2026-06-17T16:36:08Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/87802024-03-09T01:05:25Zcom_10259_4219com_10259_5086com_10259_2604col_10259_4220

Ayala, Alba Triviño Juárez, José Matías Forjaz, María Joao Rodríguez Blázquez, Carmen Rojo Abuin, José Manuel Martínez Martín, Pablo Cubo Delgado, Esther ELEP Group 2024-03-08T08:57:26Z 2024-03-08T08:57:26Z 2017-10 http://hdl.handle.net/10259/8780 10.3389/fneur.2017.00551 1664-2295 Objective: The aim of this study is to present a predictive model of Parkinson’s disease (PD) global severity, measured with the Clinical Impression of Severity Index for Parkinson’s Disease (CISI-PD). Methods: This is an observational, longitudinal study with annual follow-up assessments over 3 years (four time points). A multilevel analysis and multiple imputation techniques were performed to generate a predictive model that estimates changes in the CISI-PD at 1, 2, and 3 years. Results: The clinical state of patients (CISI-PD) significantly worsened in the 3-year follow-up. However, this change was of small magnitude (effect size: 0.44). The following baseline variables were significant predictors of the global severity change: baseline global severity of disease, levodopa equivalent dose, depression and anxiety symptoms, autonomic dysfunction, and cognitive state. The goodness-of-fit of the model was adequate, and the sensitive analysis showed that the data imputation method applied was suitable. Conclusion: Disease progression depends more on the individual’s baseline characteristics than on the 3-year time period. Results may contribute to a better understanding of the evolution of PD including the non-motor manifestations of the disease. eng http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess Atribución 4.0 Internacional Parkinson’s disease Disease global severity Predictive model Multilevel analysis Multiple imputation Parkinson’s Disease Severity at 3 Years Can Be Predicted from Non-Motor Symptoms at Baseline info:eu-repo/semantics/article