Evidence mapPaperPMID 39108745Full record

ArticleFrontiers in pharmacology2024

Clinical risk factors for moderate and severe antituberculosis drug-induced liver injury.

Quanxian Liu, Lu Huang, Hong Yan, Zhaojing Zong, Zhenyong Chen, Xiaoyan Wu, Ling Chen, Yuanbo Lan

Abstract read
In one paragraph

Article in Frontiers in pharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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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.

Quanxian LiuDepartment of Tuberculosis, Affiliated Hospital of Zunyi Medical University, Zunyi, China.
Lu HuangDepartment of Tuberculosis, Affiliated Hospital of Zunyi Medical University, Zunyi, China.
Hong YanDepartment of Tuberculosis, Affiliated Hospital of Zunyi Medical University, Zunyi, China.
Zhaojing ZongDepartment of Tuberculosis, Affiliated Hospital of Zunyi Medical University, Zunyi, China.
Zhenyong ChenDepartment of Tuberculosis, Affiliated Hospital of Zunyi Medical University, Zunyi, China.
Xiaoyan WuDepartment of Tuberculosis, Affiliated Hospital of Zunyi Medical University, Zunyi, China.
Ling ChenDepartment of Tuberculosis, Affiliated Hospital of Zunyi Medical University, Zunyi, China.
Yuanbo LanDepartment of Tuberculosis, Affiliated Hospital of Zunyi Medical University, Zunyi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To analyze the clinical and laboratory characteristics and to identify predictors of moderate to severe anti-tuberculosis drug-induced liver injury (ATB-DILI) in patients with tuberculosis. Methods: This prospective study enrolled Tuberculosis (TB) patients treated with first-line anti-tuberculosis drugs at the Affiliated Hospital of Zunyi Medical University between May 2022 and June 2023. The occurrence of ATB-DILI was monitored, and demographic and clinical data were gathered. We analyzed risk factors for the development of moderate to severe ATB-DILI. Results: ATB-DILI was detected in 120 (10.7%) of the patients, with moderate to severe ATB-DILI occurring in 23 (2.0%) of the 1,124 patients treated with anti-tuberculosis treatment. Multivariate cox regression analysis identified malnutrition (HR = 4.564, 95% CI: 1.029-20.251, Conclusion: The incidence of moderate to severe ATB-DILI was found to be 2.0%. Malnutrition and hemoglobin levels below 120 g/L emerged as significant independent risk factors for the occurrence of moderate to severe ATB-DILI in this patient population.

Indexed as

drug-induced liver injuryhaemoglobinmalnutritionmoderate and severe ATB-DlLlrisk factor

Identifiers

PMID39108745
PMCPMC11300277

What Socratic 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 Socratic graph.