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A latent-class heteroskedastic hurdle trajectory model: patterns of adherence in obstructive sleep apnea patients on CPAP therapy.
P Den Teuling, Niek G; van den Heuvel, Edwin R; Aloia, Mark S; Pauws, Steffen C.
Afiliação
  • P Den Teuling NG; Dep. of Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, The Netherlands. n.g.p.den.teuling@tue.nl.
  • van den Heuvel ER; Philips Research, Eindhoven, The Netherlands. n.g.p.den.teuling@tue.nl.
  • Aloia MS; Dep. of Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, The Netherlands.
  • Pauws SC; Department of Medicine, National Jewish Health, Denver, CO, USA.
BMC Med Res Methodol ; 21(1): 269, 2021 12 01.
Article em En | MEDLINE | ID: mdl-34852769
BACKGROUND: Sleep apnea patients on CPAP therapy exhibit differences in how they adhere to the therapy. Previous studies have demonstrated the benefit of describing adherence in terms of discernible longitudinal patterns. However, these analyses have been done on a limited number of patients, and did not properly represent the temporal characteristics and heterogeneity of adherence. METHODS: We illustrate the potential of identifying patterns of adherence with a latent-class heteroskedastic hurdle trajectory approach using generalized additive modeling. The model represents the adherence trajectories on three aspects over time: the daily hurdle of using the therapy, the daily time spent on therapy, and the day-to-day variability. The combination of these three characteristics has not been studied before. RESULTS: Applying the proposed model to a dataset of 10,000 patients in their first three months of therapy resulted in nine adherence groups, among which 49% of patients exhibited a change in adherence over time. The identified group trajectories revealed a non-linear association between the change in the daily hurdle of using the therapy, and the average time on therapy. The largest difference between groups was observed in the patient motivation score. The adherence patterns were also associated with different levels of high residual AHI, and day-to-day variability in leakage. CONCLUSION: The inclusion of the hurdle model and the heteroskedastic model into the mixture model enabled the discovery of additional adherence patterns, and a more descriptive representation of patient behavior over time. Therapy adherence was mostly affected by a lack of attempts over time, suggesting that encouraging these patients to attempt therapy on a daily basis, irrespective of the number of hours used, could drive adherence. We believe the methodology is applicable to other domains of therapy or medication adherence.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Apneia Obstrutiva do Sono / Pressão Positiva Contínua nas Vias Aéreas Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Apneia Obstrutiva do Sono / Pressão Positiva Contínua nas Vias Aéreas Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article