ArticleScientific reports2024
Development and validation of a model for predicting the risk of cardiovascular events in maintenance hemodialysis patients.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic review and meta-analysis of cardiovascular event risk prediction models in maintenance hemodialysis patients.Scientific reports · 2025Pooled it
- A time-updated scoring system derived from a nomogram to predict 3-month mortality in maintenance hemodialysis patients.Frontiers in aging · 2026Article
- Predicting cardiovascular events in hemodialysis patients based on the fusion of physicochemical indicators and tongue images: a prospective and multicenter study.Frontiers in physiology · 2026Article
- Construction of a nomogram prediction model for individualized prediction of the risk of left ventricular diastolic dysfunction in maintenance hemodialysis patients.Frontiers in cardiovascular medicine · 2026Article
- Prediction of ultrafiltration volume in maintenance hemodialysis patients using an artificial neural network model based on body composition information.BMC medical informatics and decision making · 2025Article
- Prognostic significance of the hs-CRP/Alb ratio for cardiovascular events in patients with end-stage renal disease undergoing maintenance hemodialysis.American journal of translational research · 2024Article
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6 authors.
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Abstract
The mortality rates for patients undergoing hemodialysis (HD) remain unacceptably high compared to the general population, and more specific information about the causes of death is not known. The study aimed to develop and validate a risk prediction model that uses common clinical factors to predict the probability of cardiovascular events in maintenance hemodialysis (MHD) patients. The study involved 3488 adult patients who received regular scheduled hemodialysis treatment at 20 hemodialysis centers in southwest China between June 2015 and August 2020, with follow-up until August 2021. The optimal parameter set was identified by multivariable Cox regression analyses and Cross-LASSO regression analyses and was used to establish a nomogram for predicting the risk of cardiovascular events in maintenance hemodialysis patients at 3 and 5 years. The performance of the model was evaluated using the consistency index (Harrell's C-index), the area under the receiver operating characteristic (ROC) curve, and calibration plots. The model was validated by tenfold cross-validation and bootstrapping with 1000 resamples. In the derivation cohort, the model yields an AUC of 0.764 [95% confidence interval (CI), 0.737-0.790] and 0.793 [CI, 0.757-0.829] for predicting the risk of cardiovascular events of MHD patients at 3 and 5 years. In the internal validation cohort AUC of 0.803 [95% CI, 0.756-0.849], AUC of 0.766 [95% CI, 0.686-0.846], and the external validation cohort AUC of 0.826 [95% CI, 0.765-0.888], AUC of 0.817 [95% CI, 0.745-0.889] at 3 and 5 years. The model's calibration curve is close to the ideal diagonal. By tenfold cross-validation analyses, the 3- and 5-year risk of cardiovascular events (AUC 0.732 and 0.771, respectively). By the bootstrap resampling method, the derivation cohort and validation cohort (Harrell's C-index 0.695 and 0.667, respectively) showed good uniformity with the model. The constructed model accurately predicted cardiovascular events of MHD patients in the 3rd and 5th years after dialysis. And the further research is needed to determine whether use of the risk prediction tool improves clinical outcomes.
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