Cerebrovascular Concussion Lab, Faculty of Kinesiology, University of Calgary, Calgary, Alberta, Canada.
Sport Injury Prevention Research Centre, Faculty of Kinesiology, University of Calgary, Calgary, Alberta, Canada.
Physiol Rep. 2024 Jan;12(2):e15919. doi: 10.14814/phy2.15919.
To compare the construct validity and between-day reliability of projection pursuit regression (PPR) from oscillatory lower body negative pressure (OLBNP) and squat-stand maneuvers (SSMs). Nineteen participants completed 5 min of OLBNP and SSMs at driven frequencies of 0.05 and 0.10 Hz across two visits. Autoregulatory plateaus were derived at both point-estimates and across the cardiac cycle. Between-day reliability was assessed with intraclass correlation coefficients (ICCs), Bland-Altman plots with 95% limits of agreement (LOA), coefficient of variation (CoV), and smallest real differences. Construct validity between OLBNP-SSMs were quantified with Bland-Altman plots and Cohen's d. The expected autoregulatory curve with positive rising and negative falling slopes were present in only ~23% of the data. The between-day reliability for the ICCs were poor-to-good with the CoV estimates ranging from ~50% to 70%. The 95% LOA were very wide with an average spread of ~450% for OLBNP and ~350% for SSMs. Plateaus were larger from SSMs compared to OLBNPs (moderate-to-large effect sizes). The cerebral pressure-flow relationship is a complex regulatory process, and the "black-box" nature of this system can make it challenging to quantify. The current data reveals PPR analysis does not always elicit a clear-cut central plateau with distinctive rising/falling slopes.
比较基于振动式下体负压(OLBNP)和深蹲-站立动作(SSMs)的投影寻踪回归(PPR)的构建效度和日内可靠性。19 名参与者在两次访问中分别以 0.05 和 0.10Hz 的驱动频率完成了 5 分钟的 OLBNP 和 SSM。在两点估计和整个心动周期中都得出了自动调节平台。日内可靠性评估采用组内相关系数(ICCs)、95%一致性界限(LOA)的 Bland-Altman 图、变异系数(CoV)和最小真实差异。OLBNP-SSMs 之间的构建效度通过 Bland-Altman 图和 Cohen's d 进行量化。只有约 23%的数据呈现出预期的自动调节曲线,具有正上升和负下降斜率。ICC 的日内可靠性从差到好,CoV 估计值范围从约 50%到 70%。95%LOA 非常宽,OLBNP 的平均分布约为 450%,SSMs 的平均分布约为 350%。与 OLBNP 相比,SSM 产生的平台更大(中等至大效应量)。脑压流关系是一个复杂的调节过程,该系统的“黑盒”性质使得量化变得具有挑战性。目前的数据显示,PPR 分析并不总是能引出一个具有明显上升/下降斜率的清晰中央平台。