ArticleBMC pulmonary medicine2023
Metagenomic next-generation sequencing for pulmonary infections diagnosis in patients with diabetes.
Article in BMC pulmonary medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 4 citations in OpenAlex.
- Consistency between metagenomic next-generation sequencing versus traditional microbiological tests for infective disease: systemic review and meta-analysis.Critical care (London, England) · 2025Pooled it
- Metagenomic next-generation sequencing contributes to the diagnosis ofBiomedical reports · 2026Article
- Pathogens and clinical characteristics of type 2 diabetes mellitus in patients with community-acquired pneumonia via bronchoalveolar lavage fluid (BALF) metagenomic next-generation sequencing: a comparative observational study.Journal of thoracic disease · 2026Article
- Metagenomic next-generation sequencing for the diagnosis of invasive pulmonary aspergillosis in type 2 diabetes mellitus patients.Scientific reports · 2024Article
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundDiabetes mellitus is a major cause of high mortality and poor prognosis in patients with pulmonary infections. However, limited data on the application of metagenomic next-generation sequencing (mNGS) are available for diabetic patients. This study aimed to evaluate the diagnostic performance of mNGS in diabetic patients with pulmonary infections.
methodsWe retrospectively reviewed 184 hospitalized patients with pulmonary infections at Guizhou Provincial People's Hospital between January 2020 to October 2021. All patients were subjected to both mNGS analysis of bronchoalveolar lavage fluid (BALF) and conventional testing. Positive rate by mNGS and the consistency between mNGS and conventional testing results were evaluated for diabetic and non-diabetic patients.
resultsA total of 184 patients with pulmonary infections were enrolled, including 43 diabetic patients and 141 non-diabetic patients. For diabetic patients, the microbial positive rate by mNGS was significantly higher than that detected by conventional testing methods, primarily driven by bacterial detection (microbes: 95.3% vs. 67.4%, P = 0.001; bacteria: 72.1% vs. 37.2%, P = 0.001). mNGS and traditional tests had similar positive rates with regard to fungal and viral detection in diabetic patients. Klebsiella pneumoniae was the most common pathogen identified by mNGS in patients with diabetes. Moreover, mNGS identified pathogens in 92.9% (13/14) of diabetic patients who were reported negative by conventional testing. No significant difference was found in the consistency of the two tests between diabetic and non-diabetic groups.
conclusionsmNGS is superior to conventional microbiological tests for bacterial detection in diabetic patients with pulmonary infections. mNGS is a valuable tool for etiological diagnosis of pulmonary infections in diabetic patients.
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