Late preterm infants (LPIs), those born at 34 to 36 6/7 weeks’ gestation, account for the majority of preterm births (73%).1 Given their physiologic immaturity, LPIs are at increased risk of respiratory distress, hyperbilirubinemia, hypoglycemia, and other complications in the neonatal period, and are at increased risk of hospital readmission in the first month of life.2 As Amsalu and colleagues describe in this month’s issue of Hospital Pediatrics,3 identification of a predictive model to differentiate LPI at higher risk of complications would help inform tailored discharge plans and prevent readmissions.
The authors conducted a large retrospective cohort study of almost 3 million infants, 122 014 of whom were born late preterm from 2011 to 2017, across the state of California. They used descriptive statistics and χ2 tests to characterize the timing and precipitators of hospital readmissions among late preterm infants (LPIs). The Mann-Kendall trend test was used to assess temporal trends, and multivariable logistic regression was used to estimate adjusted odds ratios for jaundice-specific and all-cause readmission, with reverse stepwise selection to simplify the variables in the model. Model performance was evaluated by estimating the c-statistic.
Odds of readmission among LPIs was over twice that of term infants (2.34 [95% confidence interval: 2.28–2.40]). Readmission rate varied by gestational age with, 35-week infants having the highest rate (6.7%), followed by 34- and 36-week infants (6.0% and 5.7%, respectively). Reasons for readmission included jaundice (58.9%), infections (10.8%), and respiratory complications (3.5%). An increase in both all-cause and jaundice-specific readmission among LPIs between 2011 and 2017 was identified. In the adjusted model, factors associated with greater odds of readmission included assisted vaginal birth, maternal age ≥34 years, chorioamnionitis, diabetes, and primiparity.
This study had significant strengths. For one, the large sample size with administrative data from the California Office of Statewide Health Planning and Development, allowed for examination of multiple potential predictors at once. Likewise, the study population was diverse and the variables were from administrative records and not self-report.
However, this study also had multiple limitations inherent to research relying on administrative data, and the final predictive model of neonatal readmission only demonstrated discriminatory ability of 60% (c-statistic 0.603 [95% confidence interval: 0.596–0.610]). This is likely because of missing key clinical information relevant to readmission risk, including feeding and weight loss status, screening test results, and treatments during birth hospitalization. Given that hyperbilirubinemia was a key indication for readmission in this cohort, the lack of data on bilirubin testing and phototherapy use is particularly salient. At least 2 recent studies have suggested that, among late preterm and term newborns, simple models comprised only of gestational age, total serum bilirubin level, and the American Academy of Pediatrics phototherapy threshold for age may be highly predictive4,5 of readmission. Because infants admitted to a NICU were excluded from the current study, selection bias is also a potential limitation because of variability in NICU admission practices across hospitals.6,7
Results of the current study underscore the continued vulnerability of LPIs, particularly in the setting of pregnancy complications including maternal diabetes, chorioamnionitis, and instrumentation at delivery. Hospital-level practices related to caring for these subgroups, including specialized care pathways, approaches and resources for lactation, and level of nursing support, are unmeasurable in administrative data, but would potentially inform key areas of intervention and future research in improving newborn care.
A particularly notable finding of the current study is the increasing temporal trend for readmission risk among LPIs. The authors suggest that previous policy interventions, such as those aimed at prolonging minimum hospital stays and standardizing hyperbilirubinemia screening, have fallen short of their desired effect. However, it is also possible that an increased awareness of potential risks for LPIs has led to more intensive outpatient surveillance and a reduced clinical threshold for readmission. As the authors allude, newborn readmission is a tricky outcome because its relationship to health care quality depends on the extent to which families have trust in and access to the health care system.
The next steps in research for LPIs involve prospective, intervention-based studies. A large sample of newborns would be required to detect a clinically meaningful decrease in readmission risk, potentially using a quality improvement collaborative or other multicenter approach.8 Such a study, in which multiple birth hospitals assess their practices and policies for phototherapy, NICU admission, lactation support, discharge planning, and the rest, identify opportunities to standardize or improve care, and measure patient-level outcomes, would be ideal for implementation in the Better Outcomes through Research for Newborns network, which represents >400 000 births annually (10% of all US births) and has already demonstrated care of the LPI to be a research topic of high priority.9
In conclusion, LPIs remain an important population of focus. It remains difficult to identify actionable interventions on the basis of secondary analysis of administrative data. Given the challenges in developing a predictive model from the variables available in administrative data sets, a focus on hospital-level approaches is needed to help optimize care for LPIs.
The contents of this publication are solely the responsibility of the authors and do not represent the official views of the National Institutes of Health.
FUNDING: Dr Kair’s effort was supported by a Building Interdisciplinary Research Careers in Women’s Health award (#K12 HD051958, PI Nancy Lane, MD) funded by the National Institute of Child Health and Human Development, Office of Research on Women’s Health, Office of Dietary Supplements, and the National Institute of Aging.
CONFLICT OF INTEREST DISCLAIMER: The authors have indicated they have no conflicts of interest relevant to this article to disclose.
COMPANION PAPER: A companion to this article can be found online at www.hosppeds.org/cgi/doi/10.1542/hpeds.2021-006215.