Evidence map›Paper›PMID 39412879›Full record

ArticleJMIR pediatrics and parenting2024

Digital Health as a Mechanism to Reduce Neonatal Intensive Care Unit Admissions: Retrospective Cohort Study.

Alison K Brinson, Hannah R Jahnke, Natalie Henrich, Christa Moss, Neel Shah

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Alison K BrinsonMaven Clinic, New York, NY, United States.ORCID http://orcid.org/0000-0002-5191-1336
Hannah R JahnkeMaven Clinic, New York, NY, United States.ORCID http://orcid.org/0000-0003-1875-5332
Natalie HenrichMaven Clinic, New York, NY, United States.ORCID http://orcid.org/0000-0002-0293-1859
Christa MossMaven Clinic, New York, NY, United States.ORCID http://orcid.org/0000-0003-2516-7862
Neel ShahMaven Clinic, New York, NY, United States.ORCID http://orcid.org/0000-0002-8971-7627

Funding

From Biological to Social Processes: Interdisciplinary Training in Life Course ResearchT32HD091058 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ROBERT A HUMMER, Amanda L Thompson · 2017 to 2026
$4.3M
NICHD NIH HHS T32 HD091058
6 · The paper itself

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.

Indexed as

digital healtheducationgestational conditionsMaven Clinicmental health managementmobile phoneneonatalneonatal intensive care unitNICU admissions

Identifiers

PMID39412879
PMCPMC11498062

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.