore,Safyer McKenzie‐Sampson,Allison M. Momany,Eric S. Ontiveros,Liana Protopsaltis,Larry Rand,Erica Sanford Kobayashi,Martina A. Steurer,Kelli K. Ryckman,Laura L. Jelliffe‐Pawlowski
出处
期刊:JAMA Pediatrics [American Medical Association]
被引量:2
标识
DOI:10.1001/jamapediatrics.2024.3033
摘要

Importance Sudden infant death syndrome (SIDS) is a major cause of infant death in the US. Previous research suggests that inborn errors of metabolism may contribute to SIDS, yet the relationship between SIDS and biomarkers of metabolism remains unclear. Objective To evaluate and model the association between routinely measured newborn metabolic markers and SIDS in combination with established risk factors for SIDS. Design, Setting, and Participants This was a case-control study nested within a retrospective cohort using data from the California Office of Statewide Health Planning and Development and the California Department of Public Health. The study population included infants born in California between 2005 and 2011 with full metabolic data collected as part of routine newborn screening (NBS). SIDS cases were matched to controls at a ratio of 1:4 by gestational age and birth weight z score. Matched data were split into training (2/3) and testing (1/3) subsets. Data were analyzed from January 2005 to December 2011. Exposures Metabolites measured by NBS and established risk factors for SIDS. Main Outcomes and Measures The primary outcome was SIDS. Logistic regression was used to evaluate the association between metabolic markers combined with known risk factors and SIDS. Results Of 2 276 578 eligible infants, 354 SIDS (0.016%) cases (mean [SD] gestational age, 38.3 [2.3] weeks; 220 male [62.1%]) and 1416 controls (mean [SD] gestational age, 38.3 [2.3] weeks; 723 male [51.1%]) were identified. In multivariable analysis, 14 NBS metabolites were significantly associated with SIDS in a univariate analysis: 17-hydroxyprogesterone, alanine, methionine, proline, tyrosine, valine, free carnitine, acetyl-L-carnitine, malonyl carnitine, glutarylcarnitine, lauroyl-L-carnitine, dodecenoylcarnitine, 3-hydroxytetradecanoylcarnitine, and linoleoylcarnitine. The area under the receiver operating characteristic curve for a 14-marker SIDS model, which included 8 metabolites, was 0.75 (95% CI, 0.72-0.79) in the training set and was 0.70 (95% CI, 0.65-0.76) in the test set. Of 32 infants in the test set with model-predicted probability greater than 0.5, a total of 20 (62.5%) had SIDS. These infants had 14.4 times the odds (95% CI, 6.0-34.5) of having SIDS compared with those with a model-predicted probability less than 0.1. Conclusions and Relevance Results from this case-control study showed an association between aberrant metabolic analytes at birth and SIDS. These findings suggest that we may be able to identify infants at increased risk for SIDS soon after birth, which could inform further mechanistic research and clinical efforts focused on monitoring and prevention.
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