Evidence map›Paper›PMID 42245749›Full record

ArticleInfection and drug resistance2026

A QuantiFERON

Jiajun Zhou, Xiaoqing Lin, Yuhui Yu, Yiyang Zhang, Liufeng Qiu, Zhiruo Lin, Xiangao Jiang, Jichan Shi

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
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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

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

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

8 authors.

Jiajun ZhouDepartment of Infectious Disease, The Wenzhou Central Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, People's Republic of China.
Xiaoqing LinDepartment of Infectious Disease, The Wenzhou Central Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, People's Republic of China.
Yuhui YuDepartment of Endocrinology, The Wenzhou Central Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, People's Republic of China.
Yiyang ZhangThe Wenzhou Central Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, People's Republic of China.
Liufeng QiuThe Wenzhou Central Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, People's Republic of China.
Zhiruo LinThe Wenzhou Central Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, People's Republic of China.
Xiangao JiangDepartment of Infectious Disease, The Wenzhou Central Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, People's Republic of China.
Jichan ShiDepartment of Infectious Disease, The Wenzhou Central Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Diabetes mellitus (DM) is a well-established independent risk factor for tuberculosis (TB), and the prevalence of latent tuberculosis infection (LTBI) among patients with DM remains a critical public health concern. This study aims to investigate the prevalence and predictive factors of LTBI in patients with DM using the QuantiFERON Methods: A cross-sectional study was conducted involving 195 participants (96 with DM and 99 healthy controls) at Wenzhou Central Hospital between June and December 2023. LTBI was diagnosed using the QFT-PLUS test, and data on patient characteristics, laboratory findings and computed tomography scans were gathered. A predictive model was constructed through univariate and multivariate logistic regression analyses. Results: Among individuals with DM, 28 (29.2%) were identified as having LTBI compared with 16.2% in healthy controls. The final predictive model included age (>60 vs ≤60 years, odds ratio [OR]: 4.994, 95% CI: 1.583-17.610), gender (male vs female, OR: 26.886, 95% CI: 5.224-231.700), duration of diabetes (>10 vs ≤10 years, OR: 3.450, 95% CI: 1.000-13.240) and presence of hyperlipidaemia (yes vs no, OR: 10.637, 95% CI: 2.299-82.340) as significant factors, yielding an area under the curve of 0.847 (95% CI: 0.765-0.928). Conclusion: This QFT-PLUS-based predictive model, incorporating readily available clinical parameters, demonstrates potential clinical utility for LTBI risk stratification and targeted TB screening in patients with DM. Future multicentre external validation studies with larger sample sizes are warranted before clinical implementation.

Indexed as

diabeteslatent tuberculosis infectionpredictive modelQFT-PLUSrisk factor

Identifiers

PMID42245749
PMCPMC13231190

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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.