Evidence map›Paper›PMID 38303958›Full record

SynthesisFrontiers in public health2023

Weekend admissions and outcomes in patients with pneumonia: a systematic review and meta-analysis.

Jiayao Lu, Jing Yang, Xiaofei Cai

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Frontiers in public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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.

Jiayao LuDepartment of 12 Ward, Huzhou Third Municipal Hospital, The Affiliated Hospital of Huzhou University, Zhejiang, Huzhou, China.
Jing YangDepartment of 12 Ward, Huzhou Third Municipal Hospital, The Affiliated Hospital of Huzhou University, Zhejiang, Huzhou, China.
Xiaofei CaiDepartment of 12 Ward, Huzhou Third Municipal Hospital, The Affiliated Hospital of Huzhou University, Zhejiang, Huzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: To document pooled evidence on the association between weekend hospital admissions and the potential risks of mortality, intensive care requirements, and readmission among patients with pneumonia. Methods: We performed a systematic search across the PubMed, EMBASE, and Scopus databases. We collected observational studies exploring the association between weekend admissions and outcomes of interest in patients with pneumonia. To analyze the data, we used a random effects model and expressed the effect sizes as pooled odds ratios (ORs) accompanied by their respective 95% confidence intervals (CIs). Results: The analysis comprised data from 13 retrospective studies. Compared to patients admitted on weekdays, those admitted during the weekend had a non-statistically significant marginally higher risk of in-hospital mortality (OR, 1.02; 95% CI, 1.00, 1.04) but similar 30-day mortality after admission (OR, 1.03; 95% CI, 0.97, 1.10), and similar risks of admission to intensive care unit (OR, 1.04; 95% CI, 0.98, 1.11) and re-admission (OR, 0.85; 95% CI, 0.65-1.12). Conclusion: Our findings do not support the presence of a "weekend effect" in patients with pneumonia. Systematic review registration: PROSPERO, identifier CRD42023425802, https://www.crd.york.ac.uk/prospero/.

Indexed as

HospitalizationPneumoniaHospital MortalityHumansRetrospective StudiesTime Factorsintensive caremeta-analysismortalitypneumoniareadmissionsystematic reviewweekend effect

Identifiers

PMID38303958
PMCPMC10832039

What OpenQuestion holds

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LicenceCC BY
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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.