4.4 Article

Prediction model for cognitive impairment in maintenance hemodialysis patients

期刊

BMC NEUROLOGY
卷 23, 期 1, 页码 -

出版社

BMC
DOI: 10.1186/s12883-023-03407-z

关键词

Prediction model; Cognitive impairment; End-stage renal disease; Maintenance hemodialysis

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This study explored the risk factors for cognitive impairment in patients undergoing maintenance hemodialysis (MHD) and constructed a predictive model with a high predictive value for cognitive impairment. The factors associated with an increased risk of cognitive impairment in MHD patients were age, duration of dialysis, and smoking status.
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:16.86482.86; 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.

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