Evidence map›Paper›PMID 33490156›Full record

ArticleAnnals of translational medicine2020

Application of next generation sequencing-based rapid detection platform for microbiological diagnosis and drug resistance prediction in acute lower respiratory infection.

Lingshan Chao, Jihong Li, Ya'nan Zhang, Hao Pu, Xixin Yan

Open access · diamondAbstract read
In one paragraph

Article in Annals of translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
2.0field-weighted citation impact, top 14% 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

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

19 citing papers in PubMed, 35 citations in OpenAlex.

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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 at 2 institutions in 1 country.

Lingshan ChaoDepartment of Respiratory and Critical Care Medicine, the Second Hospital of Hebei Medical University, Shijiazhuang, China.
Jihong LiDepartment of Laboratory Medicine, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Ya'nan ZhangDepartment of Science and Technology, Shanghai Pathogeno Medical Technology Co., Ltd., Shanghai, China.
Hao PuDepartment of Science and Technology, Shanghai Pathogeno Medical Technology Co., Ltd., Shanghai, China.
Xixin YanDepartment of Respiratory and Critical Care Medicine, the Second Hospital of Hebei Medical University, Shijiazhuang, China.
Hebei Medical University · CNSecond Hospital of Hebei Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAcute lower respiratory infections (ALRIs) have a high mortality rate. We aimed to apply a platform that rapidly detects 36 microorganisms and 49 antibiotic resistance markers in the clinical diagnosis of ALRI and drug resistance prediction.

methodsMulticenter collection of clinical samples from patients with ALRIs was carried out from 2017 to 2018. Sputum culture (SC) was performed, which provided two outcomes: the detected pathogens and the resistance to different antibiotics. Additionally, each sputum sample was used to extract deoxyribonucleic acids (DNAs) followed by high-throughput sequencing.

resultsEleven commonly observed pathogens were surveyed, and for all samples with positive SC results (137 cases), the overall coverage was 95.62% according to the sequencing results. The receiver operating characteristic (ROC) curve was drawn, and cutoff reads of the most frequently detected pathogens were acquired. Overall, sequencing exhibited significantly higher sensitivity in the detection of pathogens compared with the traditional SC method, with a generally satisfactory specificity. Furthermore, we investigated the correlation between antibiotic resistance gene phenotypes and the actual outcomes of the drug sensitivity test, and some significant correlations were found, especially for the resistance to Amikacin in the presence of

conclusionsSequencing-based sputum metagenomics can reveal a profile of the lung pathogen microbiome. The sequencing method offers both sufficient accuracy and significantly higher sensitivity in the detection of pathogens, and can be at least a complementary approach to traditional SC reporting. The sequencing technique also revealed some novel potential correlations between the presence of different pathogens, as well as new antimicrobial-resistant genes.

Indexed as

Acute lower respiratory infection (ALRI)antibioticdrug resistancemicroorganismsnext generation sequencing (NGS)

Identifiers

PMID33490156
PMCPMC7812213
OpenAlexW3111460342

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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 OpenQuestion graph.