Evidence map›Paper›PMID 41048203›Full record

ArticleInfection and drug resistance2025

Correlation Between Xpert MTB/RIF Results and

Kun Li, Long Li

Abstract read
In one paragraph

Article in Infection and drug resistance, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

Kun Li *Department of Clinical Laboratory Medicine, Suining Central Hospital, Suining, Sichuan, People's Republic of China.ORCID 0009-0000-6270-735X
Long Li *Department of Clinical Laboratory Medicine, Suining Central Hospital, Suining, Sichuan, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This study characterized mutation patterns within the rifampicin resistance-determining region (RRDR) of the Methods: We conducted a retrospective study of 197 rifampicin-resistant tuberculosis cases involving 197 cases of rifampicin-resistant tuberculosis (comprising 194 pulmonary and 3 extrapulmonary cases) confirmed through the GeneXpert MTB/RIF assay at Suining Central Hospital during 2023-2024. Mutation characteristics across five RRDR probes (labeled A-E) were assessed, along with the semi-quantitative classification of bacterial loads. Results: Single-probe mutations predominated (82.7%; 163/197), with hotspots at Probe E (S531L, 55.8%) and Probe A (Q510H/V511D, 12.2%). Dual-probe mutations (16.8%, 33/197) were primarily A+B combinations (13.7%, 27/197), showing significantly elevated prevalence in patients aged 46-60 years (OR = 2.31, 95% CI: 1.12-4.79, P< 0.05). Bacterial load stratification revealed strong diagnostic accuracy associations: smear positivity rates were 79.4% (high load) and 44.4% (medium), while culture positivity rates were 67.6% and 57.8%, respectively. Conclusion: A unique double-peak mutation pattern (primarily involving probes E and A) was identified in Sichuan Province, which contrasts sharply with the single hotspot pattern observed in Europe and the epidemiological pattern in Beijing, China, where probe E predominates. The elevated Probe A mutation rate (12.2%) potentially reflects regional rifabutin usage in second-line regimens. These findings provide molecular epidemiological insights for optimizing diagnosis and drug resistance monitoring in southwestern China.

Indexed as

drug resistanceMycobacterium tuberculosisrpoB gene

Identifiers

PMID41048203
PMCPMC12493105

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.