Cargando…

Prediction model for cognitive impairment in maintenance hemodialysis patients

PURPOSE: To explore the risk factors for cognitive impairment in patients undergoing maintenance hemodialysis (MHD) and construct a predictive model for cognitive impairment. METHODS: A total of 146 patients with end-stage renal disease (ESRD) undergoing MHD were recruited at our hospital between De...

Descripción completa

Detalles Bibliográficos
Autores principales: Chen, Ding, Xiao, Chang, Xiao, Wangyan, Lou, Linjing, Gao, Zhuo, Li, Xinlun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10568884/
https://www.ncbi.nlm.nih.gov/pubmed/37828422
http://dx.doi.org/10.1186/s12883-023-03407-z
_version_ 1785119447668752384
author Chen, Ding
Xiao, Chang
Xiao, Wangyan
Lou, Linjing
Gao, Zhuo
Li, Xinlun
author_facet Chen, Ding
Xiao, Chang
Xiao, Wangyan
Lou, Linjing
Gao, Zhuo
Li, Xinlun
author_sort Chen, Ding
collection PubMed
description PURPOSE: To explore the risk factors for cognitive impairment in patients undergoing maintenance hemodialysis (MHD) and construct a predictive model for cognitive impairment. METHODS: A total of 146 patients with end-stage renal disease (ESRD) undergoing MHD were recruited at our hospital between December 2021 and April 2022. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA), and scores of < 26 were considered indicative of cognitive impairment. Risk factors were identified using a multivariate logistic regression model, and a receiver operating characteristic curve was applied to construct the prediction model. Cognitive impairment risk was categorized using a multifactorial prediction model based on the weight of evidence. RESULTS: 46 patients with cognitive impairment were identified, with a prevalence of 31.5% in ESRD patients undergoing MHD. Multivariate logistic regression analyses indicated that the following factors were associated with an increased risk of cognitive impairment in patients undergoing MHD: aged 55.0–64.0 years (OR:6.24; 95%CI:1.81–21.48; P = 0.001), aged 65.0–74.0 years (OR:16.10; 95%CI:4.03–64.37; P < 0.001), aged ≥ 75.0 years (OR:90.22; 95%CI:16.86-482.86; P < 0.001), duration of dialysis ≥ 5 years (OR:3.99; 95%CI:1.58–10.04; P = 0.003), and current smoker (OR:4.61; 95%CI:1.46–14.57; P = 0.009). The predictive value of the constructed model based on the aforementioned factors for cognitive impairment was 84% (95%CI,77-91%). The prevalence of cognitive impairment for patients at low, moderately low, moderately high, and high risk was 0% (95%CI:0-17%), 10% (95%CI:3-22%), 32% (95%CI:16-52%), and 65% (95%CI:50-78%), respectively. CONCLUSIONS: This study constructed a multifactorial prediction model with a high predictive value for cognitive impairment in patients with ESRD undergoing MHD.
format Online
Article
Text
id pubmed-10568884
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-105688842023-10-13 Prediction model for cognitive impairment in maintenance hemodialysis patients Chen, Ding Xiao, Chang Xiao, Wangyan Lou, Linjing Gao, Zhuo Li, Xinlun BMC Neurol Research PURPOSE: To explore the risk factors for cognitive impairment in patients undergoing maintenance hemodialysis (MHD) and construct a predictive model for cognitive impairment. METHODS: A total of 146 patients with end-stage renal disease (ESRD) undergoing MHD were recruited at our hospital between December 2021 and April 2022. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA), and scores of < 26 were considered indicative of cognitive impairment. Risk factors were identified using a multivariate logistic regression model, and a receiver operating characteristic curve was applied to construct the prediction model. Cognitive impairment risk was categorized using a multifactorial prediction model based on the weight of evidence. RESULTS: 46 patients with cognitive impairment were identified, with a prevalence of 31.5% in ESRD patients undergoing MHD. Multivariate logistic regression analyses indicated that the following factors were associated with an increased risk of cognitive impairment in patients undergoing MHD: aged 55.0–64.0 years (OR:6.24; 95%CI:1.81–21.48; P = 0.001), aged 65.0–74.0 years (OR:16.10; 95%CI:4.03–64.37; P < 0.001), aged ≥ 75.0 years (OR:90.22; 95%CI:16.86-482.86; P < 0.001), duration of dialysis ≥ 5 years (OR:3.99; 95%CI:1.58–10.04; P = 0.003), and current smoker (OR:4.61; 95%CI:1.46–14.57; P = 0.009). The predictive value of the constructed model based on the aforementioned factors for cognitive impairment was 84% (95%CI,77-91%). The prevalence of cognitive impairment for patients at low, moderately low, moderately high, and high risk was 0% (95%CI:0-17%), 10% (95%CI:3-22%), 32% (95%CI:16-52%), and 65% (95%CI:50-78%), respectively. CONCLUSIONS: This study constructed a multifactorial prediction model with a high predictive value for cognitive impairment in patients with ESRD undergoing MHD. BioMed Central 2023-10-12 /pmc/articles/PMC10568884/ /pubmed/37828422 http://dx.doi.org/10.1186/s12883-023-03407-z Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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, Ding
Xiao, Chang
Xiao, Wangyan
Lou, Linjing
Gao, Zhuo
Li, Xinlun
Prediction model for cognitive impairment in maintenance hemodialysis patients
title Prediction model for cognitive impairment in maintenance hemodialysis patients
title_full Prediction model for cognitive impairment in maintenance hemodialysis patients
title_fullStr Prediction model for cognitive impairment in maintenance hemodialysis patients
title_full_unstemmed Prediction model for cognitive impairment in maintenance hemodialysis patients
title_short Prediction model for cognitive impairment in maintenance hemodialysis patients
title_sort prediction model for cognitive impairment in maintenance hemodialysis patients
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10568884/
https://www.ncbi.nlm.nih.gov/pubmed/37828422
http://dx.doi.org/10.1186/s12883-023-03407-z
work_keys_str_mv AT chending predictionmodelforcognitiveimpairmentinmaintenancehemodialysispatients
AT xiaochang predictionmodelforcognitiveimpairmentinmaintenancehemodialysispatients
AT xiaowangyan predictionmodelforcognitiveimpairmentinmaintenancehemodialysispatients
AT loulinjing predictionmodelforcognitiveimpairmentinmaintenancehemodialysispatients
AT gaozhuo predictionmodelforcognitiveimpairmentinmaintenancehemodialysispatients
AT lixinlun predictionmodelforcognitiveimpairmentinmaintenancehemodialysispatients