Subclinical left ventricular systolic dysfunction detected in obstructive sleep apnea with automated function imaging and its association with nocturnal hypoxia.

2021 
Early detection of left ventricular (LV) dysfunction is crucial in obstructive sleep apnea (OSA) due to its close relationship with cardiovascular diseases. Global longitudinal strain (GLS) derived from automated function imaging (AFI) can precisely assess global longitudinal function. The aim of this study was to determine if LV GLS was reduced in patients with OSA and a normal LV ejection fraction (LVEF) and to assess any associated determinants. Polysomnography (PSG) and echocardiography were done in consecutive patients with suspected OSA and normal LVEF in this prospective study. Patients were divided into two groups according to apnea-hypopnea index (AHI) (Group 1, normal or mild OSA: AHI < 15/h; Group 2, moderate-to-severe OSA: AHI ≥ 15/h). Clinical, PSG, and echocardiographic parameters were compared between the two groups and the associated factors were investigated. Of 425 consecutive patients, 244 were analyzed after exclusions. Patients in Group 2 had significantly worse GLS than those in Group 1 (p < 0.001). The prevalence of GLS reduction (defined as < − 19.7%) was 25% and 76%, respectively (χ2 = 34.19, p < 0.001). Nocturnal lowest pulse oxygen saturation (SpO2), AHI, body mass index (BMI), and gender were associated with GLS reduction (all p < 0.05). Further multivariate analysis showed that the lowest SpO2 (OR: 2.15), gender (OR: 2.45), and BMI (OR: 2.66) remained independent (all p < 0.05), and the lowest SpO2 was the most powerful determinant (χ2 = 33.0, p < 0.001) in forward regression analysis. The intra- and inter-operator variability for AFI and coefficient of repeatability was low even in those with relatively poor images. In patients with normal LVEF, more severe OSA was associated with a worse GLS. The major determinants were lowest nocturnal SpO2, gender, and obesity, but not AHI. GLS can be rapidly and reliably assessed using AFI.
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