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Transcranial sonography with clinical and demographic characteristics to predict cognitive impairment in PD: a longitudinal study

BACKGROUND: Parkinson’s disease (PD) is a neurodegenerative disease and is clinically characterized by a series of motor symptoms (MS) and nonmotor symptoms (NMS). NMS often appear before MS, while cognitive impairment mostly occurs within a few years after the diagnosis of PD. Therefore, we aimed t...

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Autores principales: Chen, Zhiguang, Zhang, Wei, He, Wen, Guang, Yang, Yu, Tengfei, Du, Yue, Li, Rui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9837901/
https://www.ncbi.nlm.nih.gov/pubmed/36639620
http://dx.doi.org/10.1186/s12883-023-03057-1
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author Chen, Zhiguang
Zhang, Wei
He, Wen
Guang, Yang
Yu, Tengfei
Du, Yue
Li, Rui
author_facet Chen, Zhiguang
Zhang, Wei
He, Wen
Guang, Yang
Yu, Tengfei
Du, Yue
Li, Rui
author_sort Chen, Zhiguang
collection PubMed
description BACKGROUND: Parkinson’s disease (PD) is a neurodegenerative disease and is clinically characterized by a series of motor symptoms (MS) and nonmotor symptoms (NMS). NMS often appear before MS, while cognitive impairment mostly occurs within a few years after the diagnosis of PD. Therefore, we aimed to predict the risk factors for cognitive impairment (CI) in PD patients based on transcranial sonography, clinical symptoms, and demographic characteristics. METHODS: Based on the occurrence time of CI, a total of 172 PD patients were divided into non-CI (N-CI, n = 48), CI at the first treatment (F-CI, n = 58), and CI at the last treatment (L-CI, n = 66) groups. Clinical data (including MS and NMS) and ultrasonic data of all patients at the first treatment and the last treatment were collected retrospectively. Independent samples t tests were used to compare continuous data, and chi-square tests were used to compare categorical data. The risk factors for CI and Parkinson’s disease dementia were identified by logistic regression analysis, and an ROC curve was established to explore the diagnostic efficacy. RESULTS: 1) The age of onset, first treatment and smoking history of CI patients were significantly different from those of N-CI patients. When age of first treatment ≥61 years was considered the boundary value to diagnose CI, the sensitivity and specificity were 77.40 and 66.70%, respectively. 2) The severity of depression was significantly different between F-CI and N-CI patients at the first treatment, while the cumulative and new or aggravated memory deficit was significantly different between the L-CI and N-CI patients at the last treatment. 3) There was a significant difference in TCS grading between the first and last treatment in L-CI patients. 4) Depression, sexual dysfunction, and olfactory dysfunction in NMS were independent risk factors for CI during the last treatment. 5) The sensitivity and specificity of predicting CI in PD patients were 81.80 and 64.60%, respectively. CONCLUSIONS: PD patients with CI were older, and most of them had a history of smoking. Furthermore, there was good diagnostic efficiency for predicting CI in PD via TCS combined with clinical characteristics (especially NMS).
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spelling pubmed-98379012023-01-14 Transcranial sonography with clinical and demographic characteristics to predict cognitive impairment in PD: a longitudinal study Chen, Zhiguang Zhang, Wei He, Wen Guang, Yang Yu, Tengfei Du, Yue Li, Rui BMC Neurol Research BACKGROUND: Parkinson’s disease (PD) is a neurodegenerative disease and is clinically characterized by a series of motor symptoms (MS) and nonmotor symptoms (NMS). NMS often appear before MS, while cognitive impairment mostly occurs within a few years after the diagnosis of PD. Therefore, we aimed to predict the risk factors for cognitive impairment (CI) in PD patients based on transcranial sonography, clinical symptoms, and demographic characteristics. METHODS: Based on the occurrence time of CI, a total of 172 PD patients were divided into non-CI (N-CI, n = 48), CI at the first treatment (F-CI, n = 58), and CI at the last treatment (L-CI, n = 66) groups. Clinical data (including MS and NMS) and ultrasonic data of all patients at the first treatment and the last treatment were collected retrospectively. Independent samples t tests were used to compare continuous data, and chi-square tests were used to compare categorical data. The risk factors for CI and Parkinson’s disease dementia were identified by logistic regression analysis, and an ROC curve was established to explore the diagnostic efficacy. RESULTS: 1) The age of onset, first treatment and smoking history of CI patients were significantly different from those of N-CI patients. When age of first treatment ≥61 years was considered the boundary value to diagnose CI, the sensitivity and specificity were 77.40 and 66.70%, respectively. 2) The severity of depression was significantly different between F-CI and N-CI patients at the first treatment, while the cumulative and new or aggravated memory deficit was significantly different between the L-CI and N-CI patients at the last treatment. 3) There was a significant difference in TCS grading between the first and last treatment in L-CI patients. 4) Depression, sexual dysfunction, and olfactory dysfunction in NMS were independent risk factors for CI during the last treatment. 5) The sensitivity and specificity of predicting CI in PD patients were 81.80 and 64.60%, respectively. CONCLUSIONS: PD patients with CI were older, and most of them had a history of smoking. Furthermore, there was good diagnostic efficiency for predicting CI in PD via TCS combined with clinical characteristics (especially NMS). BioMed Central 2023-01-13 /pmc/articles/PMC9837901/ /pubmed/36639620 http://dx.doi.org/10.1186/s12883-023-03057-1 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Chen, Zhiguang
Zhang, Wei
He, Wen
Guang, Yang
Yu, Tengfei
Du, Yue
Li, Rui
Transcranial sonography with clinical and demographic characteristics to predict cognitive impairment in PD: a longitudinal study
title Transcranial sonography with clinical and demographic characteristics to predict cognitive impairment in PD: a longitudinal study
title_full Transcranial sonography with clinical and demographic characteristics to predict cognitive impairment in PD: a longitudinal study
title_fullStr Transcranial sonography with clinical and demographic characteristics to predict cognitive impairment in PD: a longitudinal study
title_full_unstemmed Transcranial sonography with clinical and demographic characteristics to predict cognitive impairment in PD: a longitudinal study
title_short Transcranial sonography with clinical and demographic characteristics to predict cognitive impairment in PD: a longitudinal study
title_sort transcranial sonography with clinical and demographic characteristics to predict cognitive impairment in pd: a longitudinal study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9837901/
https://www.ncbi.nlm.nih.gov/pubmed/36639620
http://dx.doi.org/10.1186/s12883-023-03057-1
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