Resting heart rate as an independent predictor of major adverse cardiovascular events in patients receiving maintenance hemodialysis: a prospective cohort study

Figures

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  Figure 1. Nomogram based on the multivariable logistic regression model. Each predictor (RHR group, HADS group, diabetes, UA, iPTH) contributes a point score; and total points correspond to the predicted probability of total MACE. RHR: Resting heart rate; HADS: Hospital Anxiety and Depression Scale; UA: Uric acid; iPTH: Intact parathyroid hormone.

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  Figure 2. Receiver operating characteristic (ROC) curve of the multivariable logistic regression model for predicting total major adverse cardiovascular events (MACE). The area under the ROC curve (AUC) was 0.820 (95% confidence interval [CI]: 0.771–0.868). The black dot indicates the optimal cut-off value determined by the Youden index (cut-off = 0.444), corresponding to a sensitivity (Se) of 0.652 and specificity (Sp) of 0.843. The diagonal gray line represents the reference line of no discrimination (AUC = 0.5). MACE: Major adverse cardiovascular events; ROC: Receiver operating characteristic; AUC: Area under the curve; CI: Confidence interval; Se: Sensitivity; Sp: Specificity.

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  Figure 3. Internal validation of the multivariable logistic regression model using bootstrap resampling (B = 1,000). The figure compares the apparent (blue), bootstrap test (green), and optimism-corrected (yellow) performance estimates across multiple validation metrics. Dxy represents Somers’ rank correlation; R2 represents explained variation; intercept and slope reflect calibration performance; Emax indicates the maximum calibration error; D, U, and Q are components of the Brier score decomposition; B represents the Brier score; g and gp are discrimination indices related to model prediction performance.

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  Figure 4. Calibration plot of the multivariable logistic regression model for predicting total major adverse cardiovascular events (MACE). The x-axis represents the predicted probability of MACE, and the y-axis represents the observed probability. The dashed diagonal line represents the ideal calibration line, indicating perfect agreement between predicted and observed probabilities. The dotted line represents the apparent calibration of the original model, and the solid line represents the bootstrap bias-corrected calibration curve based on 1,000 resamples. MACE: Major adverse cardiovascular events.

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  Figure 5. Decision curve analysis (DCA) of the multivariable logistic regression model for predicting total major adverse cardiovascular events (MACE). The x-axis represents the threshold probability, and the y-axis represents the standardized net benefit. The red line represents the prediction model, the gray line (“All”) represents the strategy of treating all patients as high risk, and the black horizontal line (“None”) represents the strategy of treating no patients as high risk. The lower x-axis shows the corresponding cost-to-benefit ratios for different threshold probabilities. DCA: Decision curve analysis; MACE: Major adverse cardiovascular events.