Evidence map›Paper›PMID 42422591›Full record

ArticleTherapeutic advances in psychopharmacology2026

Identifying patients at risk of supratherapeutic amisulpride exposure in routine psychiatric practice: a real-world therapeutic drug monitoring study.

Keyu Yan, Gehang Ju, Aowei Li, Ruomei Gao, Na Wang, Qing Shao

Abstract read
In one paragraph

Article in Therapeutic advances in psychopharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. 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

6 authors.

Keyu YanDepartment of Pharmacy, Xi'an Mental Health Center, Xi'an, Shaanxi, P.R. China.ORCID https://orcid.org/0009-0004-7092-8338
Gehang JuInstitute of Big Data, Central South University, Changsha, Hunan, P.R. China.ORCID https://orcid.org/0000-0002-0721-5296
Aowei LiInstitute of Public Health, Tianjin University of Traditional Chinese Medicine, Tianjin, P.R. China.
Ruomei GaoBiomedical Big Data Center, West China Hospital of Sichuan University, Chengdu, Sichuan, P.R. China.
Na WangDepartment of Pharmacy, Xi'an Mental Health Center, Xi'an, Shaanxi, P.R. China.
Qing ShaoDepartment of Pharmacy, Xi'an Mental Health Center, No. 666, Kanghe Road, Chang'an District, Xi'an, Shaanxi, 710100, P.R. China.ORCID https://orcid.org/0009-0001-4052-5317

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Amisulpride is an important antipsychotic used in the treatment of schizophrenia, yet its exposure shows inter-individual variability. Although therapeutic drug monitoring (TDM) is recommended, supratherapeutic concentrations (>600 ng/mL) still occur in routine practice and may increase the risk of adverse effects. However, practical risk prediction studies of supratherapeutic amisulpride exposure based on routine clinical variables remain limited. Objectives: To identify patients at increased risk of supratherapeutic amisulpride exposure in routine psychiatric care and to develop a clinically interpretable risk prediction approach based on routinely available clinical variables. Design: This was a retrospective observational study using real-world TDM data from psychiatric inpatients. Methods: Therapeutic drug monitoring data were retrospectively analyzed. Patients were split at the patient level into training (70%) and validation (30%) cohorts. To identify the optimal representation of renal function and drug elimination, predictors were organized into three candidate pools: (i) apparent clearance (CL/F) calculated from the final covariate equation of a previously published population pharmacokinetic model, (ii) estimated creatinine clearance (eCLcr), and (iii) the original clinical variables used to calculate eCLcr. Within each candidate predictor pool, predictors were screened using LASSO-penalized logistic regression and then entered into multivariable logistic regression. The most clinically practical model was selected for nomogram construction. Model performance was assessed by discrimination, calibration, and decision curve analysis. Results: A total of 413 steady-state trough samples from 299 patients were analyzed, of which 19.6% exceeded a steady-state trough plasma concentration of 600 ng/mL. Reduced renal function and higher daily doses were consistently associated with an increased risk of supratherapeutic exposure. Among the three candidate strategies, the Key Covariate-based strategy achieved acceptable discrimination in both the training (area under the receiver operating characteristic curve (AUC) 0.738) and validation (AUC 0.720) cohorts, with good calibration. Decision curve analysis suggested potential clinical utility across a range of lower to moderate threshold probabilities. Conclusion: A simple risk stratification approach based on eCLcr and daily dose may offer a reference for individualized risk assessment. This model may provide preliminary support for identifying patients at risk of supratherapeutic exposure in routine psychiatric practice.

Indexed as

amisulpriderisk stratificationsupratherapeutic exposuretherapeutic drug monitoring

Identifiers

PMID42422591
PMCPMC13342374

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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.