A multicenter study of preterm birth weight and gestational age—specific neonatal mortality

Copper, Rachel L.; Goldenberg, Robert L.; Creasy, Robert K.; DuBard, Mary B.; Davis, Richard O.; Entman, Stephen S.; Iams, Jay D.; Cliver, Suzanne P.

doi:10.1016/s0002-9378(12)90889-3

Cited by 272 publications

(138 citation statements)

References 15 publications

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“…These findings demonstrate the importance of a perinatal±neonatal team approach to management of the anticipated delivery of a VLBW infant. GA has been reported as the primary determinant of survival for the infant weighing <751 g at birth 15,24 or less than 29 weeks GA. 45 Our data show that within each week of GA below 25 weeks survival was not reliably related to BW. Although there was a trend for decreased survival in smaller infants, it did not reach statistical significance.…”

mentioning

confidence: 56%

Nursery Survival for Infants of Birth Weight 500–1500 Grams During 1982–1995

et al. 2001

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mentioning

confidence: 56%

Nursery Survival for Infants of Birth Weight 500–1500 Grams During 1982–1995

et al. 2001

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“…Outros autores [17][18][19] têm mostrado resultados semelhantes, com as meninas apresentando mais chance de viver em todos os grupos de mesmo peso de nascimento e idade gestacional. Um dos principais motivos desta menor mortalidade do sexo feminino é o amadurecimento do pulmão fetal, que ocorre mais precocemente no sexo feminino, diminuindo, com isso, a incidência de problemas respirató-rios do RN, que estão entre as principais causas de morte no período neonatal.…”

Section: Métodosunclassified

Early neonatal mortality in Caxias do Sul: a cohort study

Araújo

Bozzetti²,

Tanaka³

2000

J Pediatr (Rio J)

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Objectives: To establish the profile of neonates in Caxias do Sul city, and to study early neonatal mortality, its causes and related variables.Methods: This cohort study enrolled 5,545 newborns, which were followed up to 7 days after birth. The probability of early neonatal mortality was calculated and multiple logistic regression was performed to relate all studied variables to the outcome of early neonatal death.Results: The observed probability of early neonatal mortality was 7.44 per thousand live births. The incidence of premature births and low birth weight was 9.4% and 8.1%, respectively. Fifty five percent of the neonates were born through cesarean section, which were related to socioeconomic and educational level. Previous history of neonatal mortality, maternal age > 35 years, gestational age, Apgar score < 7, male sex and low birth weight were related to early neonatal death. The main cause of death was hyaline membrane disease, followed by congenital cardiopaties, extreme preterm and abruptio placentae.Conclusion: Even though the observed probability of early neonatal mortality was low, some deaths may have been avoided if better prenatal and delivery care, as well as newborn assistance had been offered. J. pediatr. (Rio J.). 2000; 76(3): ResumoObjetivo: Estabelecer o perfil dos neonatos de Caxias do Sul e estudar a mortalidade neonatal precoce, suas causas e as variáveis a esta relacionadas.Métodos: Estudo de coorte envolvendo 5.545 recém-nascidos acompanhados por até 7 dias de vida. Calculou-se a probabilidade de morte neonatal precoce (PMNP), utilizando-se a regressão logística múltipla para relacionar as variáveis estudadas com a mortalidade neonatal precoce.Resultados: A PMNP observada foi de 7,44 por mil nascidos vivos. A incidência de partos prematuros e de baixo peso ao nascer foi de 9,4% e 8,1%, respectivamente. O índice de cesarianas foi de 55%, apresentando relação com o nível socioeconômico e educacional. As variáveis relacionadas ao óbito foram a história de natimortalidade, a idade materna >35 anos, idade gestacional, Apgar < 7, sexo masculino e baixo peso. A principal causa de óbito foi a doença da membrana hialina, seguida pelas cardiopatias congêni-tas, prematuridade extrema e descolamento prematuro de placenta.Conclusão: Apesar da PMNP ter sido baixa, ocorreram mortes que poderiam ter sido evitadas com um melhor atendimento no pré-natal, no parto e na assistência ao RN. J. pediatr. (Rio J. IntroduçãoA mortalidade infantil (MI) é vista hoje como um evento evitável e traçador da qualidade de vida e dos serviços de saúde. Para Leal 1 , ela é um indicador do nível de saúde de uma população, sintetizando as condições de bem-estar social, político e ético de uma dada conformação social.Nas últimas décadas, tem havido um decréscimo acentuado da MI em todo o mundo, como demonstra o relatório da Unicef, 1997. No Brasil, o coeficiente de mortalidade infantil (CMI) passou de 118 por mil nascidos vivos (NV) em 1960 para 48 por mil NV no período de 1987 a 1996, mas ainda apresenta var...

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“…There is an absence of data to explain the way in which low birth weight, small for gestational age, and preterm risks interact with neonatal mortality in high mortality burden settings. In the United States, where the neonatal mortality rate is relatively low at five per 1,000 live births, [24], mortality outcomes are reported to vary across groups of weight for gestational age, [14], with newborns born small for gestational age at 34-36 week gestation estimated to have a neonatal mortality risk as much as 44 times higher than the risk experienced by newborns with appropriate weight for gestational age, [16], [4]. There are multiple causes of low birth weight, including early induction of labour or caesarean birth, multiple pregnancies, infections and chronic conditions such as diabetes and high blood pressure but the main causes are preterm birth and restricted growth in the womb resulting in babies who are referred to as "small for their dates"; [21].…”

Section: Introductionmentioning

confidence: 99%

Modeling Maternal Risk Factors Affecting Low Birth Weight Among Infants in Kenya

Gathimba¹

2017

AJTAS

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Abstract:The strong association of birth weight with infant mortality is the main focus of birth weight research, with the assumption that birth weight is a major determinant of infant survival. Studies on factors of low birth weight in Kenya have neglected the flexible approach of using smooth functions for some covariates in models. Such flexible approach reveals detailed relationship of covariates with the response. The study sought to investigate risk factors of low birth weight in Kenya by assuming a flexible approach for continuous covariates and geographical random effect. The study used semi parametric models to flexibly model the effects of selected covariates and spatial effects. Our spatial analysis is based on a flexible geo-additive model using the provinces as the geographic unit of analysis, which allows to separate smooth structured spatial effects from random effect. A Gaussian model for birth weight in grams and a binary logistic model for the binary outcome were fitted. Continuous covariates was modeled by the penalized (p) splines and spatial effects was smoothed by the two dimensional p-spline. The specific objectives of the study was to investigate factors of low birth weight in Kenya by taking into account the hierarchical nature of child birth weight factors using a Bayesian hierarchical model. The study used secondary data from Kenya 2014 demographic and health survey (KDHS) data. The study found that child birth order, mother weight and height are significant predictors of birth weight. Secondary education for mother, birth order categories 2-3 and 4-5, wealth index of richer family and mother height were significant predictors of child size at birth. The area associated with low birth weight was North Eastern and areas with increased risk to less than average size at birth were Central and Eastern. The study found support for the flexible modeling of some covariates that clearly have nonlinear influences. Nevertheless there was no strong support for inclusion of geographical spatial analysis. The spatial patterns and the maps generated could be used for targeting development efforts at a glance. These findings have important implications for targeting policy as well as the search for left-out variables that might account for these residual spatial patterns.

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A multicenter study of preterm birth weight and gestational age—specific neonatal mortality

Cited by 272 publications

References 15 publications

Nursery Survival for Infants of Birth Weight 500–1500 Grams During 1982–1995

Nursery Survival for Infants of Birth Weight 500–1500 Grams During 1982–1995

Early neonatal mortality in Caxias do Sul: a cohort study

Modeling Maternal Risk Factors Affecting Low Birth Weight Among Infants in Kenya

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