ArticleJMIR pediatrics and parenting2024
Digital Health as a Mechanism to Reduce Neonatal Intensive Care Unit Admissions: Retrospective Cohort Study.
Article in JMIR pediatrics and parenting, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
5 authors.
Funding
Abstract
Background: Admission to the neonatal intensive care unit (NICU) is costly and has been associated with financial and emotional stress among families. Digital health may be well equipped to impact modifiable health factors that contribute to NICU admission rates. Objective: The aim of the study is to investigate how the use of a comprehensive prenatal digital health platform is associated with gestational age at birth and mechanisms to reduce the risk of admission to the NICU. Methods: Data were extracted from 3326 users who enrolled in a comprehensive digital health platform between January 2020 and May 2022. Multivariable linear and logistic regression models were used to estimate the associations between hours of digital health use and (1) gestational age at birth and (2) mechanisms to reduce the risk of a NICU admission. Multivariable logistic regression models estimated the associations between (1) gestational age at birth and (2) mechanisms to reduce the risk of a NICU admission and the likelihood of a NICU admission. All analyses were stratified by the presence of any gestational conditions during pregnancy. Results: For users both with and without gestational conditions, hours of digital health use were positively associated with gestational age at birth (in weeks; with gestational conditions: β=.01; 95% CI 0.0006-0.02; P=.04 and without gestational conditions: β=.01; 95% CI 0.0006-0.02; P=.04) and mechanisms that have the potential to reduce risk of a NICU admission, including learning medically accurate information (with gestational conditions: adjusted odds ratio [AOR] 1.05, 95% CI 1.03-1.07; P<.001 and without gestational conditions: AOR 1.04, 95% CI 1.02-1.06; P<.001), mental health management (with gestational conditions: AOR 1.06, 95% CI 1.04-1.08; P<.001 and without gestational conditions: AOR 1.03, 95% CI 1.02-1.05; P<.001), and understanding warning signs during pregnancy (with gestational conditions: AOR 1.08, 95% CI 1.06-1.11; P<.001 and without gestational conditions: AOR 1.09, 95% CI 1.07-1.11; P<.001). For users with and without gestational conditions, an increase in gestational age at birth was associated with a decreased likelihood of NICU admission (with gestational conditions: AOR 0.62, 95% CI 0.55-0.69; P<.001 and without gestational conditions: AOR 0.59, 95% CI 0.53-0.65; P<.001). Among users who developed gestational conditions, those who reported that the platform helped them understand warning signs during pregnancy had lower odds of a NICU admission (AOR 0.63, 95% CI 0.45-0.89; P=.01). Conclusions: Digital health use may aid in extending gestational age at birth and reduce the risk of NICU admission.
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