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持续气道正压通气(CPAP)治疗的睡眠呼吸暂停患者随访的新管理途径,包括数字医学和多模式远程监测。

New management pathways for follow-up of CPAP-treated sleep apnoea patients including digital medicine and multimodal telemonitoring.

作者信息

Pépin Jean-Louis, Baillieul Sébastien, Bailly Sébastien, Tamisier Renaud

机构信息

Grenoble Alpes University, HP2 Laboratory, INSERM U1300, Grenoble Alpes University Hospital, Grenoble, France

Grenoble Alpes University, HP2 Laboratory, INSERM U1300, Grenoble Alpes University Hospital, Grenoble, France.

出版信息

Thorax. 2024 Dec 23;80(1):52-61. doi: 10.1136/thorax-2024-221422.

Abstract

BACKGROUND

The ever-increasing number of patients diagnosed with obstructive sleep apnoea (OSA) and treated by long-term continuous positive airway pressure (CPAP) overstretches conventional follow-up pathways. New approaches to the management of CPAP-treated patient follow-up are needed to strike a balance between remote monitoring through digital technologies and in-person patient-healthcare-professional contacts. Focusing on the reshaping of the management of care pathways of CPAP-treated patients, with a specific focus on telemonitoring platforms, we aimed to review the evidence on how digital medicine and artificial intelligence (AI) tools are facilitating patient phenotyping and triage, risk stratification and the allocation of resources between the various healthcare professionals for an optimal follow-up of CPAP-treated patients.

PHENOTYPING

OSA is a heterogeneous condition with diverse phenotypes differing in symptoms, comorbidities, demographics, lifestyle and socioeconomic context. Different phenotypes are associated with different CPAP adherence patterns and differing long-term prognosis. This diversity demands greater plurality in management pathways with different types and levels of support to ensure treatment adherence and risk reduction for patients while easing the burden on health services. In multidimensional phenotyping, we discuss alternatives to the apnoea hypopnoea index (AHI) as a measure of OSA severity. Then we consider risk stratification taking advantage of the wealth of CPAP monitoring data already available in databases that can now be exploited using AI and machine learning to direct (stratify) patients into appropriate follow-up management pathways.

INTEGRATED CARE CLINICS FOR HIGH-RISK PATIENTS: We look at the role of integrated OSA care clinics particularly for the management of high-risk patients with low adherence and progression of comorbidities. Here, multidisciplinary teams might propose comorbidity management, and the use of connected wearable devices for long-term monitoring of physical activity, along with remote CPAP monitoring.

REMOTE MANAGEMENT PATHWAYS

The pros and cons of remote management pathways to replace in-person follow-up visits are considered, including the need to re-evaluate CPAP-device reimbursement policies in some countries. While remote CPAP monitoring has become the cornerstone of follow-up providing information on adherence and efficacy, the processing of alerts needs to be improved, particularly regarding mask changes and early detection of CPAP failures.

CHALLENGES

The implementation of CPAP monitoring alone, as well as its extension to multimodal monitoring, can present challenges that remain to be addressed (eg, access to digital care). The extent and components of remote follow-up must be adapted to each specific OSA phenotype. Finally, we give examples of certain patient phenotypes (eg, comorbid insomnia with OSA) with specific follow-up requirements, for which remote (even multimodal) monitoring alone has limitations and the intervention of both sleep specialists and/or their colleagues from other disciplines is needed.

CONCLUSION

Appropriately tailored combined digital and in-person CPAP follow-up pathways would present advantages both for patients with OSA and healthcare services.

摘要

背景

被诊断为阻塞性睡眠呼吸暂停(OSA)并接受长期持续气道正压通气(CPAP)治疗的患者数量不断增加,这使传统的随访途径不堪重负。需要新的CPAP治疗患者随访管理方法,以在通过数字技术进行远程监测与患者与医护人员的面对面接触之间取得平衡。我们专注于重塑CPAP治疗患者的护理途径管理,特别关注远程监测平台,旨在回顾有关数字医学和人工智能(AI)工具如何促进患者表型分析和分诊、风险分层以及在不同医护人员之间分配资源以实现CPAP治疗患者最佳随访的证据。

表型分析

OSA是一种异质性疾病,具有不同的表型,在症状、合并症、人口统计学、生活方式和社会经济背景方面存在差异。不同的表型与不同的CPAP依从模式和不同的长期预后相关。这种多样性要求管理途径更加多元化,提供不同类型和水平的支持,以确保患者坚持治疗并降低风险,同时减轻卫生服务的负担。在多维表型分析中,我们讨论了替代呼吸暂停低通气指数(AHI)作为OSA严重程度衡量指标的方法。然后,我们考虑利用数据库中已有的丰富CPAP监测数据进行风险分层,现在可以使用AI和机器学习来利用这些数据,将患者引导(分层)到适当的随访管理途径。

高危患者综合护理诊所

我们研究综合OSA护理诊所在管理依从性低和合并症进展的高危患者方面的作用。在这里,多学科团队可能会提出合并症管理方案,并使用连接的可穿戴设备对身体活动进行长期监测,同时进行远程CPAP监测。

远程管理途径

考虑了用远程管理途径取代面对面随访的利弊,包括在一些国家需要重新评估CPAP设备报销政策。虽然远程CPAP监测已成为随访的基石,可提供有关依从性和疗效的信息,但警报处理需要改进,特别是在面罩更换和CPAP故障早期检测方面。

挑战

仅实施CPAP监测及其扩展到多模式监测可能会带来一些有待解决的挑战(例如,获得数字护理服务)。远程随访的范围和组成部分必须适应每种特定的OSA表型。最后,我们给出了某些具有特定随访要求的患者表型(例如,OSA合并失眠)的示例,对于这些表型,仅远程(甚至多模式)监测存在局限性,需要睡眠专家和/或其他学科的同事进行干预。

结论

适当定制的数字与面对面相结合的CPAP随访途径对OSA患者和医疗服务都有好处。

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