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

Predicting fluid responsiveness in patients under mechanical ventilation with low tidal volume (VT) is challenging. This study evaluated the ability of carotid corrected flow time (FTc) assessed by ultrasound for predicting the fluid responsiveness during low VT ventilation. Patients under postoperative mechanical ventilation and clinically diagnosed with hypovolemia were enrolled. Carotid FTc and pulse pressure variation (PPV) were measured at VT of 6 and 10 mL/kg predicted body weight (PBW). FTc was calculated using both Bazett’s (FTcB) and Wodey’s (FTcW) formulas. Fluid responsiveness was defined as a ≥15% increase in the stroke volume index assessed by FloTrac/Vigileo monitor after administration of 8 mL/kg of balanced crystalloid. Among 36 patients, 16 (44.4%) were fluid responders. The areas under the receiver operating characteristic curves (AUROCs) for the FTcB at VT of 6 and 10 mL/kg PBW were 0.897 (95% confidence interval [95% CI]: 0.750–0.973) and 0.895 (95% CI: 0.748–0.972), respectively. The AUROCs for the FTcW at VT of 6 and 10 mL/kg PBW were 0.875 (95% CI: 0.722–0.961) and 0.891 (95% CI: 0.744–0.970), respectively. However, PPV at VT of 6 mL/kg PBW (AUROC: 0.714, 95% CI: 0.539–0.852) showed significantly lower accuracy than that of PPV at VT of 10 mL/kg PBW (AUROC: 0.867, 95% CI: 0.712–0.957; p = 0.034). Carotid FTc can predict fluid responsiveness better than PPV during low VT ventilation. However, further studies using automated continuous monitoring system are needed before its clinical use.

Compressor Maps and Coupling: Symmetry, Paradox, and Clarity

The most common compressor map framework, referred to here as the β-framework, will be shown to suffer from limitations that grow more troublesome in the multiple-map environment. When maps are coupled in series in the β-framework, it is very common to find operating points that are physically unrealizable, but these cannot generally be avoided without first generating them. A feasible situation is described in which the β-framework leads to an apparent physical paradox. In the proposed S-framework, the map itself is recast in terms of independent variables (corrected speed and exit corrected flow) and dependent variables (inlet corrected flow and temperature ratio). The propagation of information in map coupling is split into an upstream-marching corrected flow ‘flux’ and a downstream-marching temperature ‘flux’. Finding the equilibrium operating point requires only finding a simple intersection between curves. The S-framework is then developed further into a more compact S’-framework that exhibits a natural set of qualitative symmetries. The S- and S’-frameworks are shown to simplify compressor map expression, resolve the problems shown with the β-framework, and aid intuition with regard to off-design phenomena. The resolution of the paradox using the S’-framework is a new description of multistage compressor performance hysteresis.

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

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.

The clinical impact of phase offset errors and different correction methods in cardiovascular magnetic resonance phase contrast imaging: a multi-scanner study

Background Cardiovascular magnetic resonance (CMR) phase contrast (PC) flow measurements suffer from phase offset errors. Background subtraction based on stationary phantom measurements can most reliably be used to overcome this inaccuracy. Stationary tissue correction is an alternative and does not require additional phantom scanning. The aim of this study was 1) to compare measurements with and without stationary tissue correction to phantom corrected measurements on different GE Healthcare CMR scanners using different software packages and 2) to evaluate the clinical implications of these methods. Methods CMR PC imaging of both the aortic and pulmonary artery flow was performed in patients on three different 1.5 T CMR scanners (GE Healthcare) using identical scan parameters. Uncorrected, first, second and third order stationary tissue corrected flow measurement were compared to phantom corrected flow measurements, our reference method, using Medis QFlow, Circle cvi42 and MASS software. The optimal (optimized) stationary tissue order was determined per scanner and software program. Velocity offsets, net flow, clinically significant difference (deviation > 10% net flow), and regurgitation severity were assessed. Results Data from 175 patients (28 (17–38) years) were included, of which 84% had congenital heart disease. First, second and third order and optimized stationary tissue correction did not improve the velocity offsets and net flow measurements. Uncorrected measurements resulted in the least clinically significant differences in net flow compared to phantom corrected data. Optimized stationary tissue correction per scanner and software program resulted in net flow differences (> 10%) in 19% (MASS) and 30% (Circle cvi42) of all measurements compared to 18% (MASS) and 23% (Circle cvi42) with no correction. Compared to phantom correction, regurgitation reclassification was the least common using uncorrected data. One CMR scanner performed worse and significant net flow differences of > 10% were present both with and without stationary tissue correction in more than 30% of all measurements. Conclusion Phase offset errors had a significant impact on net flow quantification, regurgitation assessment and varied greatly between CMR scanners. Background phase correction using stationary tissue correction worsened accuracy compared to no correction on three GE Healthcare CMR scanners. Therefore, careful assessment of phase offset errors at each individual scanner is essential to determine whether routine use of phantom correction is necessary. Trial registration Observational Study

Erenumab does not alter cerebral hemodynamics and endothelial function in migraine without aura

Objective To assess whether erenumab influences cerebral vasomotor reactivity and flow-mediated dilation in migraine patients. Methods Consecutive migraineurs prescribed erenumab at our Headache Centre and age and sex-matching controls were invited to participate in this observational longitudinal study. Patients were evaluated for cerebral vasomotor reactivity to hypercapnia (breath-holding index) in middle and posterior cerebral arteries and for brachial corrected flow mediated dilation at baseline (T0), after 2 weeks from the first erenumab injection (T2) and after 2 weeks from the fourth Erenumab injection (T18). Patients displaying a reduction of at least 50% in monthly migraine days after completing the fourth month of therapy were classified as responders. Results Sixty patients and 25 controls agreed to participate. Middle and posterior cerebral artery mean flow velocities, breath-holding index and flow-mediated dilation did not differ at T0 and from T0 to T2 in patients and controls. In patients, we neither observed a variation of the explored variables from T0 to T18 nor an interaction between evaluation times (T0–T2 or T0–T18) and chronic condition at T0, responder state or erenumab fourth dose. Conclusions Our findings demonstrate that erenumab preserves cerebral vasomotor reactivity and flow-mediated dilation in migraineurs without aura.