Development and validation of a dynamic nomogram for acute kidney injury prediction in ICU patients with acute heart failure

Figure 1. LASSO regression analysis for variables selection in predicting AKI in AHF patients. Panel A shows the deviance (binomial) as a function of the log of the regularization parameter λ. The red dots represent the deviance at each λ value, with vertical dotted lines indicating the selected λ values based on cross-validation. Panel B illustrates the evolution of coefficients as a function of the log of λ, with each line representing a feature. As λ increases, the coefficients shrink, with some becoming exactly zero, indicating feature selection.

Figure 2. Nomogram for predicting the probability of AKI in AHF patients. (A) Nomogram for estimating the risk of AKI. Points are assigned for each variable, including sepsis, use of human albumin, mechanical ventilation, use of aminoglycosides, and serum creatinine (Scr) levels. The total points correspond to the probability of AKI. (B) An example of using the nomogram: input values for sepsis (No), use of human albumin (No), mechanical ventilation (No), use of aminoglycosides (No), and Scr (60 μmol/L). The predicted probability of AKI during ICU stay is 2.8%.

Figure 3. Calibration curves for the nomogram predicting AKI in AHF patients. (A) Calibration curve in the derivation set. The x-axis represents the nomogram-predicted probability of AKI, and the y-axis represents the actual probability of AKI. The diagonal dashed line represents a perfect prediction by an ideal model. The solid line shows the performance of the nomogram, where a closer fit to the diagonal line indicates better predictive accuracy. The dotted line indicates apparent predictions without bias correction. (B) Calibration curve in the validation set. The axes and lines are the same as in (A). The solid line represents the bias-corrected performance of the nomogram, showing the agreement between predicted and actual outcomes in the validation cohort.

Figure 4. Decision curve analysis for the nomogram predicting AKI in AHF patients. Decision curve analysis comparing the net benefits of the nomogram and individual predictors across a range of high-risk thresholds. The x-axis represents the high-risk threshold for predicting AKI, and the y-axis represents the net benefit. The red line represents the nomogram, showing the highest net benefit across most thresholds compared to individual predictors such as sepsis, use of human albumin, mechanical ventilation, use of aminoglycosides, and Scr.