Predictive Models for Very Preterm Birth: Developing a Point-of-Care Tool
Autor: | Giovanni Nattino, Jason A. Benedict, Gary Philips, Patricia Temple Gabbe, Steven G. Gabbe, Stanley Lemeshow, Courtney Hebert |
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Rok vydání: | 2020 |
Předmět: |
Psychological intervention
Gestational Age Logistic regression Risk Assessment 03 medical and health sciences 0302 clinical medicine Pregnancy Risk Factors 030225 pediatrics Humans Very Preterm Birth Medicine 030212 general & internal medicine Probability Retrospective Studies Receiver operating characteristic business.industry Obstetrics and Gynecology Retrospective cohort study medicine.disease Logistic Models ROC Curve Multivariate Analysis Pediatrics Perinatology and Child Health Cohort Premature Birth Female business Medicaid Demography |
Zdroj: | American Journal of Perinatology. 39:092-098 |
ISSN: | 1098-8785 0735-1631 |
Popis: | Objective The objective of this study was to create three point-of-care predictive models for very preterm birth using variables available at three different time points: prior to pregnancy, at the end of the first trimester, and mid-pregnancy. Study Design This is a retrospective cohort study of 359,396 Ohio Medicaid mothers from 2008 to 2015. The last baby for each mother was included in the final dataset. Births prior to 22 weeks were excluded. Multivariable logistic regression was used to create three models. These models were validated on a cohort that was set aside and not part of the model development. The main outcome measure was birth prior to 32 weeks. Results The final dataset contained 359,396 live births with 6,516 (1.81%) very preterm births. All models had excellent calibration. Goodness-of-fit tests suggested strong agreement between the probabilities estimated by the model and the actual outcome experience in the data. The mid-pregnancy model had acceptable discrimination with an area under the receiver operator characteristic curve of approximately 0.75 in both the developmental and validation datasets. Conclusion Using data from a large Ohio Medicaid cohort we developed point-of-care predictive models that could be used before pregnancy, after the first trimester, and in mid-pregnancy to estimate the probability of very preterm birth. Future work is needed to determine how the calculator could be used to target interventions to prevent very preterm birth. Key Points |
Databáze: | OpenAIRE |
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