Evidence map›Paper›PMID 41246737›Full record

ArticleCureus2025

Stillbirth Trends and Determinants: A Six-Year Registry-Based Analysis From Two District Hospitals in the United Kingdom (2019-2024).

Rupa Brahma, Manjula Samyraju, Lesley Carline

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

3 authors.

Rupa BrahmaObstetrics and Gynecology, Peterborough City Hospital, Peterborough, GBR.
Manjula SamyrajuObstetrics and Gynecology, Peterborough City Hospital, Peterborough, GBR.
Lesley CarlineObstetrics and Gynecology, Peterborough City Hospital, Peterborough, GBR.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionDespite advances in obstetric care, stillbirth remains a major public health concern. Understanding local patterns and risk factors is essential for developing targeted strategies for prevention. This study aimed to review the demographic and clinical characteristics of stillbirths across two district hospitals in the United Kingdom over a six-year period.

methodsA retrospective secondary analysis was conducted using registry-based surveillance data of all stillbirths occurring between 2019 and 2024 at two hospitals under the same healthcare trust. Data on maternal demographics, gestational age at stillbirth, and associated risk factors were extracted and analyzed. Descriptive statistics were used to identify key trends. As this was a secondary analysis of de-identified data, ethical approval was waived.

resultsA total of 118 stillbirths were documented during the study period. The majority occurred in women aged >30 years (n=68, 57.6%), with the highest proportion in those aged >35 years (n=39, 33.0%). A significant number of stillbirths occurred at >36 weeks' gestation (n=42, 35.6%). White women accounted for the majority of cases (n=84, 71.2%), although notable trends were also observed among Asian and Black ethnicities in specific years. Reduced fetal movements (n=50, 42.4%) and high maternal BMI (n=31, 26.3%) were the most frequently reported modifiable risk factors.

conclusionThis study highlights ongoing challenges in stillbirth prevention and emphasizes the importance of timely detection of fetal compromise and targeted interventions for at-risk groups. Regular institutional reviews are essential for guiding quality improvement efforts.

Indexed as

ethnicitymaternal obesityneonatal deathsreduced fetal movementretrospective cohortstillbirth

Identifiers

PMID41246737
PMCPMC12619131

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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.