We explored the relationship between obstructive sleep apnea (OSA) patients’ anthropometric measures and the CPAP treatment response. To that end, we processed three non-overlapping cohorts (D1, D2, D3) with 1046 patients from four sleep laboratories in Western Romania, including 145 subjects (D1) with one-night CPAP therapy. Using D1 data, we created a CPAP-response network of patients, and found neck circumference (NC) as the most significant qualitative indicator for apnea–hypopnea index (AHI) improvement. We also investigated a quantitative NC cutoff value for OSA screening on cohorts D2 (OSA-diagnosed) and D3 (control), using the area under the curve. As such, we confirmed the correlation between NC and AHI (ρ=0.35, p<0.001) and showed that 71% of diagnosed male subjects had bigger NC values than subjects with no OSA (area under the curve is 0.71, with 95% CI 0.63–0.79, p<0.001); the optimal NC cutoff is 41 cm, with a sensitivity of 0.8099, a specificity of 0.5185, positive predicted value (PPV) = 0.9588, negative predicted value (NPV) = 0.1647, and positive likelihood ratio (LR+) = 1.68. Our NC =41 cm threshold classified the D1 patients’ CPAP responses—measured as the difference in AHI prior to and after the one-night use of CPAP—with a sensitivity of 0.913 and a specificity of 0.859.

Background and objectives: Obstructive sleep apnea syndrome (OSAS) and heart failure (HF) are increasing in prevalence with a greater impact on the health system. The aim of this study was to assess the particularities of patients with OSAS and HF, focusing on the new class of HF with mid-range ejection fraction (HFmrEF, EF = 40%–49%), and comparing it with reduced EF (HFrEF, EF < 40%) and preserved EF (HFpEF, EF ≥ 50%). Materials and Methods: A total of 143 patients with OSAS and HF were evaluated in three sleep labs of “Victor Babes” Hospital and Cardiovascular Institute, Timisoara, Western Romania. We collected socio-demographic data, anthropometric sleep-related measurements, symptoms through sleep questionnaires and comorbidity-related data. We performed blood tests, cardio-respiratory polygraphy and echocardiographic measurements. Patients were divided into three groups depending on ejection fraction. Results: Patients with HFmrEF were older (p = 0.0358), with higher values of the highest systolic blood pressure (mmHg) (p = 0.0016), higher serum creatinine (p = 0.0013), a lower glomerular filtration rate (p = 0.0003), higher glycemic levels (p = 0.008) and a larger left atrial diameter (p = 0.0002). Regarding comorbidities, data were presented as percentage, HFrEF vs. HFmrEF vs. HFpEF. Higher prevalence of diabetes mellitus (52.9 vs. 72.7 vs. 40.2, p = 0.006), chronic kidney disease (17.6 vs. 57.6 vs. 21.5, p < 0.001), tricuspid insufficiency (76.5 vs. 84.8 vs.59.1, p = 0.018) and aortic insufficiency (35.3 vs.42.4 vs. 20.4, p = 0.038) were observed in patients with HFmrEF, whereas chronic obstructive pulmonary disease(COPD) (52.9 vs. 24.2 vs.18.3, p = 0.009), coronary artery disease(CAD) (82.4 vs. 6.7 vs. 49.5, p = 0.026), myocardial infarction (35.3 vs. 24.2 vs. 5.4, p < 0.001) and impaired parietal heart kinetics (70.6 vs. 68.8 vs. 15.2, p < 0.001) were more prevalent in patients with HFrEF. Conclusions: Patients with OSAS and HF with mid-range EF may represent a new group with increased risk of developing life-long chronic kidney disease, diabetes mellitus, tricuspid and aortic insufficiency. COPD, myocardial infarction, impaired parietal kinetics and CAD are most prevalent comorbidities in HFrEF patients but they are closer in prevalence to HFmrEF than HFpEF.

Background: We sought to investigate whether long-term continuous positive airway pressure (CPAP) treatment in patients with obstructive sleep apnea (OSA) and resistant hypertension (RHTN) could attenuate the cardiovascular disease risk by lowering their body-mass index (BMI). Methods: This was a long-term observational study of RHTN patients diagnosed with OSA. Patients were evaluated with polysomnography initially and after a mean follow-up period of four years. The patients were divided into two groups based on their compliance to CPAP therapy. Results: 33 patients (aged 54.67 ± 7.5, 18 men, 54.5%) were included in the study, of which 12 were compliant to CPAP therapy. A significant reduction in BMI at follow-up was noted in patients compliant to CPAP therapy (1.4 ± 3.5 vs. −1.6 ± 2.5, p = 0.006). We also noted a large effect size reduction in abdominal circumference at follow-up in the CPAP group. At follow-up evaluation, the mean heart rate (b/min) was lower in the CPAP group (58.6 ± 9.5 vs. 67.8 ± 7.8), while arrhythmia prevalence increased between initial (28.6%) and follow-up (42.9%) evaluation with an intermediate effect size in non-compliant patients. Conclusions: In our cohort of OSA patients with RHTN, long-term adherence to CPAP therapy was associated with weight loss and improvement in cardiac rhythm outcomes.