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. 2017 Sep 21;12(9):e0185191.
doi: 10.1371/journal.pone.0185191. eCollection 2017.

Characterization of the CPAP-treated patient population in Catalonia

Cecilia Turino  1   2 , Sandra Bertran  1   2 , Ricard Gavaldá  3 , Ivan Teixidó  4 , Holger Woehrle  5 , Montserrat Rué  6 , Francesc Solsona  4 , Joan Escarrabill  7 , Cristina Colls  8 , Anna García-Altés  8 , Jordi de Batlle  1   2 , Manuel Sánchez de-la-Torre  1   2 , Ferran Barbé  1   2
Affiliations

Characterization of the CPAP-treated patient population in Catalonia

Cecilia Turino et al. PLoS One. .

Abstract

There are different phenotypes of obstructive sleep apnoea (OSA), many of which have not been characterised. Identification of these different phenotypes is important in defining prognosis and guiding the therapeutic strategy. The aim of this study was to characterise the entire population of continuous positive airway pressure (CPAP)-treated patients in Catalonia and identify specific patient profiles using cluster analysis. A total of 72,217 CPAP-treated patients who contacted the Catalan Health System (CatSalut) during the years 2012 and 2013 were included. Six clusters were identified, classified as "Neoplastic patients" (Cluster 1, 10.4%), "Metabolic syndrome patients" (Cluster 2, 27.7%), "Asthmatic patients" (Cluster 3, 5.8%), "Musculoskeletal and joint disorder patients" (Cluster 4, 10.3%), "Patients with few comorbidities" (Cluster 5, 35.6%) and "Oldest and cardiac disease patients" (Cluster 6, 10.2%). Healthcare facility use and mortality were highest in patients from Cluster 1 and 6. Conversely, patients in Clusters 2 and 4 had low morbidity, mortality and healthcare resource use. Our findings highlight the heterogeneity of CPAP-treated patients, and suggest that OSA is associated with a different prognosis in the clusters identified. These results suggest the need for a comprehensive and individualised approach to CPAP treatment of OSA.

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Conflict of interest statement

Competing Interests: ResMed paid the salaries of the author HW, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Figures

Fig 1
Fig 1. Sampling framework.
Abbreviations: OSA, obstructive sleep apnoea; CPAP, continuous positive airway pressure.
Fig 2
Fig 2. The proportion of each comorbidity in each cluster.
Cluster 1: Neoplastic patients. Cluster 2: Metabolic syndrome patients. Cluster 3: Asthmatic patients. Cluster 4: Musculoskeletal and joint disorders patients. Cluster 5: Patients with few comorbidities. Cluster 6: Oldest and cardiac disease patients. Abbreviations: DLP, dyslipidaemia; OB, obesity; BD, back disorders; OA, osteoarthrosis; HF, heart failure; CD, cardiac dysrhythmia; ADT, addiction; ANXTY, anxiety; OHD, other heart disease; OJD, other joint disease; PT, peripheral tendinitis; CKD, chronic kidney disease; ASTH, asthma; STD, soft tissue disease; MN, malignant neoplasm; HBP, hypertension; CVD, cerebrovascular; COPD, chronic obstructive pulmonary disease; ANM, anaemia; DM, diabetes mellitus; OP, osteoporosis.
Fig 3
Fig 3. Percentages of high use of health care resources per year in each cluster.
Cluster 1: Neoplastic patients. Cluster 2: Metabolic syndrome patients. Cluster 3: Asthmatic patients. Cluster 4: Musculoskeletal and joint disorders patients. Cluster 5: Patients with few comorbidities. Cluster 6: Oldest and cardiac disease patients. (% Mortality).
See this image and copyright information in PMC

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