Evidence map›Paper›PMID 42093770›Full record

ArticleFrontiers in cellular and infection microbiology2026

Clinical utility of metagenomic next-generation sequencing in the diagnosis of severe influenza complicated by invasive pulmonary aspergillosis.

Siqiang Niu, Limin Guo, Zhihai Li, Yanshan Liu, Limin Zhao

Abstract read
In one paragraph

Article in Frontiers in cellular and infection microbiology, 2026. 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

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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

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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

5 authors.

Siqiang NiuXinxiang Central Hospital, Xinxiang, Henan, China.
Limin GuoXinxiang Central Hospital, Xinxiang, Henan, China.
Zhihai LiXinxiang Central Hospital, Xinxiang, Henan, China.
Yanshan LiuXinxiang Central Hospital, Xinxiang, Henan, China.
Limin ZhaoDepartment of Respiratory and Critical Care Medicine, Henan Provincial People's Hospital, Zhengzhou, Henan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The incidence and mortality of severe influenza complicated by invasive pulmonary aspergillosis (IPA) have risen markedly in recent years. This study aimed to evaluate the diagnostic performance of metagenomic next-generation sequencing (mNGS) for detecting IPA in patients with severe influenza. Methods: Severe influenza patients with suspected of having IPA admitted to Xinxiang Central Hospital, Henan Province, China, from March 2020 to September 2025 were retrospectively enrolled. Bronchoalveolar lavage fluid (BALF) and blood were collected for fungal culture, galactomannan (GM) assay, and mNGS. Final classification into IPA and non-IPA groups was based on composite clinical and microbiological criteria. Sensitivity, specificity, and receiver operating characteristic curves were used to compare the diagnostic performance of the three methods. Results: Comparison with traditional fungal culture and GM testing, mNGS provided significantly faster results. Among 189 patients suspected of severe influenza-associated IPA, mNGS demonstrated a sensitivity of 72.1% and a specificity of 80.2%. Its sensitivity was higher than that of fungal culture (28.6%), serum GM testing (37.6%), and BALF GM testing (44.1%); however, its specificity was slightly lower than that of fungal culture (89.5%), serum GM testing (84.3%), and BALF GM testing (81.3%). The area under the ROC curve (AUC) for mNGS was 0.76, which is higher than that for BALF GM testing (0.63), serum GM testing (0.61), and fungal culture (0.59). The combined diagnostic approach yielded an AUC of 0.83. Conclusion: mNGS offers a rapid, sensitive and accurate solution for invasive pulmonary aspergillosis in severe influenza patients. It outperforms conventional fungal culture and galactomannan assays. Integrating mNGS with traditional diagnostic methods could substantially improve early detection and overall yield of IPA.

Indexed as

High-Throughput Nucleotide SequencingInfluenza, HumanInvasive Pulmonary AspergillosisMetagenomicsAdultAgedBronchoalveolar Lavage FluidChinaFemaleGalactoseHumansMaleMannansMiddle AgedRetrospective StudiesROC CurvegalactomannanGalactoseMannansdiagnosisGM testinfluenzainvasive pulmonary aspergillosismetagenomic next-generation sequencing

Identifiers

PMID42093770
PMCPMC13138931

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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.