Evidence map›Paper›PMID 40822460›Full record

ArticleFrontiers in pharmacology2025

Neurological adverse events associated with antidepressants: a comprehensive 22-year analysis of the FDA adverse event reporting system.

Qian Yu, Jingyang Yao, Enping Li, Mingkai Xia, Ziang Hu, Yun Xiao, Jianliang Huang, Mingsheng Lei

Abstract read
In one paragraph

Article in Frontiers in pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
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.

Qian Yu *Zhangjiajie Hospital Affiliated to Hunan Normal University, Zhangjiajie, Hunan, China.
Jingyang Yao *Zhangjiajie Hospital Affiliated to Hunan Normal University, Zhangjiajie, Hunan, China.
Enping LiZhangjiajie Hospital Affiliated to Hunan Normal University, Zhangjiajie, Hunan, China.
Mingkai XiaZhangjiajie Hospital Affiliated to Hunan Normal University, Zhangjiajie, Hunan, China.
Ziang HuZhangjiajie Hospital Affiliated to Hunan Normal University, Zhangjiajie, Hunan, China.
Yun XiaoChangsha Central Hospital, Changsha, Hunan, China.
Jianliang HuangZhangjiajie Hospital Affiliated to Hunan Normal University, Zhangjiajie, Hunan, China.
Mingsheng LeiZhangjiajie Hospital Affiliated to Hunan Normal University, Zhangjiajie, Hunan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Antidepressants are among the most commonly prescribed medications worldwide; however, comprehensive analyses of neuropsychiatric adverse events (AEs) across different drug classes and patient subgroups remain scarce. Methods: The primary objective of this study was to utilize the U.S. Food and Drug Administration's Adverse Event Reporting System (FAERS) database to identify and characterize neurosafety signals associated with seven classes of antidepressants. Individual case safety reports involving 33 antidepressants were analyzed from 2004 to 2025, focusing on neurological AEs. The reports' odds ratios (RORs) were calculated and presented. Kaplan-Meier methods were employed for time-to-event analysis, and subgroup analyses were conducted to explore patterns specific to age, gender, and drug class. Results: The database contained 127,568 neurological AEs, accounting for 33.8% of the total reports of antidepressant. Reported data were traced to 98 countries and regions, primarily from North America and Western Europe. The number, type, and severity of reported neurological AEs varied significantly by gender, age groups, and drug categories. In the adverse reaction signal analysis, a series of strong adverse reaction signals were identified, with "neonatal movement disorders" showing the strongest signal (ROR = 51.97), and serotonin syndrome signals were also prominent. Distinct signals were also identified in the analysis of various drug categories. For instance, SSRIs and SNRIs exhibited signal patterns associated with neonatal adaptation, NaSSAs displayed the strongest single signal in "motor dysarthria," and MAOIs were associated with severe motor emergencies. NDRIs demonstrated excessive activation of the sympathetic nervous system, while the strongest signals for SARI/SMS drugs were concentrated in "visual stereotypy" and "hypoglycemic encephalopathy." TCAs exhibited the broadest spectrum of neurological AEs. Serotonin syndrome is present in nearly every drug group. The median onset time for neurological AEs was 45 days. Significant differences were observed between drug categories, with MAOIs having the longest median onset time (91 days). Onset time was unrelated to gender but closely associated with age groups. Conclusion: Overall, this 22-year database analysis revealed diverse patterns of neurological AEs associated with antidepressants, providing evidence to inform safe clinical decision-making regarding drug use across populations.

Indexed as

antidepressantsdisproportionality analysisFAERSneurological adverse eventspharmacovigilance

Identifiers

PMID40822460
PMCPMC12354350

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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.