Evidence map›Paper›PMID 35411157›Full record

ArticleInfection and drug resistance2022

Clinical Value of Metagenomics Next-Generation Sequencing in Bronchoalveolar Lavage Fluid for Patients with Severe Hospital-Acquired Pneumonia: A Nested Case-Control Study.

Tianjun Yang, Qing Mei, Xiaowei Fang, Shoujun Zhu, Yinzhong Wang, Wanli Li, Aijun Pan

Open access · goldAbstract read
In one paragraph

Article in Infection and drug resistance, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
6.2field-weighted citation impact, top 3% 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

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 41 citations in OpenAlex.

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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

7 authors at 1 institution in 1 country.

Tianjun Yang *Department of Intensive Care Unit, The First Affiliated Hospital of USTC, Division of Life Science and Medicine, University of Science and Technology of China, Hefei, Anhui Province, 230001, People's Republic of China.
Qing Mei *Department of Intensive Care Unit, The First Affiliated Hospital of USTC, Division of Life Science and Medicine, University of Science and Technology of China, Hefei, Anhui Province, 230001, People's Republic of China.ORCID 0000-0001-9087-9642
Xiaowei FangDepartment of Intensive Care Unit, The First Affiliated Hospital of USTC, Division of Life Science and Medicine, University of Science and Technology of China, Hefei, Anhui Province, 230001, People's Republic of China.
Shoujun ZhuDepartment of Intensive Care Unit, The First Affiliated Hospital of USTC, Division of Life Science and Medicine, University of Science and Technology of China, Hefei, Anhui Province, 230001, People's Republic of China.
Yinzhong WangDepartment of Intensive Care Unit, The First Affiliated Hospital of USTC, Division of Life Science and Medicine, University of Science and Technology of China, Hefei, Anhui Province, 230001, People's Republic of China.
Wanli LiDepartment of Intensive Care Unit, The First Affiliated Hospital of USTC, Division of Life Science and Medicine, University of Science and Technology of China, Hefei, Anhui Province, 230001, People's Republic of China.
Aijun PanDepartment of Intensive Care Unit, The First Affiliated Hospital of USTC, Division of Life Science and Medicine, University of Science and Technology of China, Hefei, Anhui Province, 230001, People's Republic of China.
University of Science and Technology of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Metagenomics next-generation sequencing (mNGS) is more efficient in identifying pathogens responsible for pneumonia. However, whether these patients ultimately benefit from this improvement remains unknown. Methods: In this retrospective, nested, case-control study, patients with severe hospital-acquired pneumonia (HAP) who had undergone mNGS of bronchoalveolar lavage fluid while in our intensive care unit from March 2017 to December 2020 (n = 33) were matched in a ratio of 1 to 2 (n = 66) by sex, age, comorbidities, immune status, Acute Physiology and Chronic Health Evaluation II score, severity of pulmonary infection, and use of extracorporeal life support with patients who had undergone conventional microbiological testing only. The primary outcome was 90-day mortality; secondary outcomes being length of intensive care unit stay, duration of mechanical ventilation support, 7-day and 28-day mortality, and efficacy of treatment of pulmonary infection. Results: In the CMT group, 17 patients (25.8%) had negative results, whereas only one (3.0%) had negative results in the mNGS group (P < 0.001). After receipt of microbiology results, antibiotics were altered in 23/33 patients (70.0%) in the mNGS group, but in only 29/66 (43.9%) in the CMT group (P = 0.016). Pulmonary infection-related findings improved in 20/33 patients (60.6%) in the mNGS group in the subsequent 7 days, but in only 25/66 (37.9%) in the CMT group (P = 0.032). However, the 28-day (33.3% vs 31.2%, P = 1.0) and 90-day (48.5% vs 45.5%, P = 0.78) mortality rates did not differ significantly between the two groups. These findings were supported by Cox-regression and Kaplan-Meier survival curve analyses. Conclusion: mNGS is helpful in the treatment of severe HAP but does not improve medium or long-term survival rates, especially in patients with severe comorbidities.

Indexed as

bronchoalveolar lavage fluidmortalitynext generation sequencingpathogenic microbessevere hospital-acquired pneumonia

Identifiers

PMID35411157
PMCPMC8994607
OpenAlexW4225876158

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.