对话式人工智能用于心力衰竭的远程监测:一项前性受控试点研究
Aleix Olivella1,2, Ana B Méndez Fernández1,2, Emmanuel Giménez García3,4
1Cardiology Department, Vall D'Hebron University Hospitalm Vall D'Hebron Institut de Recerca, Passeig de la Vall d'Hebron 119-129, 08035 Barcelona, Spain.
European heart journal. Digital health
|March 12, 2026
概括
对心力衰竭 (HF) 监测的对话式人工智能系统 (CAIS) 是可行的,并且受到好评. 这种人工智能辅助的随访显示了减少住院治疗和改善患者治疗结果的潜力.
科学领域:
- 心脏病学 心脏病学
- 医疗保健中的人工智能
- 数字健康数字健康
背景情况:
- 心力衰竭 (HF) 管理需要可扩展的策略,用于早期检测脱补偿和减少住院治疗.
- 目前对高压的远程监控解决方案往往具有侵入性,复杂性或与临床工作流程集成不良.
- 需要自动化后续系统来改善患者护理并减少医疗保健负担.
研究的目的:
- 评估对话式人工智能系统 (CAIS) 的可行性和临床影响,用于心力衰竭患者的自动电话随访.
- 评估系统的可接受性,护士的工作量和患者报告的结果.
- 探索CAIS对关键临床终点的影响,包括死亡率和住院病例.
主要方法:
- 一项前性,非随机化,受控的可行性研究,涉及86名心力衰竭门诊患者.
- 使用自然语言处理收集症状和生命体征的每周人工智能辅助后续电话.
- 警报是由心力衰竭护士管理的;40名患者接受了通常的照顾,以供比较.
主要成果:
- 高通话完成率 (91.7%) 和积极的患者满意度 (平均8.72±1.81).
- 在CAIS组的KCCQ-12得分显著改善 (+7.13分,P=0.019).
- 探索性分析表明,在CAIS组中,全因死亡或HF住院事件较少 (HR 0.39,P=0.041) 和心血管死亡率较低 (1.2%对10.0%,P=0.035).
结论:
- 交谈式人工智能系统的后续对心力衰竭患者来说是一种可行的,低资源和受欢迎的干预措施.
- 该系统展示了改善临床结果的探索信号,包括减少死亡率和住院治疗.
- 这种务实和可扩展的方法需要在随机对照试验中进一步验证,以确认其在增强心力衰竭护理方面的有效性.
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