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Consistent trajectories of rhinitis control and treatment in 16,177 weeks: The MASK-air® longitudinal study

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F65269705%3A_____%2F23%3A00078424" target="_blank" >RIV/65269705:_____/23:00078424 - isvavai.cz</a>

  • Result on the web

    <a href="https://onlinelibrary.wiley.com/doi/10.1111/all.15574" target="_blank" >https://onlinelibrary.wiley.com/doi/10.1111/all.15574</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1111/all.15574" target="_blank" >10.1111/all.15574</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Consistent trajectories of rhinitis control and treatment in 16,177 weeks: The MASK-air® longitudinal study

  • Original language description

    Introduction: Data from mHealth apps can provide valuable information on rhinitis control and treatment patterns. However, in MASK-air (R), these data have only been analyzed cross-sectionally, without considering the changes of symptoms over time. We analyzed data from MASK-air (R) longitudinally, clustering weeks according to reported rhinitis symptoms. Methods: We analyzed MASK-air (R) data, assessing the weeks for which patients had answered a rhinitis daily questionnaire on all 7days. 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. [GRAPHICS] .

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    30225 - Allergy

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2023

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Allergy

  • ISSN

    0105-4538

  • e-ISSN

    1398-9995

  • Volume of the periodical

    78

  • Issue of the periodical within the volume

    4

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    16

  • Pages from-to

    968-983

  • UT code for WoS article

    000898446700001

  • EID of the result in the Scopus database

    2-s2.0-85143420123