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. 2024 Nov 22:16:1476701.
doi: 10.3389/fnagi.2024.1476701. eCollection 2024.

Total burden of cerebral small vessel disease predict subjective cognitive decline in patients with Parkinson's disease

Wenchao Qiu #  1   2 , Weili Hu #  3 , Yingchao Ge #  4 , Peiting Liu  1 , Minghui Zhao  1 , Haifeng Lu  5 , Jian Tao  5 , Shouru Xue  1
Affiliations

Total burden of cerebral small vessel disease predict subjective cognitive decline in patients with Parkinson's disease

Wenchao Qiu et al. Front Aging Neurosci. .

Abstract

Introduction: This study investigates the correlation between the total burden of Cerebral Small Vessel Disease (CSVD) and Subjective Cognitive Decline (SCD) in patients with Parkinson's disease (PD).

Methods: A cross-sectional design was employed, involving 422 patients with PD. Demographic and clinical data were collected. Brain magnetic resonance imaging (MRI) was conducted to identify CSVD markers. SCD was assessed using the Cognitive Complaints Inventory (CCI).

Results: Logistic regression analyses revealed that the total burden of CSVD and specific imaging markers, including Deep White Matter Hyperintensities (DWMH), Periventricular Hyperintensities (PVH), and Enlarged Perivascular Spaces (EPVS), were significant predictors of SCD. The total burden of CSVD demonstrated the highest predictive accuracy for SCD in PD patients.

Discussion: The findings suggest that the total burden of CSVD, as measured by MRI, could serve as a potential biomarker for early identification of cognitive decline in PD, highlighting the importance of considering vascular factors in the early detection of cognitive changes in PD.

Keywords: Parkinson’s disease; cerebral small vessel disease; magnetic resonance imaging; predictive biomarkers; subjective cognitive decline.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Flowchart of patient recruitment. PD, Parkinson’s disease; PD-MCI, PD with mild cognitive impairment; PDD, PD with dementia; PD-SCD, PD with subjective cognitive decline; PD-NC, PD with normal cognition.
Figure 2
Figure 2
ROC curves for prediction of SCD in PD patients. ROC curves of the total burden of CSVD, DWMH, PVH and CS-EPVS in predicting SCD in PD patients. The AUC with 95% CI is provided. ROC, Receiver Operating Characteristic; SCD, Subjective Cognitive Decline; PD, Parkinson’s disease; CSVD, Cerebral Small Vessel Disease; DWMH, deep white matter hyperintensities; PVH, Periventricular Hyperintensities; CS-EPVS, enlarged perivascular spaces in centrum semiovale; AUC, Area Under the Curve; CI, Confidence Interval.
Figure 3
Figure 3
Comparative analysis of AUCs from ROC curves for different CSVD markers (***p < 0.001). Each bar represents the AUC of a corresponding ROC curve shown in Figure 2. AUC, Area Under the Curve; CI, Confidence Interval; ROC, Receiver Operating Characteristic; CSVD, Cerebral Small Vessel Disease.
See this image and copyright information in PMC

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