Corrected carotid flow time and passive leg raise as a measure of volume status

Chebl, Ralphe Bou; Wuhantu, Jeffrey; Kiblawi, Shafeek; Dagher, Gilbert Abou; Zgheib, Hady; Bachir, Rana; Carnell, Jennifer

doi:10.1016/j.ajem.2018.10.047

Cited by 17 publications

(10 citation statements)

References 19 publications

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“…Unfortunately, no other haemodynamic parameters were measured in that study. Similar increases in CFTc were observed in a population of blood donors [ 65 ], end-stage renal failure patients on dialysis [ 66 , 67 ], and healthy volunteers after prolonged fasting [ 68 ], but every time without recording any haemodynamic parameters except for MAP and HR, thus not correlating changes in CFTc with CO. In another study, Barjaktarevic et al [ 69 ] enrolled 77 patients with undifferentiated shock, monitoring cardiac output by a system based on bioreactance.…”

Section: Arterial Doppler Monitoringsupporting

confidence: 56%

“…Regarding limitations, most published studies have focused on patients outside of the intensive care setting and data for critically ill patients are limited. Furthermore, in a large portion of available studies, CO was not monitored directly, and its eventual changes were only assumed as a consequence of intravascular volume reduction or upon clinical presentation [ 64 , 65 , 66 , 67 , 68 ]. Lastly, despite the aforementioned technical simplicity of this technique, there are several studies indicating low reproducibility between sonographers [ 77 ] and insufficient reliability in patients undergoing the PLR manoeuvre [ 78 ].…”

Section: Arterial Doppler Monitoringmentioning

confidence: 99%

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Novel Methods for Predicting Fluid Responsiveness in Critically Ill Patients—A Narrative Review

et al. 2022

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In patients with acute circulatory failure, fluid administration represents a first-line therapeutic intervention for improving cardiac output. However, only approximately 50% of patients respond to fluid infusion with a significant increase in cardiac output, defined as fluid responsiveness. Additionally, excessive volume expansion and associated hyperhydration have been shown to increase morbidity and mortality in critically ill patients. Thus, except for cases of obvious hypovolaemia, fluid responsiveness should be routinely tested prior to fluid administration. Static markers of cardiac preload, such as central venous pressure or pulmonary artery wedge pressure, have been shown to be poor predictors of fluid responsiveness despite their widespread use to guide fluid therapy. Dynamic tests including parameters of aortic blood flow or respiratory variability of inferior vena cava diameter provide much higher diagnostic accuracy. Nevertheless, they are also burdened with several significant limitations, reducing the reliability, or even precluding their use in many clinical scenarios. This non-systematic narrative review aims to provide an update on the novel, less employed dynamic tests of fluid responsiveness evaluation in critically ill patients.

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Section: Arterial Doppler Monitoringsupporting

confidence: 56%

Section: Arterial Doppler Monitoringmentioning

confidence: 99%

Novel Methods for Predicting Fluid Responsiveness in Critically Ill Patients—A Narrative Review

et al. 2022

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“…Change in the duration of systole has been used as an accurate surrogate for stroke volume (SV) in the critically ill, chronically ill, and in healthy volunteers [1][2][3][4][5][6][7]. Indeed, previous animal work employing isolated, supported heart preparations has shown that when heart rate and blood pressure are controlled, the duration of systole is directly related to SV [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

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

Kenny

MacKenzie

Eibl

et al. 2020

ICMx

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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.

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“…Sepsis studies have revealed an association between poorer outcomes and elevated P ra ( 39 ), Doppler flow abnormalities have been correlated with organ dysfunction ( 24 ), and certain groups are advocating de-resuscitation strategies such as the ROSE approach ( 40 ). Notably, following successful hemodialysis, carotid Doppler-corrected flow time rises with PLR ( 41 ) suggesting a rising P ra -SV slope. Additionally, loss of pulsatile venous morphology is observed with successful blood volume removal in the ICU ( 42 ).…”

Section: Discussionmentioning

confidence: 99%

Inferring the Frank–Starling Curve From Simultaneous Venous and Arterial Doppler: Measurements From a Wireless, Wearable Ultrasound Patch

Kenny

MacKenzie

Rola³

et al. 2021

Front. Med. Technol.

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The Frank–Starling relationship is a fundamental concept in cardiovascular physiology, relating change in cardiac filling to its output. Historically, this relationship has been measured by physiologists and clinicians using invasive monitoring tools, relating right atrial pressure (Pra) to stroke volume (SV) because the Pra-SV slope has therapeutic implications. For example, a critically ill patient with a flattened Pra-SV slope may have low Pra yet fail to increase SV following additional cardiac filling (e.g., intravenous fluids). Provocative maneuvers such as the passive leg raise (PLR) have been proposed to identify these “fluid non-responders”; however, simultaneously measuring cardiac filling and output via non-invasive methods like ultrasound is cumbersome during a PLR. In this Hypothesis and Theory submission, we suggest that a wearable Doppler ultrasound can infer the Pra-SV relationship by simultaneously capturing jugular venous and carotid arterial Doppler in real time. We propose that this method would confirm that low cardiac filling may associate with poor response to additional volume. Additionally, simultaneous assessment of venous filling and arterial output could help interpret and compare provocative maneuvers like the PLR because change in cardiac filling can be confirmed. If our hypothesis is confirmed with future investigation, wearable monitors capable of monitoring both variables of the Frank–Starling relation could be helpful in the ICU and other less acute patient settings.

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Corrected carotid flow time and passive leg raise as a measure of volume status

Cited by 17 publications

References 19 publications

Novel Methods for Predicting Fluid Responsiveness in Critically Ill Patients—A Narrative Review

Novel Methods for Predicting Fluid Responsiveness in Critically Ill Patients—A Narrative Review

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

Inferring the Frank–Starling Curve From Simultaneous Venous and Arterial Doppler: Measurements From a Wireless, Wearable Ultrasound Patch

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