Evidence map›Paper›PMID 37803320›Full record

ArticleBMC anesthesiology2023

Atrial fibrillation is not an independent determinant of 28-day mortality among critically III sepsis patients.

Weiping Wang, Yujiang Dong, Qian Zhang, Hongmei Gao

Abstract read
In one paragraph

Article in BMC anesthesiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Article
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

4 authors.

Weiping WangDepartment of Cardiology, Sunshine Union Hospital, Weifang, 261072, Shandong , China.
Yujiang DongDepartment of Cardiology, The Second Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, 250001, Shandong, China.
Qian ZhangShandong University of Traditional Chinese Medicine, Jinan, 250014, Shandong, China.
Hongmei GaoDepartment of Cardiology, The Second Affiliated Hospital of Shandong University of Traditional Chinese Medicine, Jinan, 250001, Shandong, China. gaohongmeia@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study was conducted to investigate the relationship between atrial fibrillation and the clinical prognosis of patients with sepsis in intensive care unit. A total of 21,538 sepsis patients were enrolled in the study based on the Medical Information Mart for Intensive Care IV database, of whom 6,759 had AF. Propensity score matching was used to compare the clinical characteristics and outcomes of patients with and without AF. Besides, the inverse probability of treatment weighting, univariate and multivariate Cox regression analyzes were performed. Of the 21,538 patients, 31.4% had AF. The prevalence of AF increased in a step-by-step manner with growing age. Patients with AF were older than those without AF. After PSM, 11,180 patients remained, comprising 5,790 matched pairs in both groups. In IPTW, AF was not associated with 28-day mortality [hazard ratio (HR), 1.07; 95% confidence interval (CI), 0.99-1.15]. In Kaplan-Meier analysis, it was not observed difference of 28-day mortality between patients with and without AF. AF could be associated with increased ICU LOS, hospital LOS and need for mechanical ventilation; however, it does not remain an independent short-term predictor of 28-day mortality among patients with sepsis after PSM with IPTW and multivariate analysis.

Indexed as

Atrial FibrillationHospital MortalitySepsisHumansIntensive Care UnitsLongitudinal StudiesPrognosisRespiration, ArtificialRetrospective StudiesAtrial fibrillationMedical Information Mart for Intensive Care IV databasePropensity score matchingSepsis

Identifiers

PMID37803320
PMCPMC10557240

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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.