Evidence map›Paper›PMID 40966685›Full record

ArticleJMIR research protocols2025

Neural Activity Disparities in Deficiency and Excess Patterns of Depression: Protocol for a Systematic Review and Meta-Analysis.

Liling Chen, Xinyu Jia, Jianjun Wang, Liling Li, Jianxiang Chen, Songjun Lin, Haotao Zheng, Xinbei Li, Xiude Qin, Lanying Liu and 1 more

Abstract read
In one paragraph

Article in JMIR research protocols, 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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1 · What the graph read from it

What it found

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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

11 authors.

Liling Chen *The Fourth Clinical Medical College, Shenzhen Traditional Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, China.ORCID 0009-0008-2829-2005
Xinyu Jia *The Fourth Clinical Medical College, Shenzhen Traditional Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, China.ORCID 0009-0006-2732-8737
Jianjun WangThe Fourth Clinical Medical College, Shenzhen Traditional Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, China.ORCID 0000-0003-1565-6742
Liling LiThe Fourth Clinical Medical College, Shenzhen Traditional Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, China.ORCID 0009-0002-4788-7887
Jianxiang ChenThe Fourth Clinical Medical College, Shenzhen Traditional Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, China.ORCID 0000-0002-9998-9618
Songjun LinThe Fourth Clinical Medical College, Shenzhen Traditional Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, China.ORCID 0000-0003-3954-9247
Haotao ZhengThe Fourth Clinical Medical College, Shenzhen Traditional Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, China.ORCID 0000-0002-8992-8299
Xinbei LiThe Fourth Clinical Medical College, Shenzhen Traditional Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, China.ORCID 0000-0001-5094-8180
Xiude QinThe Fourth Clinical Medical College, Shenzhen Traditional Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, China.ORCID 0000-0002-4856-3748
Lanying LiuShanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.ORCID 0000-0002-2788-071X
Hanqing LyuThe Fourth Clinical Medical College, Shenzhen Traditional Chinese Medicine Hospital, Guangzhou University of Chinese Medicine, Shenzhen, China.ORCID 0009-0006-5024-1429

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMajor depressive disorder (MDD) is a complex and heterogeneous condition. Current diagnosis relies on symptom-based assessments, leading to varied treatment responses. Data-driven approaches have attempted to identify MDD subtypes, but their clinical applicability remains limited. Traditional Chinese Medicine (TCM) provides a theory-driven classification system that categorizes MDD into syndrome subtypes of deficiency pattern and excess pattern, offering insights into the biological mechanisms and personalized treatment strategies.

objectiveThis systematic review and meta-analysis aims to identify potential neurobiological distinctions of TCM-based deficiency and excess patterns in MDD by examining differences in the brain activity by using various functional magnetic resonance imaging (fMRI) modalities, including resting-state and task-based fMRI, diffusion tensor imaging, and magnetic resonance spectroscopy.

methodsIn accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P), we will conduct a comprehensive search of 7 electronic databases (PubMed, Embase, Web of Science, Chinese Biological Medical Literature database, China National Knowledge Infrastructure, Chinese Wanfang database, and Chongqing VIP database) for studies published up to December 2024. Eligible studies will be screened by 2 independent reviewers based on predefined inclusion criteria, followed by data extraction and quality assessment. For the meta-analysis, resting-state fMRI studies will be analyzed in Montreal Neurological Institute space using Seed-based d Mapping-Permutation of Subject Images software (version 6.21), enabling a focused evaluation of brain activity differences in deficiency and excess MDD patterns.

resultsThe search and screening for the systematic literature review were completed in December 2024. This study relies on published, publicly accessible data. We found approximately 30 eligible studies in our preliminary search, suggesting that a quantitative meta-analysis is feasible. Data extraction, quality appraisal, and subsequent data synthesis will begin in September 2025. The review should be completed by December 2025, and the study results will be published in 2026.

conclusionsThe results of this study may help to explain the neural mechanisms of depression's neurobiological subtypes from the perspective of TCM.

trial registrationPROSPERO CRD42023475178; https://www.crd.york.ac.uk/PROSPERO/view/CRD42023475178. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/68996.

Indexed as

BrainMajor Depressive DisorderHumansMagnetic Resonance ImagingMedicine, Chinese TraditionalMeta-Analysis as TopicResearch DesignSystematic Reviews as TopicChinese MedicinedepressionfALFFfractional amplitude of low-frequency fluctuationsfunctional magnetic resonance imagingsubtype

Identifiers

PMID40966685
PMCPMC12491882

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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.