Consistent trajectories of rhinitis control and treatment in 16,177 weeks: The MASK-air® longitudinal study
Jazyk angličtina Země Dánsko Médium print-electronic
Typ dokumentu časopisecké články, práce podpořená grantem
PubMed
36325824
DOI
10.1111/all.15574
Knihovny.cz E-zdroje
- Klíčová slova
- mobile health, patient-reported outcomes, real-world data, rhinitis,
- MeSH
- lidé MeSH
- longitudinální studie MeSH
- průzkumy a dotazníky MeSH
- rýma * epidemiologie MeSH
- telemedicína * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
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.
Allergy and Clinical Immunology Unit Centro Hospitalar e Universitário de Coimbra Coimbra Portugal
Allergy Center CUF Descobertas Hospital Lisbon Portugal
Allergy Department 2nd Pediatric Clinic University of Athens Athens Greece
Center for Rhinology and Allergology Wiesbaden Germany
Chiba University Hospital and Chiba Rosai Hospital Chiba Japan
CIBER Epidemiología y Salud Pública Barcelona Spain
CICS UBI Health Sciences Research Centre University of Beira Interior Covilhã Portugal
CINTESIS Center for Health Technology and Services Research University of Porto Porto Portugal
Department of Allergology Medical University of Gdańsk Gdansk Poland
Department of Allergy and Immunology Hospital Quironsalud Bizkaia Bilbao Spain
Department of Biomedical Sciences Humanitas University Pieve Emanuele Italy
Department of Computing Science Umeå University Umeå Sweden
Department of Immunoallergology Cova da Beira University Hospital Centre Covilhã Portugal
Department of Medicine Clinical Immunology and Allergy McMaster University Hamilton Ontario Canada
Department of Otolaryngology Head and Neck Surgery Eye and Ear University Hospital Beirut Lebanon
Department of Otolaryngology Head and Neck Surgery Universitätsmedizin Mainz Mainz Germany
Department of Otorhinolaryngology Amsterdam University Medical Centres AMC Amsterdam The Netherlands
Department of Otorhinolaryngology Head and Neck Surgery Dar Al Shifa Hospital Salmiya Kuwait
Department of Otorhinolaryngology Head and Neck Surgery Semmelweis University Budapest Hungary
Department of Pulmonary Diseases Celal Bayar University Faculty of Medicine Manisa Turkey
Department of Respiratory Medicine and Tuberculosis University Hospital Brno Czech Republic
Division of Allergy immunology University of South Florida Tampa Florida USA
Ecole Polytechnique Palaiseau IRBA Bretigny France
ENT Department Medical Faculty Eskisehir Osmangazi University Eskisehir Turkey
Faculty of Medicine Institute of Immunology University of Coimbra Coimbra Portugal
Faculty of Medicine University of Ljubljana Ljubljana Slovenia
Fundaçao ProAR Federal University of Bahia and GARD WHO Planning Group Salvador Brazil
Fundacion Jimenez Diaz CIBERES Faculty of Medicine Autonoma University of Madrid Madrid Spain
IMSB Medical Faculty University at Cologne and ClinCompetence Cologne GmbH Cologne Germany
International Primary Care Respiratory Group IPCRG Aberdeen UK
ISGlobal Barcelona Institute for Global Health Barcelona Spain
KYomed INNOV Montpellier France
Medical Consulting Czarlewski Levallois France
NOVA Medical School Comprehensive Health Research Centre Lisbon Portugal
Nova Southeastern University Fort Lauderdale Florida USA
Personalized Medicine Asthma and Allergy Humanitas Clinical and Research Center IRCCS Rozzano Italy
Pirogov Russian National Research Medical University Moscow Russian Federation
Poltava State Medical University Poltava Ukraine
RISE Health Research Network University of Porto Porto Portugal
School of Medicine University CEU San Pablo Madrid Spain
Servicio de Alergia e Immunologia Clinica Santa Isabel Buenos Aires Argentina
Skin and Allergy Hospital Helsinki University Hospital University of Helsinki Helsinki Finland
SOS Allergology and Clinical Immunology USL Toscana Centro Prato Italy
Transylvania University Brasov Brasov Romania
UBIAir Clinical and Experimental Lung Centre University of Beira Interior Covilhã Portugal
Unit of Geriatric Immunoallergology University of Bari Medical School Bari Italy
Universitat Pompeu Fabra Barcelona Spain
University Clinic of Respiratory and Allergic Diseases Golnick Slovenia
University Hospital Montpellier Montpellier France
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