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Identification of extremely premature infants at high risk of rehospitalization
Namasivayam Ambalavanan1, Waldemar A Carlo, Scott A McDonald
1Department of Pediatrics, University of Alabama at Birmingham, Birmingham, AL 35249-7335, USA. ambal@uab.edu
Insights
Extremely low birth weight infants often need rehospitalization. This study identified high-risk infants at discharge using predictive models to improve post-discharge care planning for vulnerable newborns.
Area of Science:
- Neonatal Medicine
- Pediatric Healthcare
- Medical Informatics
Background:
- Extremely low birth weight (ELBW) infants face a high risk of rehospitalization during infancy.
- Identifying these infants at discharge is crucial for proactive care planning.
Purpose of the Study:
- To identify ELBW infants at higher risk for rehospitalization upon discharge.
- To develop predictive tools for post-discharge care planning.
Main Methods:
- Analysis of data from 3787 ELBW infants (2002-2005) from the Eunice Kennedy Shriver National Institute of Child Health and Human Development Neonatal Research Network.
- Development of scoring systems using stepwise logistic regression and classification and regression-tree (CART) analysis.
- Primary outcome: rehospitalization by 18-22 months; Secondary outcome: respiratory rehospitalization in the first year.
Main Results:
- 45% of ELBW infants were rehospitalized by 18-22 months; 14.7% for respiratory causes in the first year.
- Predictors for rehospitalization included shunt surgery for hydrocephalus, prolonged pulmonary hospital stay (>120 days), necrotizing enterocolitis, higher fraction of inspired oxygen, and male gender.
- CART analysis showed infants with pulmonary hospital stays >120 days had a 66% rehospitalization rate.
Conclusions:
- Developed scoring systems and CART models accurately identify ELBW infants at increased risk of rehospitalization.
- These models can aid in planning targeted post-discharge care for high-risk infants.
Objective:
Extremely low birth weight infants often require rehospitalization during infancy. Our objective was to identify at the time of discharge which extremely low birth weight infants are at higher risk for rehospitalization.
Methods:
Data from extremely low birth weight infants in Eunice Kennedy Shriver National Institute of Child Health and Human Development Neonatal Research Network centers from 2002-2005 were analyzed. The primary outcome was rehospitalization by the 18- to 22-month follow-up, and secondary outcome was rehospitalization for respiratory causes in the first year. Using variables and odds ratios identified by stepwise logistic regression, scoring systems were developed with scores proportional to odds ratios. Classification and regression-tree analysis was performed by recursive partitioning and automatic selection of optimal cutoff points of variables.
Results:
A total of 3787 infants were evaluated (mean ± SD birth weight: 787 ± 136 g; gestational age: 26 ± 2 weeks; 48% male, 42% black). Forty-five percent of the infants were rehospitalized by 18 to 22 months; 14.7% were rehospitalized for respiratory causes in the first year. Both regression models (area under the curve: 0.63) and classification and regression-tree models (mean misclassification rate: 40%-42%) were moderately accurate. Predictors for the primary outcome by regression were shunt surgery for hydrocephalus, hospital stay of >120 days for pulmonary reasons, necrotizing enterocolitis stage II or higher or spontaneous gastrointestinal perforation, higher fraction of inspired oxygen at 36 weeks, and male gender. By classification and regression-tree analysis, infants with hospital stays of >120 days for pulmonary reasons had a 66% rehospitalization rate compared with 42% without such a stay.
Conclusions:
The scoring systems and classification and regression-tree analysis models identified infants at higher risk of rehospitalization and might assist planning for care after discharge.
