动态心电图对阻塞性睡眠呼吸暂停综合征严重程度的预测价值

目的 评价动态心电图(Hoher)预测阻塞性睡眠呼吸暂停综合征(OSAHS)严重程度的价值.方法 选择2008年1月至2009年7月在我院老年科就诊经多导睡眠分析仪(PSG)检查确诊为OSAHS患者76例,并于1个月内行Hoher检查.其中,28例呼吸暂停低通气指数(AHI)≤20诊断为轻度OSAHS,48例AHI>20诊断为中、重度OSAHS.根据Hoher心率变异性分析对13项睡眠窒息危险指标进行评分,总和为睡眠窒息危险总分.将体质指数(BMI)及13项睡眠窒息危险指标各项得分进行logistic二元回归分析,评估Holler预测OSAHS严重程度的价值.结果 轻度OSAHS和中、重度OSAHS患者的性别、年龄,合并高血压、冠心病、糖尿病、高脂血症及服用B受体阻滞剂的临床特征无显著性差异.严重程度不同的OSAHS患者Hoher睡眠窒息危险评分总分差异无统计学意义(分别为5.64±2.33和6.42±2.22,P>0.05).极低频/总功率百分比>70%和△白天/夜晚低频功率差异<-70以及BMI与中、重度OSAHS相关,OR值分别为3.98(1.087～14.596),3.69(1.106～12.285)和1.28(1.062～1.544)(P<0.05).结论 应用Hoher心率变异性分析指标中的极低频/总功率百分比和△白天/夜晚低频功率差异以及BMI有助于早期识别中、重度OSAHS患者.

The predictive value of Hotter recordings to detect moderate-severe obstructive sleep apnea syndrome

Objective To evaluate the predictive value of Holter ECG recordings for patients with moderate-severe obstructive sleep apnea and hypopnea syndrome ( OSAHS ) . Methods Holter recordings was performed in 76 patients who were diagnosed OSAHS by polysomnography( PSG) within one month from Jan. 2008 to July 2009 in our hospital. Twenty-eight patients were identified as mild OSAHS (AHI≤20) and forty-eight patients were moderate-to-severe OSAHS ( AHI >20). The indexes of heart rate variability (HRV) , total scores of thirteen sleep apnea risk indexes of Holter recordings and BMI were analyzed by bivariate Logistic regression analysis. Results Clinical features ( eg. Gender, age, complicated with hypertension,coronary heart disease, diabetes mellitus, hyperglycemia, and taken β-blocker) , total scores, the sum of thirteen sleep apnea risk scores collected by Holter recordings (5. 64 ± 2. 33 vs. 6.42 ± 2. 22, respectively,P>0. 05 ) were similar between patients with mild OSAHS and moderate-to-severity OSAHS. VLF/Total Power>70% ,the difference of daytime/nighttime LF Power < -70 and BMI were independent predictors of moderate-to-severe OSAHS with OR 3. 98 (1. 087 - 14. 596), 3. 69 (1. 106 - 12. 285) and 1. 28 (1. 062 - 1. 544), respectively (all P < 0. 05). Conclusions VLF/Total Power and the difference of daytime/nighttime LF Power and BMI could be used as screening parameters to recognize patients with moderate-to-severe OSAHS.