Fig. 5: Sensitivity analysis for AIHFLevel.
From: AI hybrid survival assessment for advanced heart failure patients with renal dysfunction
a Cumulative Kaplan–Meier estimates of the time to the first adjudicated occurrence of MACE within the Meta cohort, with log-rank test results indicating statistical significance. b Kaplan-Meier curve showing the incidence difference for MACE across three prognostic states, with log-rank test results indicating statistical significance. c Calibration curve depicting the predicted versus observed probabilities of MACE at 6, 12, and 24 months, as evaluated by AIHFLevel within Meta cohort (n = 712). d DCA illustrating net benefit curves of AIHFLevel for predicting MACE at 6, 12, and 24 months within Meta cohort (n = 712). The X-axis represented the threshold probability for critical care outcomes, while the Y-axis quantified the net benefit. e Subgroup analysis estimating AIHFLevel’s prognostic value for MACE across different subgroups. Statistic test: two-sided Wald test. The length of the horizontal line represented the 95% confidence interval for each subgroup, with a vertical dotted line indicating the hazard ratio of all patients. The vertical solid line denoted HR = 1. HR > 1 indicated AIHFLevel as a risk prognostic factor. f Time-dependent ROC analysis for predicting MACE within Meta cohort (n = 712). AUCs at 6-, 12-, 24-, and 30-months demonstrating strong predictive accuracy: 0.825, 0.848, 0.861, 0.846. g Comparative AIHFLevel’s efficacy in assessing ACM and MACE within the Meta cohort (n = 712) using C-index and IBS. C-index was presented with 95% confidence interval (CI).
