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一种用于预测肥胖患者中重度阻塞性睡眠呼吸暂停的新型灵敏且准确的模型。

A new sensitive and accurate model to predict moderate to severe obstructive sleep apnea in patients with obesity.

作者信息

Ahlin Sofie, Manco Melania, Panunzi Simona, Verrastro Ornella, Giannetti Giulia, Prete Anna, Guidone Caterina, Berardino Alessandro Di Marco, Viglietta Luca, Ferravante Anna, Mingrone Geltrude, Mormile Flaminio, Capristo Esmeralda

机构信息

Department of Molecular and Clinical Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.

Department of Internal Medicine, Fondazione Policlinico Universitario A. Gemelli IRCCS, Università Cattolica del Sacro Cuore Rome.

出版信息

Medicine (Baltimore). 2019 Aug;98(32):e16687. doi: 10.1097/MD.0000000000016687.

DOI:10.1097/MD.0000000000016687
PMID:31393370
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6708709/
Abstract

Obstructive sleep apnea (OSA) has a high prevalence in patients with obesity. Only patients with clinical symptoms of OSA are admitted to polysomnography; however, many patients with OSA are asymptomatic. We aimed to create and validate a population-based risk score that predicts the severity of OSA in patients with obesity.We here report the cross-sectional analysis at baseline of an ongoing study investigating the long-term effect of bariatric surgery on OSA. One-hundred sixty-one patients of the Obesity Center of the Catholic University Hospital in Rome, Italy were included in the study. The patients underwent overnight cardiorespiratory monitoring, blood chemistry analyses, hepatic ultrasound, and anthropometric measurements. The patients were divided into 2 groups according OSA severity assessed by the apnea-hypopnea index (AHI): AHI < 15 = no or mild and AHI ≥ 15 moderate to severe OSA. A statistical prediction model was created and validated. C statistics was used to evaluate the discrimination performance of the model.The prevalence of OSA was 96.3% with 74.5% of the subjects having moderate/severe OSA. Sex, body mass index, diabetes, and age were included in the final prediction model that had excellent discrimination ability (C statistics equals to 83%). An OSA risk chart score for clinical use was created.Patients with severe obesity are at a very high risk for moderate or severe OSA in particular if they are men, older, more obese, and/or with type 2 diabetes. The OSA risk chart can be useful for general practitioners and patients as well as for bariatric surgeons to select patients with high risk of moderate to severe OSA for further polysomnography.

摘要

阻塞性睡眠呼吸暂停(OSA)在肥胖患者中具有较高的患病率。只有出现OSA临床症状的患者才会接受多导睡眠图检查;然而,许多OSA患者并无症状。我们旨在创建并验证一种基于人群的风险评分,以预测肥胖患者OSA的严重程度。我们在此报告一项正在进行的研究的基线横断面分析,该研究旨在调查减肥手术对OSA的长期影响。意大利罗马天主教大学医院肥胖中心的161名患者纳入了该研究。患者接受了夜间心肺监测、血液化学分析、肝脏超声检查和人体测量。根据呼吸暂停低通气指数(AHI)评估的OSA严重程度,将患者分为两组:AHI<15 =无或轻度OSA,AHI≥15 =中度至重度OSA。创建并验证了一个统计预测模型。采用C统计量评估模型的辨别性能。OSA的患病率为96.3%,其中74.5%的受试者患有中度/重度OSA。最终的预测模型纳入了性别、体重指数、糖尿病和年龄,该模型具有出色的辨别能力(C统计量等于83%)。创建了一个供临床使用的OSA风险图表评分。严重肥胖患者尤其如果是男性、年龄较大、肥胖程度更高和/或患有2型糖尿病,发生中度或重度OSA的风险非常高。OSA风险图表对于全科医生、患者以及减肥外科医生选择有中度至重度OSA高风险的患者进行进一步的多导睡眠图检查可能会有帮助。

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