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Published on: November 20, 2015
Antenatal Prediction of Early Cord Clamping among Infants Born Extremely Preterm
Anup Katheria1, Rebecca A Dorner1, William Grobman2
1Department of Pediatrics, Sharp Neonatal Research Institute, San Diego, CA.
Insights
Prenatal factors like center, lack of magnesium, and cesarean delivery predict early cord clamping (ECC) in extremely preterm infants. Identifying these risks can guide quality improvement for deferred cord clamping (DCC).
Area of Science:
- Neonatalogy
- Perinatal Medicine
- Obstetrics
Background:
- Early cord clamping (ECC) practices in extremely preterm infants (22-28 weeks gestation) lack clear predictive risk factors.
- Understanding factors associated with ECC is crucial for optimizing neonatal outcomes and implementing targeted interventions.
Purpose of the Study:
- To identify prenatal risk factors associated with early cord clamping (ECC) in extremely preterm infants.
- To develop a predictive model for identifying infants at highest risk of receiving ECC.
Main Methods:
- Utilized stepwise logistic regression and classification and regression tree (CART) analysis.
- Analyzed data from a large cohort of extremely preterm infants (n=12,622).
Main Results:
- Key predictors for ECC included delivery center, lack of antenatal magnesium, cesarean delivery, lower gestational age, and antenatal hemorrhage.
- Maternal race and ethnicity also showed significant associations with ECC versus deferred cord clamping (DCC).
Conclusions:
- Multiple prenatal factors influence the likelihood of ECC in extremely preterm infants.
- Findings highlight disparities in DCC rates based on maternal race and ethnicity.
- Identifying these risk factors can inform future research and drive quality improvement initiatives to increase DCC.
Objective:
To identify prenatal risk factors associated with early cord clamping (ECC) in infants born extremely preterm (22-28 weeks) and to use these factors to predict which infants have the highest risk of ECC.
Study Design:
Stepwise logistic regression and classification and regression tree analysis were performed to identify variables most associated with ECC and to build a parsimonious model to identify infants born preterm who are at the highest risk of ECC.
Results:
There were 12 622 infants eligible for analysis (ECC, n = 8465 vs deferred cord clamping [DCC], n = 4157). In the classification and regression tree model, center, lack of antenatal magnesium, cesarean delivery, lower gestational age, and antenatal hemorrhage, in that rank order, were the factors that contributed most to identifying which infants received ECC. Several additional factors were also statistically significant, including time to delivery after admission to the hospital as well as maternal race and ethnicity.
Conclusions:
Our results suggest that there are multiple factors among extremely preterm pregnancies, including center, lack of antenatal magnesium, cesarean delivery, lower gestational age, and antenatal hemorrhage, that are associated with infants who are more likely to miss DCC. There are also differences in rates by maternal race and ethnicity in who receives DCC compared with ECC. Identifying these factors now can inform future research and encourage local and larger-scale quality improvement practice changes.
