Fig. 6: Extrapolation of AIHFLevel to the heterogeneous populations from BIDM center.

a Proportional hazard assumption of Cox regression for AIHFLevel demonstrated no significant correlation between Schoenfeld residuals and time. Statistical tests: two-sided Schoenfeld residuals test. b Analysis of the non-linear relationship between AIHFLevel and ACM risk using restricted cubic spline regression within the external BIDMC cohort (P_overall <0.0001, and P_non-linear < 0.0001). Non-linear patterns indicating a ‘fast-to-low’ increase in ACM risk associated with rising AIHFLevel. Univariate Cox regression analysis highlighted the AIHFLevel as a significant clinical predictor for ACM, with a HR of 1.956 (95% CI = 1.838-2.082). Statistic test: two-sided Wald test. Line chart displaying the estimated logarithm HRs represented by blue lines, along with 95% CIs indicated by shading. c Cumulative Kaplan-Meier estimates delineating time to the survival difference for ACM stratified by AIHFLevel. d Time-dependent ROC analysis for predicting ACM. AUCs at 1-, 2-, 3-, 4-year demonstrating strong predictive accuracy: 0.788, 0.816, 0.824, 0.846. e Calibration curves depicting the predicted versus observed probabilities of ACM as evaluated by AIHFLevel. f DCA illustrating net benefit curves of AIHFLevel for predicting ACM. g Distribution of AIHFLevel across three prognostic states in the BIDMC cohort (P < 0.0001, n = 1024). Statistic tests: two-sided wilcoxon test, as determined by established stratification criteria. Centre line indicates median, bounds of box indicate 25th and 75th percentiles, and whiskers indicate minimum and maximum. h Kaplan-Meier curves showing the survival difference for ACM across three prognostic states. i Trinormal snapshot of ROC surface demonstrating the discriminatory power of AIHFLevel on three prognostic states. j t-SNE dimension reduction analysis spatially segregated samples by prognostic states into two dimensions, showcasing effective and stable discrimination. k Multivariate Cox regression of AIHFLevel for ACM risk in the BIDMC (n = 1024). Upon adjusting for potential confounders, AIHFLevel demonstrated independent prognostic value. Dot plots illustrated the adjusted hazard ratios with the horizontal line indicating the 95% confidence interval for each variable. Bar graphs highlighted the -log10(adjusted P-values) to denote statistical significance levels. Statistic test: two-sided Wald test. l Comparative predictive efficacy of AIHFLevel against clinical traits in the BIDMC (n = 1024). C-index was presented with 95% CI. Statistic tests: two-sided z-score test. m Comparative predictive efficacy of AIHFLevel against established risk and prognostic models in the BIDMC (n = 1024). The analysis, visualized through bar graphs for the C-index and line graphs for the IBS, using two-sided z-score test to ascertain significance: *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.