Machine learning model and nomogram to predict the risk of heart failure hospitalization in peritoneal dialysis patients-Reference-Cited by-同舟云学术

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Machine learning model and nomogram to predict the risk of heart failure hospitalization in peritoneal dialysis patients

Published:2024-03-17 Issue:1 Volume:46 Page:
ISSN:0886-022X
Container-title:Renal Failure
language:en
Short-container-title:Renal Failure

Author:

Xu Liping¹,Cao Fang²³,Wang Lian²,Liu Weihua²,Gao Meizhu²,Zhang Li²,Hong Fuyuan²,Lin Miao²

Affiliation:

1. Department of Nephrology, The Second Affiliated Hospital of Xiamen Medical College, Xiamen, China

2. Department of Nephrology, Provincial Clinical College, Fujian Medical University, Fujian Provincial Hospital, Fuzhou, Fujian, China

3. Department of Nursing, Provincial Clinical College, Fujian Medical University, Fujian Provincial Hospital, Fuzhou, Fujian, China

Funder

Provincial Natural Science Foundation of Fujian Province

Young and Middle-Aged Scholars Program of Fujian Health Commission

Special Grant for Education and Research from Fujian Department of Finance

Xiamen Medical and Health Guiding Project

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/0886022X.2024.2324071

Reference41 articles.

1. Risks of Subsequent Hospitalization and Death in Patients with Kidney Disease

2. Epidemiology, contributors to, and clinical trials of mortality risk in chronic kidney failure

3. Design and validation of a model to predict early mortality in haemodialysis patients

4. Predicting First-Year Mortality in Incident Dialysis Patients with End-Stage Renal Disease - The UREA5 Study

5. Risk Score to Predict 1-Year Mortality after Haemodialysis Initiation in Patients with Stage 5 Chronic Kidney Disease under Predialysis Nephrology Care

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