Background and Objective: Obstructive sleep apnea (OSA) is a heterogeneous chronic sleep associated disorder. A common apnea-hypopnea index (AHI)-focused approach to OSA severity evaluation is not sufficient enough to capture the extent of OSA related risks, it limits our understanding of disease pathogenesis and may contribute to a modest response to conventional treatment. In order to resolve the heterogeneity issue, OSA patients can be divided into more homogenous therapeutically and prognostically significant groups–phenotypes. An improved understanding of OSA phenotype relationship to treatment effectiveness is required. Thus, in this study several clinical OSA phenotypes are identified and compared by their treatment effectiveness. Methods and materials: Retrospective data analysis of 233 adult patients with OSA treated with continuous positive airway pressure (CPAP) was performed. Statistical analysis of data relating to demographic and anthropometric characteristics, symptoms, arterial blood gas test results, polysomnografic and respiratory polygraphic tests and treatment, treatment results was performed. Results: 3 phenotypes have been identified: “Position dependent (supine) OSA” (Positional OSA), “Severe OSA in obese patients” (Severe OSA) and “OSA and periodic limb movements (PLM)” (OSA and PLM). The highest count of responders to treatment with CPAP was in the OSA and PLM phenotype, followed by the Positional OSA phenotype. Treatment with CPAP, despite the highest mean pressure administered was the least effective among Severe OSA phenotype. Conclusions: Different OSA phenotypes vary significantly and lead to differences in response to treatment. Thus, treatment effectiveness depends on OSA phenotypes and treatment techniques other than CPAP may be needed. This emphasizes the importance of a more individualized approach when treating OSA.
Background and Objective: Respiratory assistance tactic that is best for COVID-19-associated acute hypoxemic respiratory failure (AHRF) individuals has yet to be determined. Patients with AHRF may benefit from the use of a high-flow nasal cannula (HFNC) and non-invasive ventilation (NIV). The goals of this prospective observational research were to estimate predictive factors for HFNC and NIV failure in COVID-19-related AHRF subjects. Materials and Methods: The research enlisted the participation of 124 patients. A stepwise treatment approach was used. HFNC and NIV were used on 124 (100%) and 64 (51.6%) patients, respectively. Thirty (24.2%) of 124 patients were intubated and received invasive mechanical ventilation. Results: 85 (68.5%) patients were managed successfully. Patients who required NIV exhibited a higher prevalence of treatment failure (70.3% vs. 51.6%, p = 0.019) and had higher mortality (59.4% vs. 31.5%, p = 0.001) than patients who received HFNC. Using logistic regression, the respiratory rate oxygenation (ROX) index at 24h (odds ratio (OR) = 0.74, p = 0.018) and the Charlson Comorbidity Index (CCI) (OR = 1.60, p = 0.003) were found to be predictors of HFNC efficacy. It was the ROX index at 24 h and the CCI optimum cut-off values for HFNC outcome that were 6.1 (area under the curve (AUC) = 0.73) and 2.5 (AUC = 0.68), respectively. Serum ferritin level (OR = 0.23, p = 0.041) and lymphocyte count (OR = 1.03, p = 0.01) were confirmed as predictors of NIV failure. Serum ferritin level at a cut-off value of 456.2 ng/mL (AUC = 0.67) and lymphocyte count lower than 0.70 per mm3, (AUC = 0.70) were associated with NIV failure with 70.5% sensitivity, 68.7% specificity and sensitivity of 84.1%, specificity of 56.2%, respectively. Conclusion: The ROX index at 24 h, CCI, as well as serum ferritin level, and lymphocyte count can be used as markers for HFNC and NIV failure, respectively, in SARS-CoV-2-induced AHRF patients.
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