Clinical Evaluation of Metagenomic Next-Generation Sequencing and Identification of Risk Factors in Patients with Severe Community-Acquired Pneumonia

Lu, Dongmei; Abudouaini, Maidina; Kerimu, Munire; Leng, Qiuping; Wu, Hongtao; Aynazar, Amar; Zhong, Zhiwei

doi:10.2147/idr.s421721

Cited by 4 publications

(1 citation statement)

References 37 publications

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“…Particularly in the advanced phase of the COVID-19 pandemic and the escalating severity of antibiotic resistance, mixed respiratory infections are gaining increased attention. MNGS has the potential to enhance prognostic capabilities [ 62 ]. As mNGS technology becomes progressively integrated into various expert consensuses, clinicians continue to consolidate methods for the rational application of mNGS technology.…”

Section: Discussionmentioning

confidence: 99%

A single-center, retrospective study of hospitalized patients with lower respiratory tract infections: clinical assessment of metagenomic next-generation sequencing and identification of risk factors in patients

Gao,

Li,

et al. 2024

Respir Res

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Introduction Lower respiratory tract infections(LRTIs) in adults are complicated by diverse pathogens that challenge traditional detection methods, which are often slow and insensitive. Metagenomic next-generation sequencing (mNGS) offers a comprehensive, high-throughput, and unbiased approach to pathogen identification. This retrospective study evaluates the diagnostic efficacy of mNGS compared to conventional microbiological testing (CMT) in LRTIs, aiming to enhance detection accuracy and enable early clinical prediction. Methods In our retrospective single-center analysis, 451 patients with suspected LRTIs underwent mNGS testing from July 2020 to July 2023. We assessed the pathogen spectrum and compared the diagnostic efficacy of mNGS to CMT, with clinical comprehensive diagnosis serving as the reference standard. The study analyzed mNGS performance in lung tissue biopsies and bronchoalveolar lavage fluid (BALF) from cases suspected of lung infection. Patients were stratified into two groups based on clinical outcomes (improvement or mortality), and we compared clinical data and conventional laboratory indices between groups. A predictive model and nomogram for the prognosis of LRTIs were constructed using univariate followed by multivariate logistic regression, with model predictive accuracy evaluated by the area under the ROC curve (AUC). Results (1) Comparative Analysis of mNGS versus CMT: In a comprehensive analysis of 510 specimens, where 59 cases were concurrently collected from lung tissue biopsies and BALF, the study highlights the diagnostic superiority of mNGS over CMT. Specifically, mNGS demonstrated significantly higher sensitivity and specificity in BALF samples (82.86% vs. 44.42% and 52.00% vs. 21.05%, respectively, p < 0.001) alongside greater positive and negative predictive values (96.71% vs. 79.55% and 15.12% vs. 5.19%, respectively, p < 0.01). Additionally, when comparing simultaneous testing of lung tissue biopsies and BALF, mNGS showed enhanced sensitivity in BALF (84.21% vs. 57.41%), whereas lung tissues offered higher specificity (80.00% vs. 50.00%). (2) Analysis of Infectious Species in Patients from This Study: The study also notes a concerning incidence of lung abscesses and identifies Epstein-Barr virus (EBV), Fusobacterium nucleatum, Mycoplasma pneumoniae, Chlamydia psittaci, and Haemophilus influenzae as the most common pathogens, with Klebsiella pneumoniae emerging as the predominant bacterial culprit. Among herpes viruses, EBV and herpes virus 7 (HHV-7) were most frequently detected, with HHV-7 more prevalent in immunocompromised individuals. (3) Risk Factors for Adverse Prognosis and a Mortality Risk Prediction Model in Patients with LRTIs: We identified key risk factors for poor prognosis in lower respiratory tract infection patients, with significant findings including delayed time to mNGS testing, low lymphocyte percentage, presence of chronic lung disease, multiple comorbidities, false-negative CMT results, and positive herpesvirus affecting patient outcomes. We also developed a nomogram model with good consistency and high accuracy (AUC of 0.825) for predicting mortality risk in these patients, offering a valuable clinical tool for assessing prognosis. Conclusion The study underscores mNGS as a superior tool for lower respiratory tract infection diagnosis, exhibiting higher sensitivity and specificity than traditional methods.

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Section: Discussionmentioning

confidence: 99%

A single-center, retrospective study of hospitalized patients with lower respiratory tract infections: clinical assessment of metagenomic next-generation sequencing and identification of risk factors in patients

Gao,

Li,

et al. 2024

Respir Res

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Application of targeted next-generation sequencing to identify pathogens in the bronchoalveolar lavage fluid of adults with pulmonary infections

He,

Wu,

Liang

et al. 2024

Preprint

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Background Targeted next-generation sequencing (tNGS) has emerged as an efficient diagnostic method for pathogens identification. herein, we aimed to evaluate its performance in pathogen detection in bronchoalveolar lavage fluid (BALF). Methods BALF samples were obtained from 262 adult patients with pulmonary infection and were detected by tNGS, microbial culture, Xpert® MTB/RIF assay, and Aspergillus galactomannan (GM) test. Results In total, 47 potential pathogens were identified in the BALF samples by tNGS, including 21 bacteria, 13 viruses, 11 fungi, 1 parasite, and 1 mycoplasma. The bacterial detection rates of tNGS and ordinary bacterial culture were 74.0% (194/262) and 28.2% (74/262), respectively. The rates of negative, positive, and total consistent and the kappa value between tNGS and bacterial culture were 30.8%, 86.4%, 46.4%, and 0.116, respectively. The positive rate of fungal identification by tNGS was slightly higher than that of fungal culture (31.7% (83/262) and 22.9% (60/262), respectively). The rates of positive, negative, and total consistent and the kappa value between tNGS and fungal culture were 68.9%, 79.1%, 76.7%, and 0.424, respectively. Among the 42 patients with suspected tuberculosis infection, 23 patients showed positive results on both tNGS and Xpert® MTB/RIF assay. The rates of positive, negative, and total consistent and the kappa value between tNGS and pert® MTB/RIF assay were 100.0%, 68.4%, 85.7%, and 0.704, respectively. Finally, the sensitivity and specificity of tNGS versus the GM test were 57.1% and 90.6% versus 71.4% and 82.7%, respectively, when the fungal culture was used as the gold standard for detecting Aspergillus. Additionally, the sensitivity and specificity of tNGS increased to 86.2% and 98.7%, whereas the sensitivity of the GM test decreased to 69.0% when clinically diagnosed Aspergillus infection was used as a reference standard. The read counts of Aspergillus detected by tNGS and the optical density of the GM test were not significantly correlated. Conclusions tNGS is a promising method for detecting pathogens in BALF with a notably higher positive detection rate and a higher sensitivity and/or specificity compared with those of the conventional test.

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Clinical Application of Metagenomic Next-Generation Sequencing in Sepsis Patients with Early Antibiotic Treatment

Chen,

Chen

et al. 2024

IDR

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Purpose This study aimed to evaluate the clinical utility of metagenomic next-generation sequencing (mNGS) in sepsis patients who received early empirical antibiotic treatment. Patients and Methods A retrospective analysis was conducted on clinical data from sepsis patients diagnosed in the Emergency Intensive Care Unit (EICU) between April 2019 and May 2023. All patients underwent standard conventional microbiological testing. Patients were categorized into either the mNGS group or the control group based on whether they underwent mNGS tests. Baseline variables were matched using propensity scores. Results Out of 461 sepsis patients screened, 130 were included after propensity matching, with 65 patients in each group. Despite prior antibiotic treatment, 57 cases (87.69%) in the mNGS group had positive mNGS results, exceeding the culture detection rate (52.31%). Besides, a higher proportion of patients in the mNGS group experienced antibiotic adjustments compared to the control group (72.31% vs 53.85%). Mortality rates were also compared based on the duration of antibiotic exposure before mNGS sampling. Patients exposed to antibiotics for less than 24 hours had a lower mortality rate compared to those exposed for over 8 days (22.22% vs 42.86%). COX multivariate analysis identified mNGS testing, underlying diseases, lymphocyte percentage, infection site (respiratory and bloodstream) as independent risk factors for mortality in sepsis patients. Conclusion With increased antibiotic exposure time, the positive rate of culture testing significantly decreased (44.44% vs 59.52% vs 35.71%, P = 0.031), whereas the positive rate of mNGS remained stable (77.78% vs 88.10% vs 92.86%, P = 0.557). mNGS demonstrated less susceptibility to antibiotic exposure. Early mNGS detection positively impacted the prognosis of sepsis patients.

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Clinical Evaluation of Metagenomic Next-Generation Sequencing and Identification of Risk Factors in Patients with Severe Community-Acquired Pneumonia

Cited by 4 publications

References 37 publications

A single-center, retrospective study of hospitalized patients with lower respiratory tract infections: clinical assessment of metagenomic next-generation sequencing and identification of risk factors in patients

A single-center, retrospective study of hospitalized patients with lower respiratory tract infections: clinical assessment of metagenomic next-generation sequencing and identification of risk factors in patients

Application of targeted next-generation sequencing to identify pathogens in the bronchoalveolar lavage fluid of adults with pulmonary infections

Clinical Application of Metagenomic Next-Generation Sequencing in Sepsis Patients with Early Antibiotic Treatment

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