Articles: loop-gain.
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Positional OSA (POSA) is a recognized subtype of OSA that exhibits distinct endotypic characteristics when compared with nonpositional OSA (NPOSA). The basis for the disparity in endotypes between these subtypes remains poorly understood. ⋯ This study highlights the differences in endotypes between NPOSA and POSA. In Chinese individuals, anatomic factors were more significant in determining the severity of NPOSA, whereas nonanatomic traits were more likely to determine the severity of POSA. Future research should focus on developing personalized management strategies for individuals with NPOSA and POSA based on their endotypes.
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Emerging data suggest that determination of physiologic endotypic traits (eg, loop gain) may enable precision medicine in OSA. ⋯ Endotypic trait analysis using a single standard polysomnography shows acceptable reliability and reproducibility in patients with moderate to severe OSA. The reported MDDs of endotypic traits may facilitate the quantification of relevant changes and may guide future evaluation of interventions in OSA.
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The mechanisms responsible for the development of obstructive sleep apnea (phenotypic "traits") are known to differ between individuals and may differ across ethnicities. We aimed to examine whether loop gain, arousal threshold, pharyngeal collapsibility and muscle compensation differ between Chinese and Caucasian individuals with OSA. ⋯ Individuals of Chinese descent appear to have OSA that is driven much more by the relative contribution of their anatomical predisposition and to a lesser extent nonanatomical causes compared with Caucasians. Future research should focus on determining if Chinese versus Caucasian ethnicity is an important contributing factor to clinical outcomes and therapeutic responses in OSA.
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Increasingly, obstructive sleep apnea treatment is being recognized as amenable to a precision medicine approach. Many pathophysiologic mechanisms (endotypes) beyond anatomic compromise have now been identified and are readily determined during polysomnography, although randomized controlled trials of endotype-specific therapies are needed. Research indicates that endotypes may also be important in predicting both adherence to therapy and disease consequences (phenotypes). Biomarker discovery and Big Data approaches derived from wearable technology are areas of active investigation and may allow more robust conclusions to be drawn over time, such that patients may soon fully realize the benefits from fresh insights into sleep science.