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首页> 外文期刊>Sleep >A clinical decision rule to prioritize polysomnography in patients with suspected sleep apnea.
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A clinical decision rule to prioritize polysomnography in patients with suspected sleep apnea.

机译:临床决策规则优先考虑可疑睡眠呼吸暂停患者的多导睡眠监测。

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摘要

STUDY OBJECTIVES: To derive and validate a clinical decision rule that can help to prioritize patients who are on waiting lists for polysomnography, DESIGN: Prospective data collection on consecutive patients referred to a sleep center. SETTING: The Newcastle Sleep Disorders Centre, University of Newcastle, NSW, Australia. PATIENTS: Consecutive adult patients who had been scheduled for initial diagnostic polysomnography. MEASUREMENTS AND RESULTS: Eight hundred and thirty-seven patients were used for derivation of the decision rule. An apnea-hypopnoea index of at least 5 was used as the cutoff point to diagnose sleep apnea. Fifteen clinical features were included in the analyses using logistic regression to construct a model from the derivation data set. Only 5 variables--age, sex, body mass index, snoring, and stopping breathing during sleep--were significantly associated with sleep apnea. A scoring scheme based on regression coefficients was developed, and the total score was trichotomized into low-, moderate-, and high-risk groups with prevalence of sleep apnea of 8%, 51%, and 82%, respectively. Color-coded tables were developed for ease of use. The clinical decision rule was validated on a separate set of 243 patients. Receiver operating characteristic analysis confirmed that the decision rule performed well, with the area under the curve being similar for both the derivation and validation sets: 0.81 and 0.79, P =.612. CONCLUSION: We conclude that this decision rule was able to accurately classify the risk of sleep apnea and will be useful for prioritizing patients with suspected sleep apnea who are on waiting lists for polysomnography.
机译:研究目的:为了推导和验证一项临床决策规则,该规则可以帮助对在多导睡眠图候补名单上的患者进行优先排序,设计:对转诊至睡眠中心的连续患者进行前瞻性数据收集。地点:澳大利亚新南威尔士州纽卡斯尔大学纽卡斯尔睡眠障碍中心。患者:计划进行初次诊断性多导睡眠监测的连续成年患者。测量和结果:873例患者用于决策规则的推导。将呼吸暂停-呼吸不足指数至少为5作为诊断睡眠呼吸暂停的临界点。使用logistic回归从衍生数据集构建模型的分析中包括15种临床特征。睡眠,呼吸暂停仅与年龄,性别,体重指数,打s和停止呼吸这5个变量显着相关。制定了基于回归系数的评分方案,将总评分分为低,中和高风险组,分别为8%,51%和82%的睡眠呼吸暂停患病率。颜色编码表的开发易于使用。临床决策规则已在另一组243例患者中得到验证。接收器工作特性分析证实,决策规则执行得很好,对于衍生集和验证集,曲线下的面积相似:0.81和0.79,P = .612。结论:我们得出的结论是,该决策规则能够准确分类睡眠呼吸暂停的风险,将有助于对等待多导睡眠图检查的可疑睡眠呼吸暂停患者进行优先排序。

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