Pediatrics · 2019
Distinct Populations of Sudden Unexpected Infant Death Based on Age.
СтатьяПоддержка NIH: внешняя программаПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Lavista Ferres Juan M, Anderson Tatiana M, Johnston Richard, Ramirez Jan-Marino, Mitchell Edwin A
Аннотация
OBJECTIVES: In most recent studies, authors combine all cases of sudden infant death syndrome, other deaths from ill-defined or unknown causes, and accidental suffocation and strangulation in bed as a single population to analyze sudden unexpected infant death (SUID). Our aim with this study is to determine if there are statistically different subcategories of SUID that are based on the age of death of an infant.
METHODS: In this retrospective, cross-sectional analysis, we analyzed the Centers for Disease Control and Prevention Birth Cohort Linked Birth/Infant Death Data Set (2003-2013: 41 125 233 births and 37 624 SUIDs). Logistic regression models were developed to identify subpopulations of SUID cases by age of death, and we subsequently analyzed the effects of a set of covariates on each group.
RESULTS: Two groups were identified: sudden unexpected early neonatal deaths (SUENDs; days 0-6) and postperinatal SUIDs (days 7-364). These groups significantly differed in the distributions of assigned International Classification of Diseases, 10th Revision code, live birth order, marital status, age of mother, birth weight, and gestational length compared to postperinatal SUIDs (days 7-364). Maternal smoking during pregnancy was not a significant risk factor for deaths that occurred in the first 48 hours.
CONCLUSIONS: SUEND should be considered as a discrete entity from postperinatal SUID in future studies. These data could help improve the epidemiological understanding of SUEND and SUID and provide clues to a mechanistic understanding underlying the causes of death.
METHODS: In this retrospective, cross-sectional analysis, we analyzed the Centers for Disease Control and Prevention Birth Cohort Linked Birth/Infant Death Data Set (2003-2013: 41 125 233 births and 37 624 SUIDs). Logistic regression models were developed to identify subpopulations of SUID cases by age of death, and we subsequently analyzed the effects of a set of covariates on each group.
RESULTS: Two groups were identified: sudden unexpected early neonatal deaths (SUENDs; days 0-6) and postperinatal SUIDs (days 7-364). These groups significantly differed in the distributions of assigned International Classification of Diseases, 10th Revision code, live birth order, marital status, age of mother, birth weight, and gestational length compared to postperinatal SUIDs (days 7-364). Maternal smoking during pregnancy was not a significant risk factor for deaths that occurred in the first 48 hours.
CONCLUSIONS: SUEND should be considered as a discrete entity from postperinatal SUID in future studies. These data could help improve the epidemiological understanding of SUEND and SUID and provide clues to a mechanistic understanding underlying the causes of death.