Major risk factors for obstructive sleep apnea monitored in the home. A cross-sectional study

Autor: Ricardo Silva, Tharcisio Pereira Brito, Antônio Cavalcanti Wanderley Neto, Renata Botelho Frota, João Cateb Melo
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: São Paulo Medical Journal, Vol 139, Iss 6, Pp 643-647 (2021)
Druh dokumentu: article
ISSN: 1806-9460
1516-3180
DOI: 10.1590/1516-3180.2020.0689.r1.22042021
Popis: ABSTRACT BACKGROUND: Obstructive sleep apnea (OSA) is characterized by recurrent pharyngeal wall collapse during sleep caused by anatomical or functional changes associated with obesity or dislocation of maxillofacial structures. OBJECTIVE: To determine the major risk factors for obstructive sleep apnea monitored in the home. DESIGN AND SETTING: Cross-sectional study conducted in a private clinic in Fortaleza (CE), Brazil. METHODS: Between 2015 and 2018, 427 patients were screened for OSA with home-based monitoring, yielding 374 positives. Information was collected on age, sex, body mass index (BMI), hypertension, diabetes (DM), dyslipidemia, coronary artery disease (CAD), arrhythmia, peripheral artery occlusive disease (PAOD), heart failure (HF) and lung disease. The home sleep apnea test result was then compared with the clinical diagnosis. Lastly, parameters identified as significant in the univariate analysis were subjected to multivariate logistic regression. RESULTS: Male sex predominated, although not significantly. OSA was associated with hypertension, DM, dyslipidemia, age and BMI. The risk of OSA being associated with these parameters was 2.195 (hypertension), 11.14 (DM), 2.044 (dyslipidemia) and 5.71 (BMI). The association was also significant for BMI categories (normal, overweight or obese). No significant association was observed for CAD, arrhythmia, PAOD, HF or lung disease. After multivariate logistic analysis, only age and BMI (and its categories) remained significant. CONCLUSION: OSA was associated with hypertension, DM, dyslipidemia, age and BMI in univariate analyses, but only with age and BMI (and its categories) in multivariate logistic analysis.
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