Performance and safety of a novel, cable-free, patch-based, and AI-enhanced ECG monitoring system: a comparative study.

Abstract

Aims: ECG monitoring is often required during critical phases of illness. To evaluate the role of modern technology and advanced analytical algorithms artificial intelligence compared with standard-of care, we undertook a prospective, head-to-head comparison of a novel, cable-free, patch-based, and AI-enhanced electrocardiography system (CardioSenseSystem) with standard of care (SOC) ECG monitoring. Patients who had undergone cardiac surgery at a large university hospital (Skåne University Hospital, Sweden) were simultaneously monitored by both systems, and alarms and monitoring interruptions were recorded.

Methods and results: Forty-nine patients were recruited. The CardioSenseSystem system demonstrated significantly higher sensitivity, correctly detecting 364 critical red alarms vs. 12 for SOC (P < 0.0001), and lower rates of high priority false alarms (0.3% vs. 40%; P < 0.0001). Monitoring interruptions were markedly reduced (114 s/day vs. 584 s/day; P < 0.0001). Handling time per patient day was significantly shorter (256 s vs. 880 s). The CardioSenseSystem system also reduced alarm fatigue, with fewer disturbances per patient per hour (0.03 vs. 0.11; P < 0.0001).

Conclusion: The CardioSenseSystem system delivered significant advantages over conventional ECG monitoring in post-cardiac surgery patients. Its high sensitivity, reduced false alarms, fewer monitoring interruptions, and decreased handling time suggest that it may enhance patient outcomes and clinical efficiency, warranting broader application in acute-care settings.