摘要
目的 利用吸气驱动压 -流量曲线轨迹数字化后进行统计学处理的某些参数定量上呼吸道吸气性流量限制的程度。方法 通过一种上气道模型和 1例睡眠呼吸暂停综合征 (obstructivesleepapneasyndrome,OSAS)患者不伴有微觉醒的同一深睡眠期持续气道正压 (continuepositiveairwaypressure ,CPAP)滴定 ,由数字化后驱动压 -流量信号计算的上气道瞬间吸气阻力 (RST) ,统计不同驱动压 (跨壁压保持恒定 )和跨壁压 (驱动压保持恒定 )水平下 ,RST的中位数和几种百分位数 ,并分别作 3次多项式曲线拟合及拟合优度检验。结果 改变上气道模型驱动压、跨壁压和改变OSAS患者CPAP压 ,RST的中位数、第 2 5百分位数和第 75百分位的变化轨迹与 3次多项式轨迹极为相似 ,曲线拟合可解释 95 %以上变异 ,回归系数达 0 .97以上。RST数据群的上述统计量的变化与可塌陷软管流体阻力的动态变化规律类似。不同角度的实验验证表明 ,中位数反映出的流动阻力变化最为清晰和一致。结论 由吸气相驱动压 -流量数字模拟采样数据群统计的RST中位数 。
Objective Screening and evaluation of several non parametric descriptive statistical parameters of the ratio of digitized transient driving pressure to digitized transient flow, e.g. transient inspiratory resistance of upper airway (R ST ), in order to quantify inspiratory flow limitation during sleep.Methods Non linear estimation and Goodness of fit testifying of the 10th, 25th, 50th, 75th, 90th percentiles of the computer digitized R ST sampled at different driving pressures (while transmural pressure kept constant) and at different transmural pressures (while driving pressure kept constant) on an artificial model of upper airway and a patient with obstructive sleep apnea during his slow wave sleep stage without arousal.Results Non linear estimation and Goodness of fit test for the scatters of driving pressures or transmural pressures vs 50th, 25th and 75th percentiles of R ST when estimated by parabola of the third order revealed high coefficients of regression, all above 0.97 and the variances explained by the fitted curves are, for all, more than 95 %. The traces of these statistical quantities are similar to the dynamic variation of flow resistance in a Starling resistor. The increment of the 50th percentile (or medians) of R ST following the stepwise increasing of driving pressure or transmural pressure was most distinguishable and consistent.Conclusion The upper airway inspiratory flow limitation during sleep can be properly quantified by the 50th percentile (median) of digitized transient flow resistance.
出处
《中华物理医学与康复杂志》
CAS
CSCD
1999年第4期242-245,共4页
Chinese Journal of Physical Medicine and Rehabilitation
关键词
呼吸空气流量
睡眠呼吸暂停
综合征
Respiratory airflow Sleep apnea syndromes automatic data processing