应用判别分析法对阻塞性睡眠呼吸暂停低通气综合征患者建立筛查模型的研究

Study of discriminant analysis in screening of patients with obstructive sleep apneahypopnea syndrome

目的采用逐步Fisher判别分析法建立判别函数,为基层护士对阻塞性睡眠呼吸暂停低通气综合征患者(OSAHS)的筛查提供依据。方法对83例疑似OSAHS患者进行Epworth嗜睡量表(ESS)评分,并了解夜间症状、合并症情况,同时测量BMI及颈围,以整夜多导睡眠图监测(PSG)为金标准确立诊断。将研究对象分为OSAHS组和非OSAHS组,对各指标进行逐步Fisher判别分析,建立筛查指标的判别模型。结果经逐步Fisher判别分析,10个指标中有2个指标即BMI和夜间睡眠呼吸暂停症状进入判别模型,建立非标准化判别函数为y=(0.132×BMI)+(0.641×夜间睡眠呼吸暂停)-3.861,根据样本加权求得临界值为0,整体回带和交互验证显示,函数预测准确性分别达92.8%和90.4%。结论夜间睡眠呼吸暂停的症状和BMI等主客观指标联合应用建立判别函数,可以从统计学角度对OSAHS的筛查提供信息。

Objective To construct and evaluate a screening system for obstructive sleep apneahypopnea syndrome （OSAHS） incorporating subjective and objective factors to provide reference for primary nurses. Method Charts were reviewed from 100 consecutive patients for whom complete data regarding the body mass index grade, Epworth Sleepiness Scale, and visual analog scale for snoring were obtained prior to polysomnography （PSG）. Patient data were subjected to multi variatestepwise discriminant analysis to propose a screening system based on the Fisher line- ar classification equation. Result By Stepwise Fisher discriminant analysis, indicators was validated by PSG findings. 2 of the 10 indicators（ BMI and nocturnal sleep apnea symptoms） was selected for predicting a diagnosis model of OSAHS. When applied case-wise to the study population, this equation correctly predicted 92.8 and 90. percent of diagnoses, the equation was y= （0. 132 × BMI） ＋ （0. 641 × noeturnal breathing pauses） -3. 861. Conclusion The BMI and nocturnal sleep apnea symptoms used for seting discriminant function can provide screening reference infor- mation for OSAHS.