Journal article
Developing a resiliency model for survival without major morbidity in preterm infants
Journal of perinatology, Vol.43, pp.452-457
2023
DOI: 10.1038/s41372-022-01521-3
PMCID: PMC10079534
PMID: 36220984
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 <32 weeks. This score can be used to adjust for multiple variables across administrative datasets.
Details
- Title: Subtitle
- Developing a resiliency model for survival without major morbidity in preterm infants
- Creators
- Martina A. Steurer - University of California, San FranciscoKelli K. Ryckman - Univ Iowa, Coll Publ Hlth, Dept Epidemiol, Iowa City, IA USARebecca J. Baer - Univ Calif San Francisco, Calif Preterm Birth Initiat, San Francisco, CA 94143 USAJean Costello - Univ Calif San Francisco, Dept Epidemiol & Biostat, San Francisco, CA 94143 USAScott P. Oltman - University of California San Francisco Medical CenterCharles E. McCulloch - Univ Calif San Francisco, Dept Epidemiol & Biostat, San Francisco, CA 94143 USALaura L. Jelliffe-Pawlowski - University of California San Francisco Medical CenterElizabeth E. Rogers - Univ Calif San Francisco, Dept Pediat, San Francisco, CA 94143 USA
- Resource Type
- Journal article
- Publication Details
- Journal of perinatology, Vol.43, pp.452-457
- DOI
- 10.1038/s41372-022-01521-3
- PMID
- 36220984
- PMCID
- PMC10079534
- NLM abbreviation
- J Perinatol
- ISSN
- 0743-8346
- eISSN
- 1476-5543
- Publisher
- Springer Nature
- Number of pages
- 6
- Grant note
- R01 HD102381 / Eunice Kennedy Shriver National Institute of Child Health and Human Development; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
- Language
- English
- Electronic publication date
- 10/11/2022
- Date published
- 2023
- Academic Unit
- Stead Family Department of Pediatrics; Epidemiology
- Record Identifier
- 9984306756602771
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