Apnea del son i malaltia cardiovascular: de l’etiopatogènia a l’impacte clínic

Apnea del son; Malaltia cardiovascular; Etiopatogènia; Impacte clínicSleep apnea; Cardiovascular disease; Etiopathogenesis; Clinical impactApnea del sueño; Enfermedad cardiovascular; Etiopatogenia; Impacto clínicoComunicació que presenta els estudis al voltant de l'apnea del son en el context de les malalties cardiovasculars

Resistant/Refractory Hypertension and Sleep Apnoea: Current Knowledge and Future Challenges

Hypertension is one of the most frequent cardiovascular risk factors. The population of hypertensive patients includes some phenotypes whose blood pressure levels are particularly difficult to control, thus putting them at greater cardiovascular risk. This is especially true of so-called resistant hypertension (RH) and refractory hypertension (RfH). Recent findings suggest that the former may be due to an alteration in the renin–angiotensin–aldosterone axis, while the latter seems to be more closely related to sympathetic hyper-activation. Both these pathophysiological mechanisms are also activated in patients with obstructive sleep apnoea (OSA). It is not surprising, therefore, that the prevalence of OSA in RH and RfH patients is very high (as reflected in several studies) and that treatment with continuous positive airway pressure (CPAP) manages to reduce blood pressure levels in a clinically significant way in both these groups of hypertensive patients. It is therefore necessary to incorporate into the multidimensional treatment of patients with RH and RfH (changes in lifestyle, control of obesity and drug treatment) a study of the possible existence of OSA, as this is a potentially treatable disease. There are many questions that remain to be answered, especially regarding the ideal combination of treatment in patients with RH/RfH and OSA (drugs, renal denervation, CPAP treatment) and patients’ varying response to CPAP treatment

Characterization of the CPAP-treated patient population in Catalonia

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.This study was supported by the Spanish Respiratory Society (SEPAR), Associació Lleidatana de Respiratori (ALLER) and ResMed, a company that provides diagnostic services and treatment for sleep apnoea

Comparative analysis of predictive methods for early assessment of compliance with continuous positive airway pressure therapy

Background: Patients suffering obstructive sleep apnea are mainly treated with continuous positive airway pressure (CPAP). Although it is a highly effective treatment, compliance with this therapy is problematic to achieve with serious consequences for the patients’ health. Unfortunately, there is a clear lack of clinical analytical tools to support the early prediction of compliant patients. Methods: This work intends to take a further step in this direction by building compliance classifiers with CPAP therapy at three different moments of the patient follow-up, before the therapy starts (baseline) and at months 1 and 3 after the baseline. Results: Results of the clinical trial shows that month 3 was the time-point with the most accurate classifier reaching an f1-score of 87% and 84% in cross-validation and test. At month 1, performances were almost as high as in month 3 with 82% and 84% of f1-score. At baseline, where no information of patients’ CPAP use was given yet, the best classifier achieved 73% and 76% of f1-score in cross-validation and test set respectively. Subsequent analyzes carried out with the best classifiers of each time point revealed baseline factors (i.e. headaches, psychological symptoms, arterial hypertension and EuroQol visual analog scale) closely related to the prediction of compliance independently of the time-point. In addition, among the variables taken only during the follow-up of the patients, Epworth and the average nighttime hours were the most important to predict compliance with CPAP. Conclusions: Best classifiers reported high performances after one month of treatment, being the third month when significant differences were achieved with respect to the baseline. Four baseline variables were reported relevant for the prediction of compliance with CPAP at each time-point. Two characteristics more were also highlighted for the prediction of compliance at months 1 and 3.This work is part of the myOSA project (RTC-2014-3138-1), funded by the Spanish Ministry of Economy and Competitiveness (Ministerio de Economía y Competitividad) under the framework “Retos-Colaboración”, State Scientific and Technical Research and Innovation Plan 2013-2016. The study was also partially funded by the European Community under “H2020-EU.3.1. – Societal Challenges – Health, demographic change and well-being” programme, project grant agreement number 689802 (CONNECARE)