INTRODUCTION: Data from mHealth apps can provide valuable information on rhinitis control and treatment patterns. However, in MASK-air®, these data have only been analyzed cross-sectionally, without considering the changes of symptoms over time. We analyzed data from MASK-air® longitudinally, clustering weeks according to reported rhinitis symptoms. METHODS: We analyzed MASK-air® data, assessing the weeks for which patients had answered a rhinitis daily questionnaire on all 7 days. We firstly used k-means clustering algorithms for longitudinal data to define clusters of weeks according to the trajectories of reported daily rhinitis symptoms. Clustering was applied separately for weeks when medication was reported or not. We compared obtained clusters on symptoms and rhinitis medication patterns. We then used the latent class mixture model to assess the robustness of results. RESULTS: We analyzed 113,239 days (16,177 complete weeks) from 2590 patients (mean age ± SD = 39.1 ± 13.7 years). The first clustering algorithm identified ten clusters among weeks with medication use: seven with low variability in rhinitis control during the week and three with highly-variable control. Clusters with poorly-controlled rhinitis displayed a higher frequency of rhinitis co-medication, a more frequent change of medication schemes and more pronounced seasonal patterns. Six clusters were identified in weeks when no rhinitis medication was used, displaying similar control patterns. The second clustering method provided similar results. Moreover, patients displayed consistent levels of rhinitis control, reporting several weeks with similar levels of control. CONCLUSIONS: We identified 16 patterns of weekly rhinitis control. Co-medication and medication change schemes were common in uncontrolled weeks, reinforcing the hypothesis that patients treat themselves according to their symptoms.
- MeSH
- lidé MeSH
- longitudinální studie MeSH
- průzkumy a dotazníky MeSH
- rinitida * epidemiologie MeSH
- telemedicína * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Biomarkers for the diagnosis, treatment and follow-up of patients with rhinitis and/or asthma are urgently needed. Although some biologic biomarkers exist in specialist care for asthma, they cannot be largely used in primary care. There are no validated biomarkers in rhinitis or allergen immunotherapy (AIT) that can be used in clinical practice. The digital transformation of health and health care (including mHealth) places the patient at the center of the health system and is likely to optimize the practice of allergy. Allergic Rhinitis and its Impact on Asthma (ARIA) and EAACI (European Academy of Allergy and Clinical Immunology) developed a Task Force aimed at proposing patient-reported outcome measures (PROMs) as digital biomarkers that can be easily used for different purposes in rhinitis and asthma. It first defined control digital biomarkers that should make a bridge between clinical practice, randomized controlled trials, observational real-life studies and allergen challenges. Using the MASK-air app as a model, a daily electronic combined symptom-medication score for allergic diseases (CSMS) or for asthma (e-DASTHMA), combined with a monthly control questionnaire, was embedded in a strategy similar to the diabetes approach for disease control. To mimic real-life, it secondly proposed quality-of-life digital biomarkers including daily EQ-5D visual analogue scales and the bi-weekly RhinAsthma Patient Perspective (RAAP). The potential implications for the management of allergic respiratory diseases were proposed.
- MeSH
- alergická rýma * diagnóza terapie MeSH
- biologické markery MeSH
- bronchiální astma * diagnóza terapie MeSH
- lidé MeSH
- péče orientovaná na pacienta MeSH
- poruchy dýchání * MeSH
- rinitida * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- přehledy MeSH
This review presents state-of-the-art knowledge and identifies knowledge gaps for future research in the area of exercise-associated modifications of infection susceptibility. Regular moderate-intensity exercise is believed to have beneficial effects on immune health through lowering inflammation intensity and reducing susceptibility to respiratory infections. However, strenuous exercise, as performed by professional athletes, may promote infection: in about half of athletes presenting respiratory symptoms, no causative pathogen can be identified. Acute bouts of exercise enhance the release of pro-inflammatory mediators, which may induce infection-like respiratory symptoms. Relatively few studies have assessed the influence of regularly repeated exercise on the immune response and systemic inflammation compared to the effects of acute exercise. Additionally, ambient and environmental conditions may modify the systemic inflammatory response and infection susceptibility, particularly in outdoor athletes. Both acute and chronic regular exercise influence humoral and cellular immune response mechanisms, resulting in decreased specific and non-specific response in competitive athletes. The most promising areas of further research in exercise immunology include detailed immunological characterization of infection-prone and infection-resistant athletes, examining the efficacy of nutritional and pharmaceutical interventions as countermeasures to infection symptoms, and determining the influence of various exercise loads on susceptibility to infections with respiratory viruses, including SARS-CoV-2. By establishing a uniform definition of an "elite athlete," it will be possible to make a comparable and straightforward interpretation of data from different studies and settings.
- MeSH
- buněčná imunita MeSH
- COVID-19 * MeSH
- cvičení fyziologie MeSH
- infekce dýchací soustavy * prevence a kontrola MeSH
- lidé MeSH
- SARS-CoV-2 MeSH
- zánět MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- přehledy MeSH
