Evidence map›Paper›PMID 38347797›Full record

ArticleCurrent pharmaceutical biotechnology2024

Determination of Ideal Factors for Early Adoption and Standardization of Metagenomic Next-generation Sequencing for Respiratory System Infections.

Lei Zhao, Cole R Formslag, Qing Zhang, Braydon C Cowan, Trenton G Mayberry, Aaron R Barnhill, Yongsheng Wang, Yujiang Fang

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Article in Current pharmaceutical biotechnology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 97% of its field
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

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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

1 citing paper in PubMed, 0 citations in OpenAlex.

  1. Article
4 · The record

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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 at 3 institutions in 2 countries.

Lei ZhaoThe Department of Respiratory Medicine, the Second People's Hospital of Hefei and Hefei Second People's Hospital Affiliated to Bengbu Medical College, Hefei Hospital Affiliated to Anhui Medical University, Hefei, Anhui 230011, China.
Cole R FormslagDepartment of Microbiology, Immunology & Pathology, Des Moines University, Des Moines, IA, 50312, USA.
Qing ZhangThe Department of Respiratory Medicine, the Second People's Hospital of Hefei and Hefei Second People's Hospital Affiliated to Bengbu Medical College, Hefei Hospital Affiliated to Anhui Medical University, Hefei, Anhui 230011, China.
Braydon C CowanDepartment of Surgery, University of Missouri School of Medicine, Columbia, MO, 65212, USA.
Trenton G MayberryDepartment of Surgery, University of Missouri School of Medicine, Columbia, MO, 65212, USA.
Aaron R BarnhillDepartment of Surgery, University of Missouri School of Medicine, Columbia, MO, 65212, USA.
Yongsheng WangThe Department of Respiratory Medicine, the Second People's Hospital of Hefei and Hefei Second People's Hospital Affiliated to Bengbu Medical College, Hefei Hospital Affiliated to Anhui Medical University, Hefei, Anhui 230011, China.
Yujiang FangDepartment of Microbiology, Immunology & Pathology, Des Moines University, Des Moines, IA, 50312, USA.
Anhui Medical University · CNUniversity of Missouri · USDes Moines University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMetagenomic next-generation sequencing (mNGS) demonstrates great promise as a diagnostic tool for determining the cause of pathogenic infections. The standard diagnostic procedures (SDP) include smears and cultures and are typically viewed as less sensitive and more time-consuming when compared to mNGS. There are concerns about the logistics and ease of transition from SDP to mNGS. mNGS lacks standardization of collection processes, databases, and sequencing. Additionally, there is the burden of training clinicians on interpreting mNGS results.

objectiveUntil now, few studies have explored factors that could be used as early adoption candidates to ease the transition between SDP and mNGS. This study evaluated 123 patients who had received both SDP and mNGS and compared several variables across a diagnostic test evaluation.

methodsThe diagnostic test evaluation observed metrics such as sensitivity, specificity, positive and negative likelihood ratios (PLR, NLR), positive and negative predictive values (PPV, NPV), and accuracy. Factors included various sample sources such as bronchoalveolar lavage fluid (BALF), lung tissue, and cerebral spinal fluid (CSF). An additional factor observed was the patient's immune status.

resultsPathogen detection was found to be significantly greater for mNGS for total patients, BALF sample source, CSF sample source, and non-immunocompromised patients (p<0.05). Pathogen detection was found to be insignificant for lung tissue sample sources and immunocompromised patients. Sensitivity, PLR, NLR, PPV, NPV, and accuracy appeared to be higher with mNGS for the total patients, BALF sample source, and non-immunocompromised patients when compared with SDP (p<0.05).

conclusionWith higher metrics in sensitivity, specificity, PLR, NLR, PPV, NPV, and accuracy for overall patients, mNGS may prove a better diagnostic tool than SDP. When addressing sample sources, mNGS for BALF-collected samples appeared to have higher scores than SDP for the same metrics. When patients were in a non-immunocompromised state, mNGS also demonstrated greater diagnostic benefits to BALF and overall patients compared to SDP. This study demonstrates that using BALF as a sample source and selecting non-immunocompromised patients may prove beneficial as early adoption factors for mNGS standard protocol. Such a study may pave the road for mNGS as a routine clinical method for determining the exact pathogenic etiology of lung infections.

Indexed as

Bronchoalveolar Lavage FluidHigh-Throughput Nucleotide SequencingMetagenomicsRespiratory Tract InfectionsAdultAgedFemaleHumansMaleMiddle AgedSensitivity and Specificitybronchoalveolar lavage fluid (BALF)cereberal spinal fluid (CSF).data managementdiagnosisMetagenomic next-generation sequencing (mNGS)pulmonary infection

Identifiers

PMID38347797
OpenAlexW4391821161

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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.