Evidence map›Paper›PMID 40970726›Full record

ArticleMicrobiology spectrum2025

Lower airway microbiota compositions and diversity among ventilator-associated pneumonia patients across COVID-19 epidemic phases: a retrospective study.

Shengyu Hao, Chujun Zhou, Yilin Wei, Yuxian Wang, Pan Jiang, Jieqiong Song, Ming Zhong

Abstract read
In one paragraph

Article in Microbiology spectrum, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

7 authors.

Shengyu Hao *Department of Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.
Chujun Zhou *Department of Critical Care Medicine, Shanghai Geriatric Medical Center, Shanghai, China.
Yilin Wei *Department of Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.
Yuxian WangDepartment of Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.
Pan JiangNutrition Department, Zhongshan Hospital, Fudan University, Shanghai, China.ORCID 0009-0007-8981-5765
Jieqiong SongDepartment of Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.ORCID 0000-0002-3445-8795
Ming ZhongDepartment of Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.ORCID 0009-0005-5954-7195

Funding

National Science Fund for Young Scholar 82200061Shanghai Sailing Program 21YF1440300, 22YF1407700Three-Year Action Plan for Strengthening the Public Health System in Shanghai GWVI-11.1-14
6 · The paper itself

Abstract

Ventilator-associated pneumonia (VAP) is a major cause of morbidity in critically ill patients, and the SARS-CoV-2 infection has influenced the lung microbiome. This study aimed to examine the lower respiratory tract microbiome in VAP patients during different phases of the Shanghai COVID-19 epidemic. A total of 175 patients were included and divided into pre-epidemic (Pre), during-epidemic (Dur), and post-epidemic (Post) groups for analysis. Bronchoalveolar lavage fluid and serum were analyzed using next-generation sequencing. The intensive care unit (ICU) mortality rates were 48.3% (Pre group), 60.3% (Dur group), and 28.8% (Post group). Cytokine levels were lower in the Post group compared to the Pre group.

Indexed as

COVID-19LungMicrobiotaPneumonia, Ventilator-AssociatedAdultAgedBacteriaBronchoalveolar Lavage FluidChinaFemaleHumansIntensive Care UnitsMaleMiddle AgedRetrospective StudiesSARS-CoV-2COVID-19microbiomenext-generation sequencing technologyspecies richnessventilator-associated pneumonia

Identifiers

PMID40970726
PMCPMC12584767

What OpenQuestion holds

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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.