Efficacy of Artificial Intelligence-Driven Predictive Telemonitoring in Reducing 30-Day Readmission Rates for Acute Decompensated Heart Failure

International Journal of Cardiology | Vol. 17, No. 3, March 2026 | pp. 165–172

DOI: 10.46882/2026/IJC/001842

Original Research Article

Efficacy of Artificial Intelligence-Driven Predictive Telemonitoring in Reducing 30-Day Readmission Rates for Acute Decompensated Heart Failure

Marcus Vance¹, Elena Rostova²

¹ Cardiovascular Research Centre, University of Manchester, Manchester, UK
² Institute of Cardiology, Almazov National Medical Research Centre, St. Petersburg, Russia

Abstract:
The burden of recurrent hospitalizations in acute decompensated heart failure (ADHF) demands advanced post-discharge management paradigms. This prospective, multi-center, randomized controlled trial evaluated the efficacy of an artificial intelligence (AI)-driven predictive telemonitoring system in mitigating 30-day readmissions. Following discharge for ADHF, 400 patients were randomized 1:1 to either standard guideline-directed care or AI-driven telemonitoring (using wearable biometric sensors linked to a cloud-based neural network that analyzed real-time variations in thoracic impedance, heart rate variability, and physical activity). The primary endpoint was the 30-day all-cause readmission rate. Secondary endpoints included cardiovascular mortality and patient-reported quality of life metrics. At 30 days post-discharge, the AI telemonitoring cohort demonstrated a statistically significant reduction in all-cause readmissions compared to the control group (11.5% vs. 23.5%, Hazard Ratio = 0.49, 95% Confidence Interval: 0.31-0.77, p < 0.001). The predictive algorithm successfully identified impending clinical decompensation an average of 4.5 ± 1.2 days before symptom onset, enabling proactive outpatient medication adjustments. No significant difference was observed in 30-day cardiovascular mortality (2.0% vs. 2.5%, p = 0.73), but the intervention group reported superior Minnesota Living with Heart Failure Questionnaire scores (mean difference: -8.4 points, p = 0.01). In conclusion, integrating AI-driven predictive telemonitoring into post-discharge protocols drastically reduces short-term readmissions for ADHF patients by facilitating early, data-driven therapeutic interventions.

Keywords: Heart failure, Artificial intelligence, Telemonitoring, Wearable sensors, Readmission prevention, Digital health

Received: December 14, 2025; Revised: January 18, 2026; Accepted: February 05, 2026; Published: March 04, 2026

Citation: Vance M, Rostova E. Efficacy of Artificial Intelligence-Driven Predictive Telemonitoring in Reducing 30-Day Readmission Rates for Acute Decompensated Heart Failure. International Journal of Cardiology, 2026; 17(3): 165–172. DOI: 10.46882/2026/IJC/001842

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