Background Change of the corrected flow time (Ftc) is a surrogate for tracking stroke volume (SV) in the intensive care unit. Multiple Ftc equations have been proposed; many have not had their diagnostic characteristics for detecting SV change reported. Further, little is known about the inherent Ftc variability induced by the respiratory cycle. Materials and methods Using a wearable Doppler ultrasound patch, we studied the clinical performance of 11 Ftc equations to detect a 10% change in SV measured by non-invasive pulse contour analysis; 26 healthy volunteers performed a standardized cardiac preload modifying maneuver. Results One hundred changes in cardiac preload and 3890 carotid beats were analyzed. Most of the 11 Ftc equations studied had similar diagnostic attributes. Wodeys’ and Chambers’ formulae had identical results; a 2% change in Ftc detected a 10% change in SV with a sensitivity and specificity of 96% and 93%, respectively. Similarly, a 3% change in Ftc calculated by Bazett’s formula displayed a sensitivity and specificity of 91% and 93%. Ftc Wodey had 100% concordance and an R 2 of 0.75 with change in SV; these values were 99%, 0.76 and 98%, 0.71 for Ftc Chambers and Ftc Bazetts , respectively. As an exploratory analysis, we studied 3335 carotid beats for the dispersion of Ftc during quiet breathing using the equations of Wodey and Bazett. The coefficient of variation of Ftc during quiet breathing for these formulae were 0.06 and 0.07, respectively. Conclusions Most of the 11 different equations used to calculate carotid artery Ftc from a wearable Doppler ultrasound patch had similar thresholds and abilities to detect SV change in healthy volunteers. Variation in Ftc induced by the respiratory cycle is important; measuring a clinically significant change in Ftc with statistical confidence requires a large sample of beats.

中文翻译：

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11 个公式的诊断特征，用于计算由可穿戴多普勒贴片测量的校正血流时间

背景 校正流量时间 (Ftc) 的变化是跟踪重症监护病房中每搏输出量 (SV) 的替代指标。已提出多个 Ftc 方程；许多人没有报告检测 SV 变化的诊断特征。此外，对呼吸循环引起的固有 Ftc 变异性知之甚少。材料和方法 使用可穿戴多普勒超声贴片，我们研究了 11 个 Ftc 方程的临床性能，以检测通过无创脉冲轮廓分析测量的 SV 变化 10%；26 名健康志愿者进行了标准化的心脏前负荷修正操作。结果 分析了 100 次心脏前负荷变化和 3890 次颈动脉搏动。研究的 11 个 Ftc 方程中的大多数具有相似的诊断属性。Wodeys 和 Chambers 的公式有相同的结果；Ftc 的 2% 变化检测到 SV 的 10% 变化，灵敏度和特异性分别为 96% 和 93%。同样，通过 Bazett 公式计算的 Ftc 变化 3% 显示出 91% 和 93% 的敏感性和特异性。Ftc Wodey 具有 100% 的一致性和 0.75 的 R 2 SV 变化；Ftc Chambers 和 Ftc Bazetts 的这些值分别为 99%、0.76 和 98%、0.71。作为探索性分析，我们使用 Wodey 和 Bazett 的方程研究了 3335 次颈动脉搏动，以了解在安静呼吸期间 Ftc 的分散情况。这些公式在安静呼吸期间 Ftc 的变异系数分别为 0.06 和 0.07。结论 用于从可穿戴多普勒超声贴片计算颈动脉 Ftc 的 11 个不同方程中的大多数具有相似的阈值和检测健康志愿者 SV 变化的能力。呼吸周期引起的 Ftc 变化很重要；以统计置信度测量 Ftc 的临床显着变化需要大量的节拍样本。