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ADHERE 登记研究中批准后上气道刺激治疗效果的预测因素。

Post-approval upper airway stimulation predictors of treatment effectiveness in the ADHERE registry.

机构信息

Dept of Otorhinolaryngology, Head and Neck Surgery, Munich Technical University, Munich, Germany.

Dept of Otorhinolaryngology, University of Lubeck, Lubeck, Germany.

出版信息

Eur Respir J. 2019 Jan 3;53(1). doi: 10.1183/13993003.01405-2018. Print 2019 Jan.

Abstract

Upper airway stimulation (UAS) has been shown to reduce severity of obstructive sleep apnoea. The aim of this study was to identify predictors of UAS therapy response in an international multicentre registry.Patients who underwent UAS implantation in the United States and Germany were enrolled in an observational registry. Data collected included patient characteristics, apnoea/hypopnoea index (AHI), Epworth sleepiness scale (ESS), objective adherence, adverse events and patient satisfaction measures. univariate and multiple logistic regression were performed to evaluate factors associated with treatment success.Between October 2016 and January 2018, 508 participants were enrolled from 14 centres. Median AHI was reduced from 34 to 7 events·h, median ESS reduced from 12 to 7 from baseline to final visit at 12-month post-implant. In analyses, for each 1-year increase in age, there was a 4% increase in odds of treatment success. For each 1-unit increase in body mass index (BMI), there was 9% reduced odds of treatment success. In the multivariable model, age persisted in serving as statistically significant predictor of treatment success.In a large multicentre international registry, UAS is an effective treatment option with high patient satisfaction and low adverse events. Increasing age and reduced BMI are predictors of treatment response.

摘要

上气道刺激(UAS)已被证明可降低阻塞性睡眠呼吸暂停的严重程度。本研究旨在确定国际多中心登记处 UAS 治疗反应的预测因素。在美国和德国接受 UAS 植入的患者被纳入观察性登记处。收集的数据包括患者特征、呼吸暂停/低通气指数(AHI)、嗜睡量表(ESS)、客观依从性、不良事件和患者满意度测量。进行单变量和多变量逻辑回归分析以评估与治疗成功相关的因素。在 2016 年 10 月至 2018 年 1 月期间,从 14 个中心招募了 508 名参与者。中位 AHI 从 34 次降低到 7 次·h,中位 ESS 从基线时的 12 次降低到植入后 12 个月时的 7 次。在 分析中,年龄每增加 1 年,治疗成功的几率就会增加 4%。BMI 每增加 1 个单位,治疗成功的几率就会降低 9%。在多变量模型中,年龄仍然是治疗成功的统计学显著预测因素。在一项大型国际多中心登记处研究中,UAS 是一种有效的治疗选择,具有较高的患者满意度和较低的不良事件。年龄增加和 BMI 降低是治疗反应的预测因素。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bb17/6319796/06d6ac9056ff/ERJ-01405-2018.01.jpg

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