Svaža Artis, Freimanis Dāvis, Zariņa Dana, Osipovs Pavels, Kistkins Svjatoslavs, Ankudovičs Vitālijs, Sabeļnikovs Olegs, Pīrāgs Valdis, Chizhov Yuriy, Bliznuks Dmitrijs
Sleep Disorder Clinic, LV-1002 Riga, Latvia.
Department of Internal Medicine, Pauls Stradiņš Clinical University Hospital, LV-1002 Riga, Latvia.
J Clin Med. 2024 Jan 28;13(3):757. doi: 10.3390/jcm13030757.
Current obstructive sleep apnea treatment relies on manual PAP titration, but it has limitations. Complex interactions during titration and variations in SpO data accuracy pose challenges. Patients with co-occurring chronic hypercapnia may require precise oxygen titration. To address these issues, we propose a Clinical Decision Support System using Markov decision processes.
This study, compliant with data protection laws, focused on adults with OSA-induced hypoxemia utilizing supplemental oxygen and CPAP/BiPAP therapy. PAP titration, conducted over one night, involved vigilant monitoring of vital signs and physiological parameters. Adjustments to CPAP pressure, potential BiLevel transitions, and supplemental oxygen were precisely guided by patient metrics. Markov decision processes outlined three treatment actions for disorder management, incorporating expert medical insights.
In our study involving 14 OSA patients (average age: 63 years, 27% females, BMI 41 kg m), significant improvements were observed in key health parameters after manual titration. The initial AHI of 61.8 events per hour significantly decreased to an average of 18.0 events per hour after PAP and oxygen titration ( < 0.0001), indicating a substantial reduction in sleep-disordered breathing severity. Concurrently, SpO levels increased significantly from an average of 79.7% before titration to 89.1% after titration ( < 0.0003). Pearson correlation coefficients demonstrated aggravation of hypercapnia in 50% of patients ( = 5) with initial pCO < 55 mmHg during the increase in CPAP pressure. However, transitioning to BiPAP exhibited a reduction in pCO levels, showcasing its efficacy in addressing hypercapnia. Simultaneously, BiPAP therapy correlated with a substantial increase in SpO, underscoring its positive impact on oxygenation in OSA patients. Markov Decision Process analysis demonstrated realistic patient behavior during stable night conditions, emphasizing minimal apnea and good toleration to high CPAP pressure.
The development of a framework for Markov decision processes of PAP and oxygen titration algorithms holds promise for providing algorithms for improving pCO and SpO values. While challenges remain, including the need for high-quality data, the potential benefits in terms of patient management and care optimization are substantial, and this approach represents an exciting frontier in the realm of telemedicine and respiratory healthcare.
目前阻塞性睡眠呼吸暂停的治疗依赖于手动持续气道正压通气（PAP）滴定，但存在局限性。滴定过程中的复杂相互作用以及脉搏血氧饱和度（SpO）数据准确性的变化带来了挑战。同时患有慢性高碳酸血症的患者可能需要精确的氧滴定。为解决这些问题，我们提出一种使用马尔可夫决策过程的临床决策支持系统。
本研究符合数据保护法，聚焦于使用补充氧气和持续气道正压通气（CPAP）/双水平气道正压通气（BiPAP）治疗的阻塞性睡眠呼吸暂停（OSA）所致低氧血症的成年人。PAP滴定在一个晚上进行，包括密切监测生命体征和生理参数。根据患者指标精确指导对CPAP压力的调整、可能的双水平转换以及补充氧气。马尔可夫决策过程概述了三种用于疾病管理的治疗行动，并纳入了医学专家的见解。
在我们纳入14名OSA患者（平均年龄：63岁，27%为女性，体重指数41kg/m²）的研究中，手动滴定后关键健康参数有显著改善。初始每小时呼吸暂停低通气指数（AHI）为61.8次事件，在PAP和氧滴定后显著降至平均每小时18.0次事件（<0.0001），表明睡眠呼吸紊乱严重程度大幅降低。同时，SpO水平从滴定前的平均79.7%显著升至滴定后的89.1%（<0.0003）。皮尔逊相关系数显示，在CPAP压力增加期间，50%（n = 5）初始动脉血二氧化碳分压（pCO₂）<55mmHg的患者高碳酸血症加重。然而，转换为BiPAP显示pCO₂水平降低，表明其在解决高碳酸血症方面的疗效。同时，BiPAP治疗与SpO显著增加相关，强调其对OSA患者氧合的积极影响。马尔可夫决策过程分析表明在稳定夜间条件下患者行为符合实际，强调呼吸暂停极少且对高CPAP压力耐受性良好。
PAP和氧滴定算法的马尔可夫决策过程框架的开发有望提供改善pCO₂和SpO值的算法。尽管挑战仍然存在，包括对高质量数据的需求，但在患者管理和护理优化方面的潜在益处巨大，并且这种方法代表了远程医疗和呼吸保健领域一个令人兴奋的前沿领域。
