Predictive Model of Quality of Life in Patients with Parkinson’s Disease

Parkinson’s disease is a chronic, progressive, and disabling neurodegenerative disease which evolves until the end of life and triggers different mood and organic alterations that influence health-related quality of life. The objective of our study was to identify the factors that negatively impact...

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Autores: Candel Parra, Eduardo, Corcoles Jiménez, María Pilar, Delicado Useros, Victoria, Ruiz Grao, Marta Carolina, Hernández Martínez, Antonio, Molina Alarcón, Milagros
Tipo de recurso: artículo
Fecha de publicación:2022
País:España
Institución:Universidad de Castilla-La Mancha
Repositorio:RUIdeRA. Repositorio Institucional de la UCLM
OAI Identifier:oai:ruidera.uclm.es:10578/32956
Acceso en línea:https://www.mdpi.com/1660-4601/19/2/672
https://hdl.handle.net/10578/32956
Access Level:acceso abierto
Palabra clave:Model predictive
Parkinson’s disease
PDQ-39
Quality of life
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spelling Predictive Model of Quality of Life in Patients with Parkinson’s DiseaseCandel Parra, EduardoCorcoles Jiménez, María PilarDelicado Useros, VictoriaRuiz Grao, Marta CarolinaHernández Martínez, AntonioMolina Alarcón, MilagrosModel predictiveParkinson’s diseasePDQ-39Quality of lifeParkinson’s disease is a chronic, progressive, and disabling neurodegenerative disease which evolves until the end of life and triggers different mood and organic alterations that influence health-related quality of life. The objective of our study was to identify the factors that negatively impact the quality of life of patients with Parkinson’s disease and construct a predictive model of health-related quality of life in these patients. Methods: An analytical, prospective observational study was carried out, including Parkinson’s patients at different stages in the Albacete Health Area. The sample consisted of 155 patients (T0) who were followed up at one (T1) and two years (T2). The instruments used were a purpose-designed data collection questionnaire and the “Parkinson’s Disease Questionnaire” (PDQ-39), with a global index where a higher score indicates a worse quality of life. A multivariate analysis was performed by multiple linear regression at T0. Next, the model’s predictive capacity was evaluated at T1 and T2 using the area under the ROC curve (AUROC). Results: Predictive factors were: sex, living in a residence, using a cane, using a wheelchair, having a Parkinson’s stage of HY > 2, having Alzheimer’s disease or a major neurocognitive disorder, having more than five non-motor symptoms, polypharmacy, and disability greater than 66%. This model showed good predictive capacity at one year and two years of follow-up, with an AUROC of 0.89 (95% CI: 0.83–0.94) and 0.83 (95% CI: 0.76–0.89), respectively. Conclusions: A predictive model constructed with nine variables showed a good discriminative capacity to predict the quality of life of patients with Parkinson’s disease at one and two years of follow-up.MDPI202420242022info:eu-repo/semantics/articleapplication/pdfapplication/pdfhttps://www.mdpi.com/1660-4601/19/2/672https://hdl.handle.net/10578/32956reponame:RUIdeRA. Repositorio Institucional de la UCLMinstname:Universidad de Castilla-La ManchaInglésinfo:eu-repo/semantics/openAccessoai:ruidera.uclm.es:10578/329562026-05-27T07:36:41Z
dc.title.none.fl_str_mv Predictive Model of Quality of Life in Patients with Parkinson’s Disease
title Predictive Model of Quality of Life in Patients with Parkinson’s Disease
spellingShingle Predictive Model of Quality of Life in Patients with Parkinson’s Disease
Candel Parra, Eduardo
Model predictive
Parkinson’s disease
PDQ-39
Quality of life
title_short Predictive Model of Quality of Life in Patients with Parkinson’s Disease
title_full Predictive Model of Quality of Life in Patients with Parkinson’s Disease
title_fullStr Predictive Model of Quality of Life in Patients with Parkinson’s Disease
title_full_unstemmed Predictive Model of Quality of Life in Patients with Parkinson’s Disease
title_sort Predictive Model of Quality of Life in Patients with Parkinson’s Disease
dc.creator.none.fl_str_mv Candel Parra, Eduardo
Corcoles Jiménez, María Pilar
Delicado Useros, Victoria
Ruiz Grao, Marta Carolina
Hernández Martínez, Antonio
Molina Alarcón, Milagros
author Candel Parra, Eduardo
author_facet Candel Parra, Eduardo
Corcoles Jiménez, María Pilar
Delicado Useros, Victoria
Ruiz Grao, Marta Carolina
Hernández Martínez, Antonio
Molina Alarcón, Milagros
author_role author
author2 Corcoles Jiménez, María Pilar
Delicado Useros, Victoria
Ruiz Grao, Marta Carolina
Hernández Martínez, Antonio
Molina Alarcón, Milagros
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Model predictive
Parkinson’s disease
PDQ-39
Quality of life
topic Model predictive
Parkinson’s disease
PDQ-39
Quality of life
description Parkinson’s disease is a chronic, progressive, and disabling neurodegenerative disease which evolves until the end of life and triggers different mood and organic alterations that influence health-related quality of life. The objective of our study was to identify the factors that negatively impact the quality of life of patients with Parkinson’s disease and construct a predictive model of health-related quality of life in these patients. Methods: An analytical, prospective observational study was carried out, including Parkinson’s patients at different stages in the Albacete Health Area. The sample consisted of 155 patients (T0) who were followed up at one (T1) and two years (T2). The instruments used were a purpose-designed data collection questionnaire and the “Parkinson’s Disease Questionnaire” (PDQ-39), with a global index where a higher score indicates a worse quality of life. A multivariate analysis was performed by multiple linear regression at T0. Next, the model’s predictive capacity was evaluated at T1 and T2 using the area under the ROC curve (AUROC). Results: Predictive factors were: sex, living in a residence, using a cane, using a wheelchair, having a Parkinson’s stage of HY > 2, having Alzheimer’s disease or a major neurocognitive disorder, having more than five non-motor symptoms, polypharmacy, and disability greater than 66%. This model showed good predictive capacity at one year and two years of follow-up, with an AUROC of 0.89 (95% CI: 0.83–0.94) and 0.83 (95% CI: 0.76–0.89), respectively. Conclusions: A predictive model constructed with nine variables showed a good discriminative capacity to predict the quality of life of patients with Parkinson’s disease at one and two years of follow-up.
publishDate 2022
dc.date.none.fl_str_mv 2022
2024
2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
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dc.identifier.none.fl_str_mv https://www.mdpi.com/1660-4601/19/2/672
https://hdl.handle.net/10578/32956
url https://www.mdpi.com/1660-4601/19/2/672
https://hdl.handle.net/10578/32956
dc.language.none.fl_str_mv Inglés
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dc.publisher.none.fl_str_mv MDPI
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dc.source.none.fl_str_mv reponame:RUIdeRA. Repositorio Institucional de la UCLM
instname:Universidad de Castilla-La Mancha
instname_str Universidad de Castilla-La Mancha
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