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Nomogram to Predict Cognitive State Improvement after Deep Brain Stimulation for Parkinson’s Disease

Purpose: Parkinson’s disease (PD) is a common neurodegenerative disease, for which cognitive impairment is a non-motor symptom (NMS). Bilateral subthalamic nucleus deep brain stimulation (STN-DBS) is an effective treatment for PD. This study established a nomogram to predict cognitive improvement ra...

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Autores principales: Chang, Bowen, Ni, Chen, Zhang, Weiwen, 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/PMC9220903/
https://www.ncbi.nlm.nih.gov/pubmed/35741644
http://dx.doi.org/10.3390/brainsci12060759
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author Chang, Bowen
Ni, Chen
Zhang, Weiwen
Mei, Jiaming
Xiong, Chi
Chen, Peng
Jiang, Manli
Niu, Chaoshi
author_facet Chang, Bowen
Ni, Chen
Zhang, Weiwen
Mei, Jiaming
Xiong, Chi
Chen, Peng
Jiang, Manli
Niu, Chaoshi
author_sort Chang, Bowen
collection PubMed
description Purpose: Parkinson’s disease (PD) is a common neurodegenerative disease, for which cognitive impairment is a non-motor symptom (NMS). Bilateral subthalamic nucleus deep brain stimulation (STN-DBS) is an effective treatment for PD. This study established a nomogram to predict cognitive improvement rate after STN-DBS in PD patients. Methods: We retrospectively analyzed 103 PD patients who underwent STN-DBS. Patients were followed up to measure improvement in MoCA scores one year after surgery. Univariate and multivariate logistic regression analyses were used to identify factors affecting improvement in cognitive status. A nomogram was developed to predict this factor. The discrimination and fitting performance were evaluated by receiver operating characteristics (ROC) analysis, calibration diagram, and decision curve analysis (DCA). Results: Among 103 patients, the mean improvement rate of the MoCA score was 37.3% and the median improvement rate was 27.3%, of which 64% improved cognition, 27% worsened cognition, and 8.7% remained unchanged. Logistic multivariate regression analysis showed that years of education, UPDRSIII drug use, MoCA Preop, and MMSE Preop scores were independent factors affecting the cognitive improvement rate. A nomogram model was subsequently developed. The C-index of the nomogram was 0.98 (95%CI, 0.97–1.00), and the area under the ROC was 0.98 (95%CI 0.97–1.00). The calibration plot and DCA demonstrated the goodness-of-fit between nomogram predictions and actual observations. Conclusion: Our nomogram could effectively predict the possibility of achieving good cognitive improvement one year after STN-DBS in patients with PD. This model has value in judging the expected cognitive improvement of patients with PD undergoing STN-DBS.
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spelling pubmed-92209032022-06-24 Nomogram to Predict Cognitive State Improvement after Deep Brain Stimulation for Parkinson’s Disease Chang, Bowen Ni, Chen Zhang, Weiwen Mei, Jiaming Xiong, Chi Chen, Peng Jiang, Manli Niu, Chaoshi Brain Sci Article Purpose: Parkinson’s disease (PD) is a common neurodegenerative disease, for which cognitive impairment is a non-motor symptom (NMS). Bilateral subthalamic nucleus deep brain stimulation (STN-DBS) is an effective treatment for PD. This study established a nomogram to predict cognitive improvement rate after STN-DBS in PD patients. Methods: We retrospectively analyzed 103 PD patients who underwent STN-DBS. Patients were followed up to measure improvement in MoCA scores one year after surgery. Univariate and multivariate logistic regression analyses were used to identify factors affecting improvement in cognitive status. A nomogram was developed to predict this factor. The discrimination and fitting performance were evaluated by receiver operating characteristics (ROC) analysis, calibration diagram, and decision curve analysis (DCA). Results: Among 103 patients, the mean improvement rate of the MoCA score was 37.3% and the median improvement rate was 27.3%, of which 64% improved cognition, 27% worsened cognition, and 8.7% remained unchanged. Logistic multivariate regression analysis showed that years of education, UPDRSIII drug use, MoCA Preop, and MMSE Preop scores were independent factors affecting the cognitive improvement rate. A nomogram model was subsequently developed. The C-index of the nomogram was 0.98 (95%CI, 0.97–1.00), and the area under the ROC was 0.98 (95%CI 0.97–1.00). The calibration plot and DCA demonstrated the goodness-of-fit between nomogram predictions and actual observations. Conclusion: Our nomogram could effectively predict the possibility of achieving good cognitive improvement one year after STN-DBS in patients with PD. This model has value in judging the expected cognitive improvement of patients with PD undergoing STN-DBS. MDPI 2022-06-09 /pmc/articles/PMC9220903/ /pubmed/35741644 http://dx.doi.org/10.3390/brainsci12060759 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
Zhang, Weiwen
Mei, Jiaming
Xiong, Chi
Chen, Peng
Jiang, Manli
Niu, Chaoshi
Nomogram to Predict Cognitive State Improvement after Deep Brain Stimulation for Parkinson’s Disease
title Nomogram to Predict Cognitive State Improvement after Deep Brain Stimulation for Parkinson’s Disease
title_full Nomogram to Predict Cognitive State Improvement after Deep Brain Stimulation for Parkinson’s Disease
title_fullStr Nomogram to Predict Cognitive State Improvement after Deep Brain Stimulation for Parkinson’s Disease
title_full_unstemmed Nomogram to Predict Cognitive State Improvement after Deep Brain Stimulation for Parkinson’s Disease
title_short Nomogram to Predict Cognitive State Improvement after Deep Brain Stimulation for Parkinson’s Disease
title_sort nomogram to predict cognitive state improvement after deep brain stimulation for parkinson’s disease
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9220903/
https://www.ncbi.nlm.nih.gov/pubmed/35741644
http://dx.doi.org/10.3390/brainsci12060759
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