Temporal Variability of ECG Risk Markers and Clinical Outcomes in Non-Dilated Left Ventricular Cardiomyopathy

<b>Background/Objectives</b>: Non-dilated left ventricular cardiomyopathy (NDLVC) is a recently defined clinical entity associated with increased risk of ventricular arrhythmias (VA) and sudden cardiac death (SCD), despite preserved LV geometry. The role and temporal variability of noninvasive electrocardiographic (ECG) risk markers in this population remain insufficiently characterized. To assess the temporal variability of ECG-derived risk markers in patients with NDLVC and explore their association with major adverse cardiac events, including heart failure (HF) and VA hospitalization. <b>Methods</b>: We prospectively studied 55 patients with NDLVC who underwent cardiac magnetic resonance imaging and serial 24 h Holter monitoring, signal-averaged ECG, and standard 12-lead ECG over a one-year period. Patients were followed up for 39.5 ± 8.6 months. Nine ECG-based risk markers were analyzed, including premature ventricular contraction (PVC) burden, non-sustained ventricular tachycardia (NSVT) occurrence, its maximum rate and maximum beats, mean QTc interval, standard deviation of NN intervals (SDNN), deceleration capacity (DC), heart rate turbulence onset and slope (TO/TS), T-wave alternans (TWA), and late potentials. Clinical outcomes were HF and VA hospitalization. Logistic regression was used to evaluate associations between changes in ECG parameters and outcomes. <b>Results</b>: A change (from positive to negative and vice versa) in at least one ECG parameter was detected in 67.3% of patients, with the highest variability observed in TWA (34.5%), NSVT (23.6%), and PVC burden (23.6%). Despite this variability, only SDNN was significantly associated with increased risk of VA hospitalization during follow-up (OR = 0.98, 95% CI: 0.97-0.99, <i>p</i> = 0.006). No ECG changes were associated with HF hospitalization. <b>Conclusions</b>: Patients with NDLVC exhibit substantial temporal variability in noninvasive ECG risk markers. While most changes do not correlate with clinical events, an inverse association was found between SDNN and VA risk. These findings support the ongoing evaluation and the necessity to identify more effective risk stratification markers in this subgroup of patients.