The influence of continuous positive airway pressure therapy on prevalence of masked hypertension in patients with obstructive sleep apnea

Abstract

Introduction Obstructive sleep apnea (OSA) is a common disorder with important clinical consequences. Many studies have proven that OSA is one of the most important causes of secondary hypertension. Masked hypertension (MH) is defined as a presence of normal office blood pressure together with abnormal results in 24 h ambulatory blood pressure monitoring (ABPM). The prevalence of this condition in patients with OSA is not well defined. Continuous positive airway pressure (CPAP) is the most effective method of OSA therapy. The influence of CPAP therapy on prevalence of masked hypertension is not well known. The aim of this study was to evaluate the influence of CPAP therapy on prevalence of MH in patients with OSA. Materials and methods 43 patients (40 men) were included, average age 54.2 ± 10.5. All of these patients were evaluated using polysomnography with diagnosis of OSA, average apnea-hypopnea index (AHI) 60.6 ± 23.6. Patients were treated with CPAP for one year. Patients with low compliance (CPAP usage Results Masked hypertension was initially present in 25 (58.1%) patients. After one year of CPAP therapy the MH was present in 26 (60.5%) patients. McNemar test did not found significant change in prevalence of MH ( p = 1.000) after CPAP treatment. In 15 patients (35.9%) was MH present initially and after CPAP therapy, in 10 (23.3%) patients was MH present initially but not after CPAP therapy and in 11 (25.6%) patients was MH present only after one year but not initially. In 7 (16.3%) patients MH was not present at all. Conclusion Masked hypertension is highly prevalent in patients with OSA. According to these results CPAP treatment does not influence prevalence of MH in patients with OSA. Because of long term consequences of suboptimal arterial hypertension compensation, it is crucial to perform ABPM in patients with OSA, preferably together with sleep study. With this algorithm we can better diagnose and treat patients with OSA and arterial hypertension. Acknowledgement This study has been supported by grant: LF_2013_17.