Evidence map›Paper›PMID 40432632›Full record

ArticleCureus2025

Unsupervised Medication-Induced Abortions: A Cross-Sectional Study in a Tertiary-Care Hospital.

Preetam K Lenka, Manoj Kumar Mohanty, Saubhagya K Jena, Sudipta Singh, Jyotiranjan Sahoo

Abstract read
In one paragraph

Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Preetam K LenkaForensic Medicine, Institute of Medical Sciences (IMS) and Sum Hospital, Siksha 'O' Anusandhan (SOA), Bhubaneswar, IND.
Manoj Kumar MohantyForensic Medicine, All India Institute of Medical Sciences, Bhubaneswar, Bhubaneswar, IND.
Saubhagya K JenaObstetrics and Gyenacology, All India Institute of Medical Sciences, Bhubaneswar, Bhubaneswar, IND.
Sudipta SinghForensic Medicine, All India Institute of Medical Sciences, Bhubaneswar, Bhubaneswar, IND.
Jyotiranjan SahooCommunity Medicine, IMS and Sum Hospital, Siksha 'O' Anusandhan, Bhubaneswar, IND.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background Abortion refers to the termination of pregnancy before fetal viability, which is legally recognized at 28 weeks in India. Unsafe abortions, characterized by the absence of medical supervision, pose significant risks, including incomplete abortion, retained products of conception, and elevated maternal morbidity and mortality. Despite the Medical Termination of Pregnancy (MTP) Act (1971) and the introduction of Medical Abortion Pills (MAP), unsafe abortions remain prevalent. Objective To determine the prevalence of induced abortions through unsupervised use of MAP and to identify socio-demographic and obstetric factors associated with these cases, reported to the All India Institute of Medical Sciences (AIIMS), Bhubaneswar. Methods This hospital-based cross-sectional study enrolled 81 female patients aged 14-49 years, presenting with complications of unsupervised medical abortions. Data were collected using Case Report Forms (CRFs) and analyzed using SPSS v20. Statistical associations were assessed with chi-square or Fisher's exact tests. Results The prevalence of unsupervised medical abortions was 67 out of 81 (82.7%). Age of the subject was weakly associated with a number of abortions, but statistically significant (r = 0.238, p = 0.020). Socioeconomic status (χ

Indexed as

induced abortionmedical abortionmedical abortion pillsmtp actunsafe abortionunsupervised medication

Identifiers

PMID40432632
PMCPMC12106933

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.