Table 1_Three-dimensional facial features of suicide risk in females with depression.docx

AimSuicide 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.
MethodsWe 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.
ResultsData 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, p < 0.05). Analyses revealed sex-specific facial patterns, with males demonstrating suicide risk association with philtrum depth (t=2.389, p < 0.05) and females showing nose-eye distance variations (U = 1121, p < 0.05). Logistic regression identified female (OR = 2.055, 95% CI: 1.107-3.873, p < 0.05) and shallow philtrum (OR = 0.644, 95% CI: 0.419-0.952, p < 0.05) as potential factors, with a significant interaction effect (OR = 1.963, 95% CI: 0.419-0.952, p < 0.05).
ConclusionThis 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 registrationhttps://www.chictr.org.cn, identifier ChiCTR2400090458.

【研究背景与目的】自杀行为是重性抑郁障碍（Major Depressive Disorder，MDD）最严重的不良结局。当前的自杀风险评估高度依赖主观性自我报告，其信度欠佳。新兴技术如面部与行为识别设备正被探索用于优化自杀风险评估流程。本研究旨在探究三维面部特征在识别MDD患者自杀风险中的应用潜力，并揭示患者的性别特异性相关特征。
【研究方法】本研究为横断面研究，共纳入222名MDD患者。研究人员从照料者处收集与自杀相关的信息，由独立评估者评定患者的抑郁症状并记录其社会人口学资料。采用3dMDface系统采集患者的三维面部扫描图像，随后通过预处理步骤提取关键面部标志点（facial landmarks）。本研究采用性别分层亚组分析以筛选与自杀风险相关的面部特征；并通过逻辑回归分析以评估人口学资料、临床特征及筛选出的面部标记物作为预测因子的预测效能。
【研究结果】本研究最终纳入203名患者的数据进行分析，其中自杀风险组110人，非自杀组93人。自杀风险组患者的人中长度显著更短（t=2.137，p<0.05）。分析结果显示存在性别特异性的面部特征模式：男性中，人中深度与自杀风险存在显著关联（t=2.389，p<0.05）；女性中，鼻眼距离的变化与自杀风险相关（U=1121，p<0.05）。逻辑回归分析显示，女性（比值比（Odds Ratio，OR）=2.055，95%置信区间（Confidence Interval，CI）：1.107~3.873，p<0.05）与人中较浅（OR=0.644，95%CI：0.419~0.952，p<0.05）是自杀风险的潜在预测因子，且二者存在显著的交互效应（OR=1.963，95%CI：0.419~0.952，p<0.05）。
【研究结论】本研究明确了MDD患者中与自杀风险相关的性别特异性面部特征，其中女性人群的人中深度降低与自杀风险存在关联。此类客观检测指标可作为当前临床自杀风险评估的补充手段，但仍需开展后续纵向研究以验证其效能。
【临床试验注册】本研究已在中国临床试验注册中心（https://www.chictr.org.cn）注册，注册号为ChiCTR2400090458。