Evidence map›Paper›PMID 41204288›Full record

SynthesisBMC medicine2025

Gaps in the detection of drug-drug interactions between antipsychotic and cardiometabolic medications: a multisource analysis.

Honghui Yao, Zixuan Peng, Yue Huang, Shuiyuan Xiao, Renrong Wu

Abstract readSystematic Review
In one paragraph

Synthesis in BMC medicine, 2025. 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
0cells of the map it votes in
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

5 authors.

Honghui YaoDepartment of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China.
Zixuan PengSchool of Public Health, Southeast University, Nanjing, China.
Yue HuangSchool of Public Health, Shandong Second Medical University, Weifang, China.
Shuiyuan XiaoDepartment of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China.
Renrong WuDepartment of Psychiatry, National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China. wurenrong@csu.edu.cn.

Funding

Key Research and Development Project of Ministry of Science and Technology of China 2016YFC0900802National Natural Science Foundation of China 82325020
6 · The paper itself

Abstract

backgroundIndividuals with severe mental illness (SMI) are frequently prescribed both antipsychotic medications and cardiometabolic medications, placing them at increased risk of drug-drug interactions (DDIs). However, evidence guiding the identification and management of these interactions remains fragmented. To address this research gap, in this study, we systematically summarize potential DDIs between antipsychotic and cardiometabolic medications and evaluate the performance of commonly used online DDI checkers in identifying these interactions.

methodsA systematic review was conducted using PubMed, Embase, PsycINFO, and Web of Science to identify studies reporting DDIs between antipsychotic and cardiometabolic medications up to March 20, 2024. Disproportionality analysis was performed using data from the Canada Vigilance Adverse Reaction Online Database (1965-2024) and the FDA Adverse Event Reporting System (FAERS, 2004-2024) to identify DDI signals. Four online DDI checkers-Drugs.com, Medscape, ddinter, and ANSM Thesaurus-were used to evaluate their ability to identify the observed interactions.

resultsAcross all sources, 1776 unique potential DDIs were identified. Clozapine was the most frequently implicated antipsychotic medication in a systematic review, often associated with musculoskeletal and connective tissue disorders. DDI signals associated with aripiprazole and quetiapine were also frequently observed. Except for nervous system disorders and cardiometabolic disorders, the adverse outcomes of DDIs involving aripiprazole or quetiapine were most commonly associated with musculoskeletal and connective tissue disorders and gastrointestinal disorders. Quetiapine interactions, especially with lipid-lowering agents such as simvastatin, were also commonly linked to musculoskeletal and connective tissue disorders. Notably, 45.4% of identified DDIs were not flagged by any of the four DDI checkers. Drugs.com detected the most interactions. Combinations of clozapine and metformin, ziprasidone and metformin, and risperidone and clonidine were consistently identified by at least three of the checkers.

conclusionsThis systematic review and disproportionality analysis identified potential DDIs between antipsychotic medications and cardiometabolic medications, many of which were not captured by commonly used DDI checkers. These findings underscore the need for clinicians to consult multiple sources and apply clinical judgment when prescribing these medications. Improved integration of pharmacovigilance data into DDI checkers may enhance the identification and prevention of harmful interactions.

Indexed as

Antipsychotic AgentsCardiovascular AgentsAdverse Drug Reaction Reporting SystemsDrug InteractionsHumansMental DisordersAntipsychotic AgentsCardiovascular AgentsAntipsychotic medicationDisproportionality analysisDrug-drug interaction

Identifiers

PMID41204288
PMCPMC12595901

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.