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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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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 |
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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 |
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