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一种新型、无电缆、基于贴片且人工智能增强的心电图监测系统的性能与安全性:一项对比研究。

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

作者信息

Thomas Owain, Linnér Rikard, Dardashti Alain

机构信息

Anesthesiology and Intensive Care, Department of Clinical Sciences, Lund, Section II, Skånes Universitetssjukhus Lund 221 85, Sweden.

Thoracic Surgery, Department of Clinical Sciences, Lund, Section II, Skånes Universitetssjukhus  Lund 221 85, Sweden.

出版信息

Eur Heart J Digit Health. 2025 May 26;6(5):888-896. doi: 10.1093/ehjdh/ztaf059. eCollection 2025 Sep.

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 ( < 0.0001), and lower rates of high priority false alarms (0.3% vs. 40%; < 0.0001). Monitoring interruptions were markedly reduced (114 s/day vs. 584 s/day; < 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; < 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.

摘要

目的

在疾病的关键阶段通常需要进行心电图监测。为了评估现代技术和先进分析算法人工智能与标准护理相比的作用,我们对一种新型的、无电缆、基于贴片且人工智能增强的心电图系统(CardioSenseSystem)与标准护理(SOC)心电图监测进行了前瞻性的直接比较。瑞典斯科讷大学医院这所大型大学医院中接受心脏手术的患者同时由这两种系统进行监测,并记录警报和监测中断情况。

方法与结果

招募了49名患者。CardioSenseSystem系统显示出显著更高的灵敏度,正确检测到364次关键红色警报,而SOC为12次(<0.0001),且高优先级误报率更低(0.3%对40%;<0.0001)。监测中断显著减少(114秒/天对584秒/天;<0.0001)。每位患者每天的处理时间显著更短(256秒对880秒)。CardioSenseSystem系统还减少了警报疲劳,每位患者每小时的干扰更少(0.03对0.11;<0.0001)。

结论

CardioSenseSystem系统在心脏手术后患者中比传统心电图监测具有显著优势。其高灵敏度、减少误报、更少监测中断以及缩短处理时间表明,它可能改善患者预后并提高临床效率,值得在急性护理环境中更广泛地应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a696/12450504/144b9dfb5ab8/ztaf059_ga.jpg

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