Diagnostic characteristics of 11 formulae for calculating corrected flow time as measured by a wearable Doppler patch

Abstract

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%. FtcWodey had 100% concordance and an R2 of 0.75 with change in SV; these values were 99%, 0.76 and 98%, 0.71 for FtcChambers and FtcBazetts, 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.

Ability of Carotid Corrected Flow Time to Predict Fluid Responsiveness in Patients Mechanically Ventilated Using Low Tidal Volume after Surgery

“…In addition, there were little differences between FTc 6 and FTc 10 . However, a recent study showed that the respiratory cycle could induce a variation in FTc [ 28 ]. This could affect the results of our study.…”

A novel, hands-free ultrasound patch for continuous monitoring of quantitative Doppler in the carotid artery

“…However, not all clinical studies have replicated these findings 36 . One contributing factor to these discrepancies may be the small number of beats sampled (e.g., 1–3) used to calculate blood flow metrics coupled with normal, inherent VTI variation introduced by the respiratory cycle 37 – 39 . The hands-free CW Doppler patch is well-suited to overcome this potential source of variability by acquiring continuous measurements over many beats 20 .…”

Carotid Doppler Measurement Variability in Functional Hemodynamic Monitoring: An Analysis of 17,822 Cardiac Cycles

“…Importantly, the number of beats sampled varies as a function of CV and the threshold to detect. For example, detecting a 3% change in FTc ( 6 ) with a CV of 4.5% demands roughly 36 beats sampled before and after an intervention.…”

“…It was placed by palpation below the angle of the jaw; when an audible Doppler shift and spectrogram consistent with the common carotid artery were obtained, the patch was adhered to the neck. The duration of systole, in seconds, was used to calculate the corrected flow time (FTc), as described previously ( 5 , 6 ).…”