Individualized Algorithm-Based Intermittent Hypoxia Improves Quality of Life in Patients Suffering from Long-Term...

Background/Objectives: Post-COVID-19 condition (PCC), also known as long COVID, has emerged as a recognized syndrome affecting millions of people worldwide, significantly impairing their quality of life. Currently, no effective therapeutic options are available to manage this condition. The objective of the present study was to evaluate the long-term effects of personalized, algorithm-based intermittent hypoxia-hyperoxia conditioning (IHHC) on quality of life and pain in patients with PCC. Methods: This open-label cohort study included 199 PCC patients, aged 11-87 years (female-to-male ratio: 67:33) and experiencing moderate-to-severe fatigue, between 1 January 2020 and 31 December 2023. Each patient received an algorithm-based treatment plan tailored to their demographics, symptom duration, and baseline pain (NRS) and quality of life (SF-36) scores. Patients received an average of six treatment sessions (range: 2-21), each consisting of intermittent hypoxic-hyperoxic cycles, with hypoxia (9-13% O₂) lasting 3-8 min and hyperoxia (34-36% O₂) lasting 1-3 min. The primary outcomes were changes in the NRS and SF-36 scores at the 6-week and 6-month follow-ups. Results: At the 6-week follow-up after treatment initiation, the SF-36 scores increased by 102 points (p < 0.001, 95% CI: 78.4-127), and this improvement persisted at the 6-month follow-up (Δ106, p < 0.001, 95% CI: 57.0-154). Pain was reduced by 28-32% at both follow-up time points, exceeding the clinically relevant threshold. Health transition scores indicated a patient-perceived improvement in health status. Conclusions: In this study, a personalized, algorithm-based IHHC alleviated pain and improved quality of life in patients suffering from persistent long-term sequelae after COVID-19 infection. The effects were sustained for up to six months. Further research is warranted to elucidate the mechanisms underlying IHHC's therapeutic effects in this patient population.