Evidence map›Paper›PMID 40542362›Full record

ArticleLipids in health and disease2025

Clinical management of lipid metabolism abnormalities induced by antipsychotics in closed psychiatric settings: challenges and integrated strategies.

Jiakuan Tu, Yu Qiu, Yueting Zhang, Yang Yang, Yi Huang

Abstract readLetter
In one paragraph

Article in Lipids in health and disease, 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.

Jiakuan Tu *The First Department of Orthopedics, Jiangxi Provincial Hospital of Integrated Traditional Chinese and Western Medicine, Nanchang, 33003, China.
Yu Qiu *Department of Hepatic Diseases of Chongqing hospital of traditional Chinese medicine, Chongqing, 400021, China. xiaoyu10187715@qq.com.
Yueting ZhangDepartment of Hepatic Diseases of Chongqing hospital of traditional Chinese medicine, Chongqing, 400021, China.
Yang YangDepartment of Hepatic Diseases of Chongqing hospital of traditional Chinese medicine, Chongqing, 400021, China.
Yi HuangDepartment of Hepatic Diseases of Chongqing hospital of traditional Chinese medicine, Chongqing, 400021, China. hy11_22@sina.com.

Funding

Chongqing Natural Science Foundation General Project No. cstc2021jcyj-msxmX0390Youth Science Foundation Project of the National Natural Science Foundation of China 82405162
6 · The paper itself

Abstract

In closed psychiatric settings, antipsychotic-induced lipid metabolism abnormalities pose significant clinical challenges. Constrained by limited patient mobility, fluctuating treatment adherence, and monotonous diets, traditional management struggles to adequately balance drug side effects with patient health needs. This study presents an integrated framework involving surveillance, intervention, and interdisciplinary collaboration. It includes a comprehensive "admission-to-intervention" monitoring system, low-glycemic diet combined with portion control, symptom-specific exercise programs, and strategies to improve treatment adherence. We establish quality metrics, including 100% baseline lipid testing for new admissions and ≥ 95% timely intervention rate for abnormalities. The patient-centered model reduces cardiovascular risks, improves patient outcomes, and offers a scalable approach for metabolic health management in resource-limited environments.

Indexed as

Antipsychotic AgentsLipid MetabolismMental DisordersHumansAntipsychotic AgentsAntipsychoticsClosed psychiatric settingsInterdisciplinary collaborationLipid metabolism disordersMetabolic monitoring.

Identifiers

PMID40542362
PMCPMC12181918

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Registered trials

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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.