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Predictors of positive airway pressure therapy termination in the first year: analysis of big data from a German homecare provider

BACKGROUND: There is a lack of robust data about factors predicting continuation (or termination) of positive airway pressure therapy (PAP) for sleep apnea. This analysis of big data from a German homecare provider describes patients treated with PAP, analyzes the therapy termination rate over the f...

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Autores principales: Woehrle, Holger, Arzt, Michael, Graml, Andrea, Fietze, Ingo, Young, Peter, Teschler, Helmut, Ficker, Joachim H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6280473/
https://www.ncbi.nlm.nih.gov/pubmed/30518372
http://dx.doi.org/10.1186/s12890-018-0748-8
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author Woehrle, Holger
Arzt, Michael
Graml, Andrea
Fietze, Ingo
Young, Peter
Teschler, Helmut
Ficker, Joachim H.
author_facet Woehrle, Holger
Arzt, Michael
Graml, Andrea
Fietze, Ingo
Young, Peter
Teschler, Helmut
Ficker, Joachim H.
author_sort Woehrle, Holger
collection PubMed
description BACKGROUND: There is a lack of robust data about factors predicting continuation (or termination) of positive airway pressure therapy (PAP) for sleep apnea. This analysis of big data from a German homecare provider describes patients treated with PAP, analyzes the therapy termination rate over the first year, and investigates predictive factors for therapy termination. METHODS: Data from a German homecare service provider were analyzed retrospectively. Patients who had started their first PAP therapy between September 2009 and April 2014 were eligible. Patient demographics, therapy start date, and the date of and reason for therapy termination were obtained. At 1 year, patients were classified as having compliance-related therapy termination or remaining on therapy. These groups were compared, and significant predictors of therapy termination determined. RESULTS: Of 98,329 patients included in the analysis, 11,702 (12%) terminated PAP therapy within the first year (after mean 171 ± 91 days). There was a U-shaped relationship between therapy termination and age; therapy termination was higher in the youngest (< 30 years, 15.5%) and oldest (≥ 80 years, 19.8%) patients, and lower in those aged 50–59 years (9.9%). Therapy termination was significantly more likely in females versus males (hazard ratio 1.48, 95% confidence interval 1.42–1.54), in those with public versus private insurance (1.75, 1.64–1.86) and in patients whose first device was automatically adjusting or fixed-level continuous positive airway pressure versus bilevel or adaptive servo-ventilation (1.28, 1.2–1.38). CONCLUSIONS: This analysis of the largest dataset investigating PAP therapy termination identified a number of predictive factors. These can help health care providers chose the most appropriate PAP modality, identify specific patient phenotypes at higher risk of stopping PAP and target interventions to support ongoing therapy to these groups, as well as allow them to develop a risk stratification tool.
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spelling pubmed-62804732018-12-10 Predictors of positive airway pressure therapy termination in the first year: analysis of big data from a German homecare provider Woehrle, Holger Arzt, Michael Graml, Andrea Fietze, Ingo Young, Peter Teschler, Helmut Ficker, Joachim H. BMC Pulm Med Research Article BACKGROUND: There is a lack of robust data about factors predicting continuation (or termination) of positive airway pressure therapy (PAP) for sleep apnea. This analysis of big data from a German homecare provider describes patients treated with PAP, analyzes the therapy termination rate over the first year, and investigates predictive factors for therapy termination. METHODS: Data from a German homecare service provider were analyzed retrospectively. Patients who had started their first PAP therapy between September 2009 and April 2014 were eligible. Patient demographics, therapy start date, and the date of and reason for therapy termination were obtained. At 1 year, patients were classified as having compliance-related therapy termination or remaining on therapy. These groups were compared, and significant predictors of therapy termination determined. RESULTS: Of 98,329 patients included in the analysis, 11,702 (12%) terminated PAP therapy within the first year (after mean 171 ± 91 days). There was a U-shaped relationship between therapy termination and age; therapy termination was higher in the youngest (< 30 years, 15.5%) and oldest (≥ 80 years, 19.8%) patients, and lower in those aged 50–59 years (9.9%). Therapy termination was significantly more likely in females versus males (hazard ratio 1.48, 95% confidence interval 1.42–1.54), in those with public versus private insurance (1.75, 1.64–1.86) and in patients whose first device was automatically adjusting or fixed-level continuous positive airway pressure versus bilevel or adaptive servo-ventilation (1.28, 1.2–1.38). CONCLUSIONS: This analysis of the largest dataset investigating PAP therapy termination identified a number of predictive factors. These can help health care providers chose the most appropriate PAP modality, identify specific patient phenotypes at higher risk of stopping PAP and target interventions to support ongoing therapy to these groups, as well as allow them to develop a risk stratification tool. BioMed Central 2018-12-05 /pmc/articles/PMC6280473/ /pubmed/30518372 http://dx.doi.org/10.1186/s12890-018-0748-8 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Woehrle, Holger
Arzt, Michael
Graml, Andrea
Fietze, Ingo
Young, Peter
Teschler, Helmut
Ficker, Joachim H.
Predictors of positive airway pressure therapy termination in the first year: analysis of big data from a German homecare provider
title Predictors of positive airway pressure therapy termination in the first year: analysis of big data from a German homecare provider
title_full Predictors of positive airway pressure therapy termination in the first year: analysis of big data from a German homecare provider
title_fullStr Predictors of positive airway pressure therapy termination in the first year: analysis of big data from a German homecare provider
title_full_unstemmed Predictors of positive airway pressure therapy termination in the first year: analysis of big data from a German homecare provider
title_short Predictors of positive airway pressure therapy termination in the first year: analysis of big data from a German homecare provider
title_sort predictors of positive airway pressure therapy termination in the first year: analysis of big data from a german homecare provider
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6280473/
https://www.ncbi.nlm.nih.gov/pubmed/30518372
http://dx.doi.org/10.1186/s12890-018-0748-8
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