کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5633619 1581349 2017 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Clinical ReviewPhenotypes in obstructive sleep apnea: A definition, examples and evolution of approaches
ترجمه فارسی عنوان
بررسی های بالینی در مورد آپنه های انسداد خواب: تعریف، نمونه ها و تکامل رویکردها
موضوعات مرتبط
علوم زیستی و بیوفناوری علم عصب شناسی عصب شناسی
چکیده انگلیسی

SummaryObstructive sleep apnea (OSA) is a complex and heterogeneous disorder and the apnea hypopnea index alone can not capture the diverse spectrum of the condition. Enhanced phenotyping can improve prognostication, patient selection for clinical trials, understanding of mechanisms, and personalized treatments. In OSA, multiple condition characteristics have been termed “phenotypes.” To help classify patients into relevant prognostic and therapeutic categories, an OSA phenotype can be operationally defined as: “A category of patients with OSA distinguished from others by a single or combination of disease features, in relation to clinically meaningful attributes (symptoms, response to therapy, health outcomes, quality of life).” We review approaches to clinical phenotyping in OSA, citing examples of increasing analytic complexity. Although clinical feature based OSA phenotypes with significant prognostic and treatment implications have been identified (e.g., excessive daytime sleepiness OSA), many current categorizations lack association with meaningful outcomes. Recent work focused on pathophysiologic risk factors for OSA (e.g., arousal threshold, craniofacial morphology, chemoreflex sensitivity) appears to capture heterogeneity in OSA, but requires clinical validation. Lastly, we discuss the use of machine learning as a promising phenotyping strategy that can integrate multiple types of data (genomic, molecular, cellular, clinical) to identify unique, meaningful OSA phenotypes.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Sleep Medicine Reviews - Volume 35, October 2017, Pages 113-123
نویسندگان
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