Hem-monitorering och molekylär fenotypning av patienter med långtids-COVID för subgruppering samt uppföljning av interventioner

Since the inception of the SARS-CoV-2 pandemic, the focus of authorities and healthcare providers worldwide has been on the acute form of Coronavirus disease-2019 (COVID-19), and treatment strategies to reduce mortality associated with severe COVID-19. After a year of the pandemic, however, it is becoming increasingly clear that survival in the acute phase of the disease is not the only threat to the population.

While the mortality rate of individuals affected by severe COVID-19 has been relatively high, they have made up a small proportion of those infected. A much larger group of severely affected individuals has instead emerged during the fall: the long-term sick.

Long-term symptoms after covid-19 were initially associated only with recovery from hospitalization for severe respiratory disease. It is important to highlight that the majority of these patients do not consist of individuals with prolonged recovery after hospitalization. The majority of the group with long-COVID instead seems to constitute a completely different phenotype of the disease, which affects a different demographic group.

While those requiring hospital care are largely elderly or multi-morbid individuals, the majority of patients in long-COVID are formerly young, mentally and physically strong individuals who at the initial illness had mild to moderate symptoms of the disease - so mild that they usually did not seek hospital care. Here we intend to evaluate and further develop a home monitoring system originally developed for patients with severe COPD, in order to facilitate continuous follow-up of long-COVID patients.

Long-COVID patients with initial mild to moderate disease, with symptoms that then intensified cause 50% impairment in daily activities and persistent for >12 weeks will be compared with those of COVID patient recovering from hospitalization due to severe COVID, as well as with moderate to severe COPD patients. Identification of daily fluctuations, as well as how these correlate with activity and physiological parameters can also identify sub-groups of the disease, and be used to identify physiological, perceived, or molecular biomarkers as predictors of exacerbations and course of disease.

At a later stage, the fully developed system will also be used to evaluate the effectiveness of various forms of treatment.