Rodsutti Julvit, Hensley Michael, Thakkinstian Ammarin, D'Este Catherine, Attia John
Department of Oto-Rhino-Laryngology Head and Neck Surgery Bhumibol Adulyadej Hospital, Bangkok, Thailand.
Sleep. 2004 Jun 15;27(4):694-9. doi: 10.1093/sleep/27.4.694.
To derive and validate a clinical decision rule that can help to prioritize patients who are on waiting lists for polysomnography,
Prospective data collection on consecutive patients referred to a sleep center.
The Newcastle Sleep Disorders Centre, University of Newcastle, NSW, Australia.
Consecutive adult patients who had been scheduled for initial diagnostic polysomnography.
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.
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.
推导并验证一项临床决策规则,以帮助对多导睡眠图等候名单上的患者进行优先排序。
对转诊至睡眠中心的连续患者进行前瞻性数据收集。
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。
已安排进行初次诊断性多导睡眠图检查的连续成年患者。
837名患者用于推导决策规则。采用呼吸暂停低通气指数至少为5作为诊断睡眠呼吸暂停的切点。在分析中纳入了15项临床特征,使用逻辑回归从推导数据集构建模型。只有5个变量——年龄、性别、体重指数、打鼾和睡眠中呼吸暂停——与睡眠呼吸暂停显著相关。基于回归系数制定了评分方案,总分被分为低、中、高风险组,睡眠呼吸暂停的患病率分别为8%、51%和82%。制定了彩色编码表格以便于使用。该临床决策规则在另一组243名患者中得到验证。受试者工作特征分析证实该决策规则表现良好,推导集和验证集的曲线下面积相似:分别为0.81和0.79,P = 0.612。
我们得出结论,该决策规则能够准确分类睡眠呼吸暂停风险,对于对多导睡眠图等候名单上疑似睡眠呼吸暂停的患者进行优先排序将很有用。