Key result
Brachial cuff oscillometry moderately correlates with MRI stroke volume estimates at r=~0.54.
Why the study?
Steady state hemodynamics such as stroke volume have been difficult to measure clinically due to technical challenges, motivating evaluation of a brachial cuff-based estimation method.
Does a model-based algorithm utilizing brachial cuff pressure waveforms accurately estimate stroke volume compared to cardiac MRI and inert gas rebreathing in patients with myocardial infarction and healthy individuals?
Cross-Sectional (n=118)
Yes
Does a model-based algorithm utilizing brachial cuff pressure waveforms accurately estimate stroke volume compared to cardiac MRI and inert gas rebreathing in patients with myocardial infarction and healthy individuals?
Effect estimate: r = 0.54
Absolute Event Rate: 67.2% vs 76%
p-value: p=<0.001
Brachial oscillometry combined with mathematical modeling provides a reasonable non-invasive estimate of stroke volume under static conditions, offering a potential tool for clinical hemodynamic assessment.
May support non-invasive stroke volume estimates in stable patients; leaves open prospective validation before clinical adoption.
Background Steady state hemodynamics [Stroke Volume - SV, cardiac output, peripheral resistance (Rp)] have attracted researchers in hypertension for decades. However, due to technical difficulties, they never entered clinical medicine. Objective To investigate the performance of a model-based algorithm, utilizing brachial pressure waveforms obtained with a cuff, to estimate stroke volume. The model combines a modified three-element like Windkessel system and transmission line theory. Participants and Methods In study 1, 97 patients with reperfused acute myocardial infarction and two healthy controls underwent cardiac magnetic resonance imaging (1.5 Tesla Magnetom, Siemens, Germany), and SV was measured with standard protocols from short axis cine images (11 slices). In study 2, 19 healthy individuals (12 females) had SVs measured with inert gas rebreathing at rest, and during light exercise (20 watts) on a bicycle ergometer. In both studies, model-based SV, estimated with a brachial cuff, was the comparator. Results In study 1, both SVs were moderately correlated (r = 0.54, p < 0.001). Using the method of Bland–Altman, mean difference between both methods was 8.7 ml (1.96 limits of agreement were 36.7 and –19.3 ml), with no systematic bias. In study 2, both SVs were moderately correlated at rest (r = 0.63, p = 0.004) and at light exercise (r = 0.70, p = 0.0057). Using the method of Bland-Altman, mean difference between both methods was 8.6 ml (1.96 limits of agreement were 39.2 and –22.0 ml) at rest, and 42.7 ml (1.96 limits of agreement were 95.4 and –10.1 ml) at light exercise. Conclusion Brachial oscillometry and mathematical modeling provide a reasonable estimate of SV under static conditions, which may be a useful addition to 24-h measurements of blood pressure and pulsatile hemodynamics.
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WEBER et al. (2020) conducted a cross-sectional in Acute myocardial infarction and healthy individuals (n=118). Brachial-cuff derived pressure waveforms with mathematical modeling vs. Cardiac MRI and Inert Gas Rebreathing was evaluated on Correlation of stroke volume between oscillometric method and MRI (Study 1) (r = 0.54, p=<0.001). Brachial oscillometry combined with mathematical modeling provided stroke volume estimates that moderately correlated with MRI (r = 0.54) and inert gas rebreathing at rest (r = 0.63).
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