Combined effect of functional impairment and metabolic dysregulation on post-stroke depression risk
- 1Department of Radiology, Affiliated Nantong Clinical College of Nantong University, Nantong First People’s Hospital, Nantong University
- 2Department of Neurology, Nantong First People’s Hospital, Southeast University
- 3Department of Intervention, Affiliated Nantong Clinical College of Nantong University, Nantong First People’s Hospital, Nantong University
Abstract
Background: Post-stroke depression (PSD) is one of the most common neuropsychiatric complications among stroke survivors, significantly affecting rehabilitation adherence and long-term clinical outcomes. Although previous studies have examined the roles of either functional impairment or metabolic dysregulation in PSD, limited research has explored their combined impact from an integrative perspective.
Methods: This study included 245 stroke patients, of whom 65 were diagnosed with PSD. Restricted cubic spline (RCS) analysis was used to assess nonlinear associations between the atherogenic index of plasma (AIP), triglyceride-glucose (TyG) index, and the risk of PSD. Multivariate logistic regression was performed to identify independent predictors. A partial least squares (PLS) model was constructed using four variables—Barthel index, body mass index (BMI), AIP, and TyG index. Then the K-means clustering was applied to identify functional–metabolic subtypes and examine their associations with PSD.
Results: Compared with non-PSD patients, those with PSD showed significantly lower Barthel index scores and higher TyG and AIP levels. RCS analysis indicated a nonlinear relationship between AIP and PSD. Logistic regression identified the Barthel index (OR = 0.97, 95% CI: 0.95-0.99) and TyG index (OR = 2.04, 95% CI: 1.19-3.47) as independent predictors of PSD. PLS-K-means clustering revealed four distinct subtypes. Patients in subtype 3 (metabolically susceptible subtype) and subtype 4 (dual-impaired subtype) had significantly higher PSD risks compared to subtypes 1 and 2 (OR = 2.13 and 2.63, respectively).
Conclusions: Functional impairment and metabolic dysregulation are jointly associated with the development of PSD, and their interaction may constitute a key potential mechanistic.
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BibTeX
@article{zhang2026combined,
title = {{Combined effect of functional impairment and metabolic dysregulation on post-stroke depression risk}},
author = {Tianhao Zhang and WenLu Shi and Qingjie Chi and Jinhua Qian and Tianle Wang and Li Zhu and Wenbing Ding and Zhuo Chen},
journal = {Frontiers in Psychiatry},
year = {2026},
month = oct,
doi = {10.3389/fpsyt.2026.1843802},
url = {https://www.frontiersin.org/articles/10.3389/fpsyt.2026.1843802/full},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Combined effect of functional impairment and metabolic dysregulation on post-stroke depression risk
AU - Tianhao Zhang
AU - WenLu Shi
AU - Qingjie Chi
AU - Jinhua Qian
AU - Tianle Wang
AU - Li Zhu
AU - Wenbing Ding
AU - Zhuo Chen
PY - 2026
DA - 2026/10/16
JO - Frontiers in Psychiatry
DO - 10.3389/fpsyt.2026.1843802
UR - https://www.frontiersin.org/articles/10.3389/fpsyt.2026.1843802/full
AB - Background: Post-stroke depression (PSD) is one of the most common neuropsychiatric complications among stroke survivors, significantly affecting rehabilitation adherence and long-term clinical outcomes. Although previous studies have examined the roles of either functional impairment or metabolic dysregulation in PSD, limited research has explored their combined impact from an integrative perspective. Methods: This study included 245 stroke patients, of whom 65 were diagnosed with PSD. Restricted cubic spline (RCS) analysis was used to assess nonlinear associations between the atherogenic index of plasma (AIP), triglyceride-glucose (TyG) index, and the risk of PSD. Multivariate logistic regression was performed to identify independent predictors. A partial least squares (PLS) model was constructed using four variables—Barthel index, body mass index (BMI), AIP, and TyG index. Then the K-means clustering was applied to identify functional–metabolic subtypes and examine their associations with PSD. Results: Compared with non-PSD patients, those with PSD showed significantly lower Barthel index scores and higher TyG and AIP levels. RCS analysis indicated a nonlinear relationship between AIP and PSD. Logistic regression identified the Barthel index (OR = 0.97, 95% CI: 0.95-0.99) and TyG index (OR = 2.04, 95% CI: 1.19-3.47) as independent predictors of PSD. PLS-K-means clustering revealed four distinct subtypes. Patients in subtype 3 (metabolically susceptible subtype) and subtype 4 (dual-impaired subtype) had significantly higher PSD risks compared to subtypes 1 and 2 (OR = 2.13 and 2.63, respectively). Conclusions: Functional impairment and metabolic dysregulation are jointly associated with the development of PSD, and their interaction may constitute a key potential mechanistic.
SN - 1664-0640
ER -