Evidence map›Paper›PMID 36673531›Full record

ArticleHealthcare (Basel, Switzerland)2023

Profile of Hospital Admissions Due to Preterm Labor and Delivery in England.

Abdallah Y Naser, Hassan Al-Shehri, Noora Altamimi, Anas Alrasheed, Lama Albalawi

Abstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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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

5 authors.

Abdallah Y NaserDepartment of Applied Pharmaceutical Sciences and Clinical Pharmacy, Faculty of Pharmacy, Isra University, Amman 11622, Jordan.ORCID 0000-0001-8440-7446
Hassan Al-ShehriDepartment of Pediatrics, College of Medicine, Imam Mohammad Ibn Saud Islamic University, Riyadh 11564, Saudi Arabia.ORCID 0000-0003-2972-8276
Noora AltamimiCollege of Medicine, Imam Mohammad Ibn Saud Islamic University, Riyadh 11564, Saudi Arabia.ORCID 0000-0001-9978-4383
Anas AlrasheedCollege of Medicine, Imam Mohammad Ibn Saud Islamic University, Riyadh 11564, Saudi Arabia.
Lama AlbalawiCollege of Medicine, Imam Mohammad Ibn Saud Islamic University, Riyadh 11564, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesPreterm labor and delivery are associated with various short- and long-term complications in neonates and infants. This research aimed to look at the trends in preterm labor and birth-related hospitalizations in England. MATERIAL AND

methodsThe Hospital Episode Statistics database was used to extract hospital admission data for the ecological study of preterm labor and delivery between April 2012 and April 2020 in England.

resultsThe overall admission rates decreased by 26.2%, from 14,210 in 2012 (CI: 99.18-102.49) to 10,490 in 2020 (CI: 73.02-75.87) per 100,000 individuals. Hospitalizations were frequently caused by spontaneous labor with preterm delivery, spontaneous labor without delivery, and preterm delivery without spontaneous labor (68.9%, 20.6%, and 9.6%, respectively). The rate of hospital admission due to preterm delivery without spontaneous labor, preterm labor without delivery, preterm spontaneous labor with preterm delivery, and preterm spontaneous labor with term delivery decreased by 32.0%, 26.9%, 24.4%, and 14.7%, respectively. Women aged 25-29 years accounted for most hospital admissions.

conclusionPreterm labor and delivery-related hospital admissions rates have significantly decreased over the past decade. Women in the reproductive age range of 25-34 years were more prone to hospital admission followed by preterm labor due to various reasons.

Indexed as

admissionsdeliveryEnglandhospitallaborpreterm

Identifiers

PMID36673531
PMCPMC9859329

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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.