Evidence map›Paper›PMID 37959282›Full record

ArticleJournal of clinical medicine2023

Association between Delivery during Off-Hours and the Risk of Severe Maternal Morbidity: A Nationwide Population-Based Cohort Study.

Il Yun, Eun-Cheol Park, Jin Young Nam

Open access · goldAbstract read
In one paragraph

Article in Journal of clinical medicine, 2023. 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
0.3field-weighted citation impact, top 35% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

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 at 2 institutions in 1 country.

Il YunDepartment of Public Health, Graduate School, Yonsei University, Seoul 03722, Republic of Korea.
Eun-Cheol ParkInstitute of Health Services Research, Yonsei University, Seoul 03722, Republic of Korea.ORCID 0000-0002-2306-5398
Jin Young NamDepartment of Healthcare Management, Eulji University, Seongnam 13135, Republic of Korea.ORCID 0000-0003-0540-8753
Yonsei University · KREulji University · KR

Funding

National Research Foundation of Korea 2020R1C1C1013668
6 · The paper itself

Abstract

This study evaluated the association between off-hour deliveries and the risk of severe maternal morbidity (SMM). Data regarding Korean deliveries between 2005 and 2019 obtained from the National Health Insurance Service were used. SMM was evaluated using an algorithm developed by the United States Centers for Disease Control and Prevention. Modified Poisson regression analyses were conducted to investigate the association between off-hour deliveries and SMM, with stratification by hospital region and the number of beds. Approximately 32.7% of the 3,076,448 nulliparous women in this study delivered during off-hours, including 2.6% who experienced SMM. Patients who delivered at night had the highest risk of SMM (weekday nights, adjusted risk ratio (aRR): 1.41, 95% confidence interval (CI): 1.38-1.44; weekend nights, OR: 1.40, 95% CI: 1.34-1.46). The SMM of night deliveries was higher at hospitals located in small cities and those with 100-499 beds (weekend night: small cities, aRR: 1.49, 95% CI: 1.40-1.59; 100-499 beds, aRR: 1.83, 95% CI: 1.67-2.01; weekday night: small cities, aRR: 1.46, 95% CI: 1.42-1.51; 100-499 beds, aRR: 1.70, 95% CI: 1.62-1.79). Therefore, nighttime deliveries are associated with a higher risk of SMM, especially at hospitals located in small cities and those with 100-499 beds.

Indexed as

maternal healthnighttime deliveryoff-hour deliverysevere maternal morbidity

Identifiers

PMID37959282
PMCPMC10648246
OpenAlexW4388009239

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.