Evidence map›Paper›PMID 39502134›Full record

ArticleInfection and drug resistance2024

Clinical Characteristics, Species Distribution, and Drug Resistance of Non-Tuberculous Mycobacteria Lung Disease in Qingdao, China.

Yan Chu, Xiaomin Wang, Min Dou, Jin Wang, Baoqian Wang, Hairong Wang, Shasha Lv, Shuihua Lu, Tongxia Li

Abstract read
In one paragraph

Article in Infection and drug resistance, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
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

2 citing papers in PubMed.

  1. Article
  2. Article
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

9 authors.

Yan Chu *Qingdao Chest Hospital, Qingdao, Shandong, People's Republic of China.
Xiaomin Wang *National Clinical Research Center for Infectious Diseases, Shenzhen Third People's Hospital, Shenzhen, Guangdong, People's Republic of China.
Min DouQingdao Chest Hospital, Qingdao, Shandong, People's Republic of China.
Jin WangNational Clinical Research Center for Infectious Diseases, Shenzhen Third People's Hospital, Shenzhen, Guangdong, People's Republic of China.
Baoqian WangQingdao Chest Hospital, Qingdao, Shandong, People's Republic of China.
Hairong WangQingdao Chest Hospital, Qingdao, Shandong, People's Republic of China.
Shasha LvQingdao Chest Hospital, Qingdao, Shandong, People's Republic of China.
Shuihua Lu *National Clinical Research Center for Infectious Diseases, Shenzhen Third People's Hospital, Shenzhen, Guangdong, People's Republic of China.
Tongxia Li *Qingdao Chest Hospital, Qingdao, Shandong, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To analyze the clinical characteristics, species distribution and drug resistance of patients with non-tuberculous mycobacteria (NTM) lung disease in Qingdao, China. Methods: Clinical data of patients with NTM lung disease and pulmonary tuberculosis (TB) treated at Qingdao Chest Hospital from July 2021 to July 2023 were retrospectively analyzed. Results: The prevalence of NTM lung disease was 8.03%, with a high rate of drug resistance during the study period. Patients with NTM lung disease had higher rates of older age, bronchiectasis, malignancy, HIV infection and bronchial dilatation shadow and lower rates of hollow shadow compared to patients with pulmonary TB. Conclusion: Comprehensive understanding of NTM lung disease, improved laboratory testing techniques and appropriate treatment regimens are essential for the management of NTM lung disease.

Indexed as

clinical characteristicsdrug resistancenon-tuberculous mycobacteriapulmonary tuberculosis

Identifiers

PMID39502134
PMCPMC11537159

What OpenQuestion holds

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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.