Evidence map›Paper›PMID 36353024›Full record

ArticleJournal of family medicine and primary care2022

Pregnancy outcome among high-risk pregnant women in the rural area of Belagavi.

Sphurti Uday Chate, Chandra Shrishail Metgud

Open access · goldAbstract read
In one paragraph

Article in Journal of family medicine and primary care, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
3.0field-weighted citation impact, top 9% of its field
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

7 citing papers in PubMed, 11 citations in OpenAlex.

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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 at 1 institution in 1 country.

Sphurti Uday ChateDepartment of Community Medicine, Symbiosis Medical College for Women (SMCW), Symbiosis International University (Deemed University), Lavale, Pune, Maharashtra, India.
Chandra Shrishail MetgudDepartment of Community Medicine, J. N. Medical College, KAHER, Belagavi, Karnataka, India.
Symbiosis International University · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: India has around 25% high-risk pregnant mothers, which leads to about 75% perinatal morbidities.(1) The early prediction of a high-risk pregnancy and planning interventions can help in preventing complications and result in good pregnancy outcomes. Aims: To study the pregnancy outcome among the high-risk pregnant women of a rural area and to associate pregnancy outcomes of high-risk pregnant women with modified Coopland's criteria. Material and Methods: Study design: 1-year Longitudinal study from 2016 to 2017, Study population: The high-risk pregnant women attending PMSMA camp, Study area: Kinaye, Primary Health Centre, Belagavi. Sample size: 147, Data collection was done using a pretested predesigned questionnaire after obtaining patient consent and ethical clearance. Chi-square test was used to study the association of variables and categorical data presented as percentages. Results: Among the participants, 40.4% of the pregnant women had low-risk scores; 45.9% had high-risk scores, and 13.7% had severe-risk scores according to Coopland's high-risk pregnancy scoring. Nearly 29.5% high-risk pregnancies resulted in bad fetal outcomes. As Coopland's score in the high-risk group increased, the chance of having good fetal outcomes decreased, and this association was found to be statistically significant. Conclusions: 70.5% of the high-risk mothers had good pregnancy outcomes. The scoring system can be used by health workers for the prediction of high-risk pregnancy and plan treatment and preventive measures.

Indexed as

BelagaviHigh riskPMSMApregnancy outcome

Identifiers

PMID36353024
PMCPMC9638629
OpenAlexW4295345860

What OpenQuestion holds

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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.