Evidence map›Paper›PMID 37700800›Full record

ArticleInfection and drug resistance2023

Comparative Study on Tuberculosis Drug Resistance and Molecular Detection Methods Among Different Mycobacterium Tuberculosis Lineages.

Chuan-Jiang He, Jiang-Li Wan, Sheng-Fang Luo, Rui-Jie Guo, Pawuziye Paerhati, Xiang Cheng, Chao-Hui Duan, Ai-Min Xu

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Infection and drug resistance, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.0field-weighted citation impact, top 25% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Article
  3. The chosen few:Frontiers in immunology · 2024
    Review
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

8 authors at 3 institutions in 1 country.

Chuan-Jiang HeDepartment of Laboratory Medicine, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, People's Republic of China.
Jiang-Li WanDepartment of Laboratory Medicine, The First People's Hospital of Kashgar, Kashgar, 844000, People's Republic of China.
Sheng-Fang LuoDepartment of Laboratory Medicine, The First People's Hospital of Kashgar, Kashgar, 844000, People's Republic of China.
Rui-Jie GuoDepartment of Laboratory Medicine, The First People's Hospital of Kashgar, Kashgar, 844000, People's Republic of China.
Pawuziye PaerhatiDepartment of Laboratory Medicine, The First People's Hospital of Kashgar, Kashgar, 844000, People's Republic of China.
Xiang ChengDepartment of Laboratory Medicine, The First People's Hospital of Kashgar, Kashgar, 844000, People's Republic of China.
Chao-Hui Duan *Department of Laboratory Medicine, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, People's Republic of China.
Ai-Min Xu *Department of Laboratory Medicine, The First People's Hospital of Kashgar, Kashgar, 844000, People's Republic of China.
Kashi University · CNSun Yat-sen Memorial Hospital · CNSun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This study aims to compare drug resistance and detection efficacy across different Mycobacterium tuberculosis lineages, offering insights for precise treatment and molecular diagnosis. Methods: 161 strains of Mycobacterium tuberculosis ( Results: Among the 161 strains of Conclusion: There are significant differences in drug resistance rates among different lineages of

Indexed as

drug resistancelineageMycobacterium tuberculosissensitivityspecificitywhole-genome sequencing

Identifiers

PMID37700800
PMCPMC10494918
OpenAlexW4386506037

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.