Evidence map›Paper›PMID 41948600›Full record

ArticleInfection and drug resistance2026

Species Distribution and Antimicrobial Susceptibility Profiles of Non-Tuberculous Mycobacteria in Nanjing, Jiangsu Province, China: A Three-Year Retrospective Study.

Xingyu Liu, Tianzhen Wang, Yicheng Guo, Yi Zeng, Weiwei Gao

Abstract read
In one paragraph

Article in Infection and drug resistance, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Xingyu Liu *Department of Tuberculosis, The Second Hospital of Nanjing, Affiliated to Nanjing University of Chinese Medicine, Nanjing, 211100, People's Republic of China.
Tianzhen Wang *Department of Tuberculosis, The Second Hospital of Nanjing, Affiliated to Nanjing University of Chinese Medicine, Nanjing, 211100, People's Republic of China.
Yicheng GuoDepartment of Tuberculosis, The School of Public Health of Nanjing Medical University, The Second Hospital of Nanjing, Nanjing, 211166, People's Republic of China.
Yi Zeng *Department of Tuberculosis, The Second Hospital of Nanjing, Affiliated to Nanjing University of Chinese Medicine, Nanjing, 211100, People's Republic of China.
Weiwei Gao *Department of Tuberculosis, The Second Hospital of Nanjing, Affiliated to Nanjing University of Chinese Medicine, Nanjing, 211100, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Non-tuberculous mycobacteria (NTM) are emerging pathogens with increasing clinical significance worldwide, yet regional epidemiological and drug susceptibility data remain limited. The purpose of this study is to analyze the distribution, demographic characteristics, and drug susceptibility of NTM infections in Nanjing, and to provide a basis for clinical diagnosis and treatment. Patients and Methods: Confirmed cases of NTM infection were collected from the Tuberculosis Department of Nanjing Second Hospital between January 2023 and November 2025. Clinical isolates were cultured using the BACTEC MGIT960 system. Results: Among 249 cases of NTM detected, the most common bacterial strains are Conclusion: This study reveals distribution of NTM species in Nanjing Jiangsu Province China and distinct antimicrobial susceptibility profiles between single and mixed NTM infections, highlighting the clinical complexity of NTM disease, reinforce the necessity of species-level identification and antimicrobial susceptibility testing to guide individualized treatment and address the growing challenge of antimicrobial resistance in clinical practice.

Indexed as

antimicrobial resistanceantimicrobial susceptibilityMICminimum inhibitory concentrationNTM mixed infection

Identifiers

PMID41948600
PMCPMC13051360

What Socratic holds

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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 Socratic graph.