Evidence map›Paper›PMID 39866262›Full record

ArticleAME case reports2025

Case report: co-infection of

Chengying Liu, Weiwei Wu, Lan Wang, Jie Li

Abstract readCase Reports
In one paragraph

Article in AME case reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Chengying LiuDivision of Respiratory and Critical Care Medicine, Jiangyin People's Hospital Affiliated to Nantong, Jiangyin, China.
Weiwei WuDinfectome Inc., Nanjing, China.
Lan WangDivision of Respiratory and Critical Care Medicine, Jiangyin People's Hospital Affiliated to Nantong, Jiangyin, China.
Jie LiDivision of Respiratory and Critical Care Medicine, Jiangyin People's Hospital Affiliated to Nantong, Jiangyin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: There are hundreds of pathogens that cause lung infections. Compared to infections caused by a single pathogen, mixed infections account for a larger proportion of pulmonary infections and have a more severe clinical presentation, while treatment options differ between the two. We aimed to explore the advantages of metagenomic next-generation sequencing (mNGS) in the diagnosis and treatment of mixed infections. Case Description: To investigate the specific pathogens in a 79-year-old male pneumonia patient who had recurrent cough with poor empirical treatment, we collected bronchoalveolar lavage fluid (BALF) from the patient and performed mNGS technology, along with Sanger sequencing and polymerase chain reaction (PCR) was carried out to confirm the authenticity of the pathogens detected by mNGS. The findings showed that rare pathogen Conclusions: mNGS, a non-targeted sequencing technology, could improve the efficiency of clinical diagnosis for mixed infection of rare or atypical pathogens, bring new ideas for clinical pathogen diagnosis, and improve patient prognosis.

Indexed as

case reportmetagenomic next-generation sequencing (mNGS)Mycobacterium avium complex (MAC)pulmonary mixed infectionScedosporium boydii (S. boydii)

Identifiers

PMID39866262
PMCPMC11760516

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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.