Evidence map›Paper›PMID 41659179›Full record

ArticleFrontiers in psychiatry2025

Three-dimensional facial features of suicide risk in females with depression.

Jie Yang, Lingui Chen, Ling Zhang, Jing-Dong J Han, Gang Wang

Abstract read
In one paragraph

Article in Frontiers in psychiatry, 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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0citing papers in PubMed
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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

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.

Jie Yang *Beijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.
Lingui Chen *National Institute of Biological Science Joint Graduate Program, Peking University, Beijing, China.
Ling ZhangBeijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.
Jing-Dong J HanNational Institute of Biological Science Joint Graduate Program, Peking University, Beijing, China.
Gang WangBeijing Key Laboratory of Mental Disorders, National Clinical Research Center for Mental Disorders & National Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aim: Suicide is the most severe consequence of Major Depressive Disorder (MDD). Current risk assessments rely heavily on subjective self-reports, which lack reliability. Emerging technologies, such as facial and behavioral recognition devices, are being explored to improve suicide risk evaluation. This study aimed to examine the potential of 3D facial features in identifying suicide risk and uncovering sex-specific characteristics in patients with MDD. Methods: We conducted a cross-sectional study involving 222 MDD patients. Suicide-related information was collected from caregivers, while independent raters assessed depressive symptoms and recorded sociodemographic data. Three-dimensional facial scans were acquired using the 3dMDface System, followed by preprocessing to extract key facial landmarks. Sex-stratified subgroup analyses were performed to identify suicide risk-associated facial features. Logistic regression analysis was used to evaluate predictors, including demographic data, clinical characteristics, and the identified facial markers. Results: Data from 203 patients were analyzed, including 110 in the suicide-risk group and 93 in the non-suicidal group. The suicidal group exhibited significantly shorter philtrum length (t = 2.137, Conclusion: This study identified sex-specific facial features associated with suicide risk in MDD, with reduced philtrum depth in females emerging as a correlate. These objective measures could complement current clinical risk assessments, though further longitudinal validation is required. Clinical trial registration: https://www.chictr.org.cn, identifier ChiCTR2400090458.

Indexed as

3D facial features3D imagingfemalemajor depressive disordersex-specificsuicide risk

Identifiers

PMID41659179
PMCPMC12873306

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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.