Cargando…

Nomogram for Predicting Depression Improvement after Deep Brain Stimulation for Parkinson’s Disease

Background: Parkinson’s disease is a common neurodegenerative disease, with depression being a common non-motor symptom. Bilateral subthalamic nucleus deep brain stimulation is an effective method for the treatment of Parkinson’s disease. Thus, this study aimed to establish a nomogram of the possibi...

Descripción completa

Detalles Bibliográficos
Autores principales: Chang, Bowen, Ni, Chen, Mei, Jiaming, Xiong, Chi, Chen, Peng, Jiang, Manli, Niu, Chaoshi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9313072/
https://www.ncbi.nlm.nih.gov/pubmed/35884652
http://dx.doi.org/10.3390/brainsci12070841
_version_ 1784753989441552384
author Chang, Bowen
Ni, Chen
Mei, Jiaming
Xiong, Chi
Chen, Peng
Jiang, Manli
Niu, Chaoshi
author_facet Chang, Bowen
Ni, Chen
Mei, Jiaming
Xiong, Chi
Chen, Peng
Jiang, Manli
Niu, Chaoshi
author_sort Chang, Bowen
collection PubMed
description Background: Parkinson’s disease is a common neurodegenerative disease, with depression being a common non-motor symptom. Bilateral subthalamic nucleus deep brain stimulation is an effective method for the treatment of Parkinson’s disease. Thus, this study aimed to establish a nomogram of the possibility of achieving a better depression improvement rate after subthalamic nucleus deep brain stimulation in patients with Parkinson’s disease. Methods: We retrospectively analyzed 103 patients with Parkinson’s disease who underwent subthalamic nucleus deep brain stimulation and were followed up for the improvement of their Hamilton Depression scale scores 1 year postoperatively. Univariate and multivariate logistic regression analyses were used to select factors affecting the improvement rate of depression. A nomogram was then developed to predict the possibility of achieving better depression improvement. Furthermore, the discrimination and fitting performance was evaluated using a calibration diagram, receiver operating characteristics, and decision curve analysis. Results: The mean and median improvement rates of Hamilton Depression scores were 13.1 and 33.3%, respectively. Among the 103 patients, 70.8% had an improved depression, 23.3% had a worsened depression, and 5.8% remained unchanged. Logistic multivariate regression analysis showed that age, preoperative Parkinson’s Disease Questionnaire, Hamilton Anxiety, and Hamilton Depression scores were independent factors for the possibility of achieving a better depression improvement rate. Based on these results, a nomogram model was developed. The nomogram had a C-index of 0.78 (95% confidence interval: 0.69–0.87) and an area under the receiver operating characteristics of 0.78 (95% confidence interval: 0.69–0.87). The calibration plot and decision curve analysis further demonstrated goodness-of-fit between the nomogram predictions and actual observations. Conclusion: We developed a nomogram to predict the possibility of achieving good depression improvement 1 year after subthalamic nucleus deep brain stimulation in patients with Parkinson’s disease, which showed a certain value in judging the expected depression improvement of these patients.
format Online
Article
Text
id pubmed-9313072
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-93130722022-07-26 Nomogram for Predicting Depression Improvement after Deep Brain Stimulation for Parkinson’s Disease Chang, Bowen Ni, Chen Mei, Jiaming Xiong, Chi Chen, Peng Jiang, Manli Niu, Chaoshi Brain Sci Article Background: Parkinson’s disease is a common neurodegenerative disease, with depression being a common non-motor symptom. Bilateral subthalamic nucleus deep brain stimulation is an effective method for the treatment of Parkinson’s disease. Thus, this study aimed to establish a nomogram of the possibility of achieving a better depression improvement rate after subthalamic nucleus deep brain stimulation in patients with Parkinson’s disease. Methods: We retrospectively analyzed 103 patients with Parkinson’s disease who underwent subthalamic nucleus deep brain stimulation and were followed up for the improvement of their Hamilton Depression scale scores 1 year postoperatively. Univariate and multivariate logistic regression analyses were used to select factors affecting the improvement rate of depression. A nomogram was then developed to predict the possibility of achieving better depression improvement. Furthermore, the discrimination and fitting performance was evaluated using a calibration diagram, receiver operating characteristics, and decision curve analysis. Results: The mean and median improvement rates of Hamilton Depression scores were 13.1 and 33.3%, respectively. Among the 103 patients, 70.8% had an improved depression, 23.3% had a worsened depression, and 5.8% remained unchanged. Logistic multivariate regression analysis showed that age, preoperative Parkinson’s Disease Questionnaire, Hamilton Anxiety, and Hamilton Depression scores were independent factors for the possibility of achieving a better depression improvement rate. Based on these results, a nomogram model was developed. The nomogram had a C-index of 0.78 (95% confidence interval: 0.69–0.87) and an area under the receiver operating characteristics of 0.78 (95% confidence interval: 0.69–0.87). The calibration plot and decision curve analysis further demonstrated goodness-of-fit between the nomogram predictions and actual observations. Conclusion: We developed a nomogram to predict the possibility of achieving good depression improvement 1 year after subthalamic nucleus deep brain stimulation in patients with Parkinson’s disease, which showed a certain value in judging the expected depression improvement of these patients. MDPI 2022-06-28 /pmc/articles/PMC9313072/ /pubmed/35884652 http://dx.doi.org/10.3390/brainsci12070841 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Chang, Bowen
Ni, Chen
Mei, Jiaming
Xiong, Chi
Chen, Peng
Jiang, Manli
Niu, Chaoshi
Nomogram for Predicting Depression Improvement after Deep Brain Stimulation for Parkinson’s Disease
title Nomogram for Predicting Depression Improvement after Deep Brain Stimulation for Parkinson’s Disease
title_full Nomogram for Predicting Depression Improvement after Deep Brain Stimulation for Parkinson’s Disease
title_fullStr Nomogram for Predicting Depression Improvement after Deep Brain Stimulation for Parkinson’s Disease
title_full_unstemmed Nomogram for Predicting Depression Improvement after Deep Brain Stimulation for Parkinson’s Disease
title_short Nomogram for Predicting Depression Improvement after Deep Brain Stimulation for Parkinson’s Disease
title_sort nomogram for predicting depression improvement after deep brain stimulation for parkinson’s disease
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9313072/
https://www.ncbi.nlm.nih.gov/pubmed/35884652
http://dx.doi.org/10.3390/brainsci12070841
work_keys_str_mv AT changbowen nomogramforpredictingdepressionimprovementafterdeepbrainstimulationforparkinsonsdisease
AT nichen nomogramforpredictingdepressionimprovementafterdeepbrainstimulationforparkinsonsdisease
AT meijiaming nomogramforpredictingdepressionimprovementafterdeepbrainstimulationforparkinsonsdisease
AT xiongchi nomogramforpredictingdepressionimprovementafterdeepbrainstimulationforparkinsonsdisease
AT chenpeng nomogramforpredictingdepressionimprovementafterdeepbrainstimulationforparkinsonsdisease
AT jiangmanli nomogramforpredictingdepressionimprovementafterdeepbrainstimulationforparkinsonsdisease
AT niuchaoshi nomogramforpredictingdepressionimprovementafterdeepbrainstimulationforparkinsonsdisease