Evidence map›Paper›PMID 40458233›Full record

ArticleJournal of multidisciplinary healthcare2025

Risk Assessment of Linezolid-Associated Neurological Adverse Drug Reactions Based on the Food and Drug Administration Adverse Event Reporting System Database.

Jingwen Yin, Xi Chen, Jingjing Sun, Yu Wang, Kunkun Wang

Abstract read
In one paragraph

Article in Journal of multidisciplinary healthcare, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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.

Jingwen YinDepartment of Pharmacy, Tianjin 4th Center Hospital, Tianjin, People's Republic of China.
Xi ChenDepartment of Critical Care Medicine, Tianjin 4th Center Hospital, Tianjin, People's Republic of China.
Jingjing SunDepartment of Critical Care Medicine, Tianjin 4th Center Hospital, Tianjin, People's Republic of China.
Yu WangDepartment of Pharmacy, Tianjin 4th Center Hospital, Tianjin, People's Republic of China.
Kunkun WangDepartment of Critical Care Medicine, Tianjin 4th Center Hospital, Tianjin, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To conduct data mining and analysis on neurological adverse drug reactions (ADRs), defined as any unwanted neurological effects caused by the use of linezolid, affecting both the central and peripheral nervous systems. This study also aims to investigate potential drug-drug interactions that may increase the risk of these ADRs when linezolid is used in combination with other medications. The findings aim to provide guidance for the safe clinical use of linezolid. Methods: Data from the US Food and Drug Administration Adverse Event Reporting System between 1 July 2014 and 30 June 2024 were analysed to identify linezolid-related neurological ADRs. The Ω shrinkage measure was used to detect drugs associated with an elevated risk of neurological ADRs. Results: A total of 8521 reports of linezolid-related ADRs were retrieved, of which 20.12% (1720 cases) involved neurological ADRs. Forty-five signals of neurological ADRs were detected, with serotonin syndrome (436 cases, reporting odds ratio [ROR] = 43.66, representing 25.35%) and peripheral neuropathy (413 cases, ROR = 7.88, representing 24.01%) being the most prevalent. Additionally, 23 previously undocumented ADR signals and 21 drugs associated with an increased risk of neurological ADRs (Ω 025 > 0) were identified. Conclusion: This study highlights the need for careful monitoring of neurological ADRs associated with linezolid, vigilance regarding previously undocumented ADRs and the prudent management of concomitant medications. These findings provide essential guidance for the safe clinical use of linezolid.

Indexed as

adverse drug reactionlinezolidneurotoxicitysignal detection

Identifiers

PMID40458233
PMCPMC12127208

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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.