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The severity assessment of Parkinson's disease based on plasma inflammatory factors and third ventricle width by transcranial sonography.
- Source :
-
CNS neuroscience & therapeutics [CNS Neurosci Ther] 2024 Mar; Vol. 30 (3), pp. e14670. - Publication Year :
- 2024
-
Abstract
- Background: Predicting Parkinson's disease (PD) can provide patients with targeted therapies. However, disease severity can be roughly evaluated in clinical practice based on the patient's symptoms and signs.<br />Objective: The current study attempted to explore the factors linked with PD severity and construct a predictive model.<br />Method: The PD patients and healthy controls were recruited from our study center while recording their basic demographic information. The serum inflammatory markers levels, such as Cystatin C (Cys C), C-reactive protein (CRP), RANTES (regulated on activation, normal T cell expressed and secreted), Interleukin-10 (IL-10), and Interleukin-6 (IL-6) were determined for all the participants. PD patients were categorized into early and mid-advanced groups based on the Hoehn and Yahr (H-Y) scale and evaluated using PD-related scales. LASSO logistic regression analysis (Model C) helped select variables based on clinical scale evaluations, serum inflammatory factor levels, and transcranial sonography measurements. The optimal harmonious model coefficient λ was determined via 10-fold cross-validation. Moreover, Model C was compared with multivariate (Model A) and stepwise (Model B) logistic regression. The area under the curve (AUC) of a receiver operator characteristic (ROC), brier score, calibration curve, and decision curve analysis (DCA) helped determine the discrimination and calibration of the predictive model, followed by configuring a forest plot and column chart.<br />Results: The study included 113 healthy individuals and 102 PD patients, with 26 early and 76 mid-advanced patients. Univariate analysis of variance screened out statistically significant differences among inflammatory markers Cys C and RANTES. The average Cys C level in the mid-advanced stage was significantly higher than in the early stage (p < 0.001) but not for RANTES (p = 0.740). The LASSO logistic regression model (λ.1se = 0.061) associated with UPDRS-I, UPDRS-II, UPDRS-III, HAMA, PDQ-39, and Cys C as the included independent variables revealed that the Model C discrimination and calibration (AUC = 0.968, Brier = 0.049) were superior to Model A (AUC = 0.926, Brier = 0.079) and Model B (AUC = 0.929, Brier = 0.071) models.<br />Conclusion: The study results show multiple factors are linked with PD assessment. Moreover, the inflammatory marker Cys C and transcranial sonography measurement could objectively predict PD symptom severity, helping doctors monitor PD evolution in patients while targeting interventions.<br /> (© 2024 The Authors. CNS Neuroscience & Therapeutics published by John Wiley & Sons Ltd.)
Details
- Language :
- English
- ISSN :
- 1755-5949
- Volume :
- 30
- Issue :
- 3
- Database :
- MEDLINE
- Journal :
- CNS neuroscience & therapeutics
- Publication Type :
- Academic Journal
- Accession number :
- 38459662
- Full Text :
- https://doi.org/10.1111/cns.14670