Controlling the Management of a Multimodal Stress-Controlled Therapy for Post-COVID-19-Patients - Urban, Thomas; Reichmann, Heinz; Lohse, Peter; Spitzer, Stefan G.; Reinhardt, Fritjof (Archives of Clinical and Biomedical Research, 2024)
Background: For the medical treatment of Post-COVID-19 syndrome, no medical treatment or causal therapy based on evidence-based criteria is currently recommended. As an interlinking of digital modules and classic on-site therapy, we developed a cross-sector, doctor-led blended therapy that is aimed at the main syndromes of fatigue/immunometabolic depression and sensorimotor instability (easily manageable real-time cognitive parameters). The real-time recording and analysis of the corresponding parameters become an important environmentally stable and control training item. Methodology: Changing the leading syndromes of fatigue and sensorimotor instability through stress-controlled standardized training therapy and intensified cognitive behavioral therapy were the overarching goals of the intervention and observation study over a 3-year period (Q1-2021 - Q2- 2024). The outcome assessment was based on the Post-COVID-19-key symptoms and motor fatigue parameters. A secondary psychosomatic syndrome that emerged during the course of treatment was examined using cognitive fatigue parameters. The analysis of participation, quality of life and mental health was carried out using validated questionnaires. The patients' health behavior was evaluated using a guideline-supported expert interview. Results: With blended therapy, improvements in Post-COVID-19-key symptoms as well as motor and cognitive fatigability parameters were achieved. The timing of the start of the individual sections of the treatment path had an influence on the outcome. The intensification of cognitive behavioral therapy also had positive effects, achieving an increasing development of the patients' own activity and their self-control. With the results of the guideline-supported expert interview, the social-cognitive process model of health action was specified. Conclusion: Cross-sector blended therapy with central data storage can coordinate the structured exchange of information between the individual actors in the treatment process with an impact on the success of the therapy. A delay in the start of therapy is counteracted, service provision and coordination is accelerated at a central and peripheral level, and an effective, efficient, safe and scalable intervention is implemented.