Evidence map›Paper›PMID 41098458›Full record

ArticleJournal of education and health promotion2025

Prenatal prognostics: Validating high-risk pregnancy predictions for maternal and perinatal outcomes.

Payal Bhagat, Jasneet Kaur

Abstract read
In one paragraph

Article in Journal of education and health promotion, 2025. 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

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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.

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

2 authors.

Payal BhagatDepartment of Nursing, Symbiosis College of Nursing (SCON), Symbiosis International (Deemed University), Pune, Maharashtra, India.
Jasneet KaurDepartment of Nursing, Symbiosis College of Nursing (SCON), Symbiosis International (Deemed University), Pune, Maharashtra, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHigh-risk pregnancies pose significant challenges to maternal and perinatal health, necessitating effective identification and management strategies. The development of reliable prediction tools is critical for early intervention and improving outcomes in this vulnerable population to identify high-risk pregnancy and assess its maternal and perinatal outcome. MATERIAL AND

methodsIt is a prospective cross-sectional research design. A non-probability convenience sampling was used to collect 300 samples who met the inclusion criteria. The data were collected from antenatal mothers who were visiting selected primary health centers (PHCs) demographic, obstetric data collected, and a scoring system of high-risk pregnancies were used. Data analysis was performed by using one-way ANOVA and logistic regression.

resultsA total of 58% of antenatal mothers were at extremely high risk of pregnancy. By using one-way ANOVA for regression analysis, a statistically significant variation was found between regression and residual (

conclusionThis study establishes the significance of prenatal prediction in identifying high-risk pregnancies and offering a valuable tool for maternal and perinatal risk assessment. The findings underscore the potential for prenatal care strategies to mitigate the risk associated with high-risk pregnancies and contribute to enhanced overall prenatal and perinatal outcomes.

Indexed as

High-risk pregnancyoutcomespredictionprenatalvalidation

Identifiers

PMID41098458
PMCPMC12520309

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LicenceCC BY-NC-SA
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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.