TRI-based heart rate variability parameterisation: advancing autonomic dysfunction assessment in diabetes and aging—A cross-sectional observational study

Abstract

This cross-sectional observational study introduces the T-R interval (TRI), a novel electrocardiographic parameter designed to improve heart rate variability (HRV) assessment in ageing and diabetic populations. Defined as the R-R interval (RRI) minus the heart rate-corrected RT interval (RTc), TRI incorporates both depolarisation and repolarisation phases of the cardiac cycle, thereby offering deeper insights into autonomic function. A total of 126 participants, including 58 individuals with type 2 diabetes mellitus and 68 healthy controls, were assessed using conventional HRV indices. These included the low-to-high frequency power ratio (LHR), the short-to-long variability ratio (SSR), and the baroreflex entropy index (BEI), all of which were calculated from both RRI and TRI data. TRI-based indices demonstrated superior sensitivity in detecting autonomic dysfunction. Significant group differences were observed for TRI-derived MSE_LS (mean difference = 0.205, 95 % CI: 0.093–0.317, p = 0.036), SSR (mean difference =  − 0.083, 95 % CI: −0.136–−0.029, p = 0.051), and BEI (mean difference = 0.205, 95 % CI: 0.093–0.318, p = 0.002), while their RRI-based equivalents did not reach statistical significance. ROC curve analysis showed improvements in the area under the curve (AUC) when TRI was used as the input parameter, with gains of 5.9 % for MSE_LS, 10.6 %for SSR, and 6.1 % for BEI. Logistic regression further identified TRI-based BEI as a protective factor against new-onset T2DM (OR = 0.058; 95 % CI: 0.009–0.378; p = 0.003). These findings suggest that TRI improves the diagnostic performance of HRV analysis and may support earlier detection of autonomic dysfunction, especially in clinical and wearable monitoring settings.