Correction: Early Mortality Was Highly and Strongly Associated with Functional Status in Incident Japanese Hemodialysis Patients: A Cohort Study of the Large National Dialysis Registry

Development and validation of a model for predicting the risk of cardiovascular events in maintenance hemodialysis patients

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.

Development and validation of a nomogram for predicting the 6-months survival rate of patients undergoing incident hemodialysis in China

Background

The all-cause mortality of patients undergoing hemodialysis (HD) is higher than in the general population. The first 6 months after dialysis are important for new patients. The aim of this study was to develop and validate a nomogram for predicting the 6-month survival rate of HD patients.

Methods

A prediction model was constructed using a training cohort of 679 HD patients. Multivariate Cox regression analyses were performed to identify predictive factors. The identified factors were used to establish a nomogram. The performance of the nomogram was assessed using the C-index and calibration plots. The nomogram was validated by performing discrimination and calibration tests on an additional cohort of 173 HD patients.

Results

During a follow-up period of six months, 47 and 16 deaths occurred in the training cohort and validation cohort, respectively, representing a mortality rate of 7.3% and 9.2%, respectively. The nomogram comprised five commonly available predictors: age, temporary dialysis catheter, intradialytic hypotension, use of ACEi or ARB, and use of loop diuretics. The nomogram showed good discrimination in the training cohort [C-index 0.775(0.693–0.857)] and validation cohort [C-index 0.758(0.677–0.836)], as well as good calibration, indicating that the performance of the nomogram was good. The total score point was then divided into two risk classifications: low risk (0–90 points) and high risk (≥ 91 points). Further analysis showed that all-cause mortality was significantly different between the high-risk group and the low-risk group.

Conclusions

The constructed nomogram accurately predicted the 6-month survival rate of HD patients, and thus it can be used in clinical decision-making.