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Can a central blood volume deficit be detected by systolic pressure variation during spontaneous breathing?

ABSTRACT: Whether during spontaneous breathing arterial pressure variations (APV) can detect a volume deficit is not established. We hypothesized that amplification of intra-thoracic pressure oscillations by breathing through resistors would enhance APV to allow identification of a reduced cardiac output (CO). This study tested that hypothesis in healthy volunteers exposed to central hypovolemia by head-up tilt.Thirteen healthy volunteers were exposed to central hypovolemia by 45° head-up tilt while breathing through a facemask with 7.5 cmH2O inspiratory and/or expiratory resistors. A brachial arterial catheter was used to measure blood pressure and thus systolic pressure variation (SPV), pulse pressure variation and stroke volume variation . Pulse contour analysis determined stroke volume (SV) and CO and we evaluated whether APV could detect a 10 % decrease in CO.During head-up tilt SV decreased form 91 (±46) to 55 (±24) mL (mean?±?SD) and CO from 5.8 (±2.9) to 4.0 (±1.8) L/min (p?

SUBMITTER: Dahl M

PROVIDER: S-EPMC4982018 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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Can a central blood volume deficit be detected by systolic pressure variation during spontaneous breathing?

Dahl Michael M Hayes Chris C Steen Rasmussen Bodil B Larsson Anders A Secher Niels H NH

BMC anesthesiology 20160811 1

<h4>Background</h4>Whether during spontaneous breathing arterial pressure variations (APV) can detect a volume deficit is not established. We hypothesized that amplification of intra-thoracic pressure oscillations by breathing through resistors would enhance APV to allow identification of a reduced cardiac output (CO). This study tested that hypothesis in healthy volunteers exposed to central hypovolemia by head-up tilt.<h4>Methods</h4>Thirteen healthy volunteers were exposed to central hypovole ...[more]

PMID: 27515038

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Project description:BackgroundWhether cardiovascular risk is more tightly associated with central (cSBP) than brachial (bSBP) systolic pressure remains debated, because of their close correlation and uncertain thresholds to differentiate cSBP into normotension versus hypertension.MethodsIn a person-level meta-analysis of the International Database of Central Arterial Properties for Risk Stratification (n=5576; 54.1% women; mean age 54.2 years), outcome-driven thresholds for cSBP were determined and whether the cross-classification of cSBP and bSBP improved risk stratification was explored. cSBP was tonometrically estimated from the radial pulse wave using SphygmoCor software.ResultsOver 4.1 years (median), 255 composite cardiovascular end points occurred. In multivariable bootstrapped analyses, cSBP thresholds (in mm Hg) of 110.5 (95% CI, 109.1-111.8), 120.2 (119.4-121.0), 130.0 (129.6-130.3), and 149.5 (148.4-150.5) generated 5-year cardiovascular risks equivalent to the American College of Cardiology/American Heart Association bSBP thresholds of 120, 130, 140, and 160. Applying 120/130 mm Hg as cSBP/bSBP thresholds delineated concordant central and brachial normotension (43.1%) and hypertension (48.2%) versus isolated brachial hypertension (5.0%) and isolated central hypertension (3.7%). With concordant normotension as reference, the multivariable hazard ratios for the cardiovascular end point were 1.30 (95% CI, 0.58-2.94) for isolated brachial hypertension, 2.28 (1.21-4.30) for isolated central hypertension, and 2.02 (1.41-2.91) for concordant hypertension. The increased cardiovascular risk associated with isolated central and concordant hypertension was paralleled by cerebrovascular end points with hazard ratios of 3.71 (1.37-10.06) and 2.60 (1.35-5.00), respectively.ConclusionsIrrespective of the brachial blood pressure status, central hypertension increased cardiovascular and cerebrovascular risk indicating the importance of controlling central hypertension.

Project description:Integrating spontaneous breathing into mechanical ventilation (MV) can speed up liberation from it and reduce its invasiveness. On the other hand, inadequate and asynchronous spontaneous breathing has the potential to aggravate lung injury. During use of airway-pressure-release-ventilation (APRV), the assisted breaths are difficult to measure. We developed an algorithm to differentiate the breaths in a setting of lung injury in spontaneously breathing ewes. We hypothesized that differentiation of breaths into spontaneous, mechanical and assisted is feasible using a specially developed for this purpose algorithm. Ventilation parameters were recorded by software that integrated ventilator output variables. The flow signal, measured by the EVITA® XL (Lübeck, Germany), was measured every 2 ms by a custom Java-based computerized algorithm (Breath-Sep). By integrating the flow signal, tidal volume (VT) of each breath was calculated. By using the flow curve the algorithm separated the different breaths and numbered them for each time point. Breaths were separated into mechanical, assisted and spontaneous. Bland Altman analysis was used to compare parameters. Comparing the values calculated by Breath-Sep with the data from the EVITA® using Bland-Altman analyses showed a mean bias of - 2.85% and 95% limits of agreement from - 25.76 to 20.06% for MVtotal. For respiratory rate (RR) RRset a bias of 0.84% with a SD of 1.21% and 95% limits of agreement from - 1.53 to 3.21% were found. In the cluster analysis of the 25th highest breaths of each group RRtotal was higher using the EVITA®. In the mechanical subgroup the values for RRspont and MVspont the EVITA® showed higher values compared to Breath-Sep. We developed a computerized method for respiratory flow-curve based differentiation of breathing cycle components during mechanical ventilation with superimposed spontaneous breathing. Further studies in humans and optimizing of this technique is necessary to allow for real-time use at the bedside.

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Can a central blood volume deficit be detected by systolic pressure variation during spontaneous breathing?

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Can a central blood volume deficit be detected by systolic pressure variation during spontaneous breathing?

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