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Developing a resiliency model for survival without major morbidity in preterm infants
- Source :
- Journal of perinatology : official journal of the California Perinatal Association, vol 43, iss 4
- Publication Year :
- 2023
- Publisher :
- eScholarship, University of California, 2023.
-
Abstract
- Objective Develop and validate a resiliency score to predict survival and survival without neonatal morbidity in preterm neonates Study design Models using maternal, perinatal, and neonatal variables were developed using LASSO method in a population based Californian administrative dataset. Outcomes were survival and survival without severe neonatal morbidity. Discrimination was assessed in the derivation and an external dataset from a tertiary care center. Results Discrimination in the internal validation dataset was excellent with a c-statistic of 0.895 (95% CI 0.882–0.908) for survival and 0.867 (95% CI 0.857–0.877) for survival without severe neonatal morbidity, respectively. Discrimination remained high in the external validation dataset (c-statistic 0.817, CI 0.741–0.893 and 0.804, CI 0.770–0.837, respectively). Conclusion Our successfully predicts survival and survival without major morbidity in preterm babies born at
- Subjects :
- Pediatric
Clinical Sciences
Obstetrics and Gynecology
Infant
Diseases
Gestational Age
Reproductive health and childbirth
Perinatal Period - Conditions Originating in Perinatal Period
Newborn
Low Birth Weight and Health of the Newborn
Pediatrics
Paediatrics and Reproductive Medicine
Good Health and Well Being
Pregnancy
Preterm
Pediatrics, Perinatology and Child Health
Infant Mortality
Humans
Female
Morbidity
Premature
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- Journal of perinatology : official journal of the California Perinatal Association, vol 43, iss 4
- Accession number :
- edsair.doi.dedup.....1b7ff31fa362621ffce18ba8a3594d4a