Evidence map›Paper›PMID 30745169›Full record

ArticleEBioMedicine2019

Integrating exosomal microRNAs and electronic health data improved tuberculosis diagnosis.

Xuejiao Hu, Shun Liao, Hao Bai, Lijuan Wu, Minjin Wang, Qian Wu, Juan Zhou, Lin Jiao, Xuerong Chen, Yanhong Zhou and 4 more

Open access · goldAbstract read
In one paragraph

Article in EBioMedicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed, 2 pooled it
3.4field-weighted citation impact, top 7% 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

45 citing papers in PubMed, 2 syntheses or guidelines pooled it, 78 citations in OpenAlex.

  1. Pooled it
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  12. Exosomal microRNAs associated with tuberculosis among people living with human immunodeficiency virus.Journal of clinical tuberculosis and other mycobacterial diseases · 2024
    Article
  13. Review
  14. Article
  15. Review
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  17. Lung Inflammation Signature in Post-COVID-19 TB Patients.International journal of molecular sciences · 2023
    Article
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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

14 authors at 2 institutions in 2 countries.

Xuejiao HuDepartment of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu 610041, China; The Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada.
Shun LiaoThe Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada; Department of Computer Science, University of Toronto, Toronto, ON, Canada.
Hao BaiDepartment of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu 610041, China.
Lijuan WuDepartment of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu 610041, China.
Minjin WangDepartment of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu 610041, China.
Qian WuDepartment of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu 610041, China.
Juan ZhouDepartment of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu 610041, China.
Lin JiaoDepartment of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu 610041, China.
Xuerong ChenDepartment of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu 610041, China.
Yanhong ZhouDepartment of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu 610041, China.
Xiaojun LuDepartment of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu 610041, China.
Binwu YingDepartment of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu 610041, China. Electronic address: docbwy@126.com.
Zhaolei ZhangThe Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada; Department of Computer Science, University of Toronto, Toronto, ON, Canada. Electronic address: zhaolei.zhang@utoronto.ca.
Weimin LiDepartment of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, Chengdu 610041, China. Electronic address: weimin003@163.com.
Sichuan University · CNUniversity of Toronto · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background Tuberculosis (TB) is difficult to diagnose under complex clinical conditions as electronic health records (EHRs) are often inadequate in making an affirmative diagnosis. As exosomal miRNAs emerged as promising biomarkers, we investigated the potential of using exosomal miRNAs and EHRs in TB diagnosis.

methodsA total of 370 individuals, including pulmonary tuberculosis (PTB), tuberculous meningitis (TBM), non-TB disease controls and healthy state controls, were enrolled. Exosomal miRNAs were profiled in the exploratory cohort using microarray and miRNA candidates were selected in the selection cohort using qRT-PCR. EHRs and follow-up information of the patients were collected accordingly. miRNAs and EHRs were used to develop diagnostic models for PTB and TBM in the selection cohort with the Support Vector Machine (SVM) algorithm. These models were further evaluated in an independent testing cohort.

findingsSix exosomal miRNAs (miR-20a, miR-20b, miR-26a, miR-106a, miR-191, miR-486) were differentially expressed in the TB patients. Three SVM models, "EHR+miRNA", "miRNA only" and "EHR only" were compared, and "EHR + miRNA" model achieved the highest diagnostic efficacy, with an AUC up to 0.97 (95% CI 0.80-0.99) in TBM and 0.97 (0.87-0.99) in PTB, respectively. However, "EHR only" model only showed an AUC of 0.67 (0.46-0.83) in TBM. After 2-month anti-tuberculosis therapy, overexpressed miRNAs presented a decreased expression trend (p= 4.80 × 10

interpretationOur results showed that the combination of exosomal miRNAs and EHRs could potentially improve clinical diagnosis of TBM and PTB. FUND: Funds for the Central Universities, the National Natural Science Foundation of China.

Indexed as

BiomarkersElectronic Health RecordsAdultCase-Control StudiesCell FractionationComputational BiologyExosomesFemaleGene Expression ProfilingHumansMaleMicroRNAsMiddle AgedPatient Care ManagementQuality ImprovementROC CurveBiomarkersMicroRNAsElectronic health recordExosomal miRNAMachine learningTuberculosis differential diagnosis

Identifiers

PMID30745169
PMCPMC6413343
OpenAlexW2913725813

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.