Evidence map›Paper›PMID 40442233›Full record

ArticleScientific reports2025

Characteristics of SARS-CoV-2 variants and potential co-infected pathogens in hospitalized patients based on metagenomic next-generation sequencing.

Xinxin Li, Chenyue Tang, Min Zhou, Jianqing Mi, Jialin Liu, Lizhong Han, Xiaoqi Yu, Xinxin Zhang

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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. Article
  2. NK Cells: A Powerful Squad Versus SARS-CoV-2.International journal of molecular sciences · 2025
    Review
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

8 authors.

Xinxin Li *Department of Infectious Diseases, Research Laboratory of Clinical Virology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No.197 Ruijin 2nd Road, Shanghai, 200025, China.
Chenyue Tang *Department of Infectious Diseases, Research Laboratory of Clinical Virology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No.197 Ruijin 2nd Road, Shanghai, 200025, China.
Min ZhouDepartment of Pulmonary and Critical Care Medcine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Jianqing MiShanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shangha, China.
Jialin LiuDepartment of Geriatrics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Lizhong HanDepartment of Laboratory Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Xiaoqi YuDepartment of Infectious Diseases, Research Laboratory of Clinical Virology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No.197 Ruijin 2nd Road, Shanghai, 200025, China. yuxiaoqi_03@163.com.
Xinxin ZhangDepartment of Infectious Diseases, Research Laboratory of Clinical Virology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, No.197 Ruijin 2nd Road, Shanghai, 200025, China. zhangx@shsmu.edu.cn.

Funding

National Key Research and Development Program of China 2024YFC3044400Shanghai Municipal Science and Technology Major Project ZD2021CY001Shanghai Targeted Biomedical Emergency Project 23DX1900300
6 · The paper itself

Abstract

Metagenomic next-generation sequencing (mNGS) is widely used to diagnose complex infections in hospitalized patients, particularly those associated with COVID-19 which has garnered significant concern over the past five years. To investigate the molecular epidemic of the viral variant and the potential co-infection pathogens, we conducted retrospective mNGS analysis of 254 SARS-CoV-2-positive specimens collected from 200 hospitalized patients between March and September 2023. Phylogenetic analysis of the identified Omicron subvariants showed minimal evolutionary divergence, with no association between sub-lineages and pneumonia severity. Notably, mNGS demonstrated enhanced detection of polymicrobial coinfections, identifying bacterial, fungal, and viral co-pathogens in 92.5% (185/200) of cases. Pneumonia severity was associated with advanced age (proportion of elderly patients: 61.1 vs 78.3%; p = 0.032) and comorbid conditions, particularly diabetes mellitus (OR 2.03, 95% CI 1.03-4.02, p = 0.041), but showed no correlation with SARS-CoV-2 sub-lineages or coinfecting pathogens. While mNGS enhances coinfection diagnosis, COVID-19 outcomes are predominantly driven by host factors rather than Omicron subvariant evolution. Prioritized monitoring of elderly and comorbid individuals remained critical for severe pneumonia management.

Indexed as

CoinfectionCOVID-19SARS-CoV-2AdultAgedAged, 80 and overFemaleHigh-Throughput Nucleotide SequencingHospitalizationHumansMaleMetagenomicsMiddle AgedPhylogenyRetrospective StudiesCo-infectionCOVID-19Metagenomic next-generation sequencing (mNGS)Severe pneumonia (SP)

Identifiers

PMID40442233
PMCPMC12122725

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.