Predicting fluid responsiveness with stroke volume variation despite multiple extrasystoles.

To investigate the ability of a new stroke volume variation algorithm to predict fluid responsiveness during general anesthesia and mechanical ventilation in animals with multiple extrasystoles. Prospective laboratory animal experiment. Investigational laboratory. Eight instrumented pigs. Eight anesthetized and mechanically ventilated pigs were monitored with an arterial line and a pulmonary artery catheter. Multiple extrasystoles were induced by right ventricular pacing (25% of heart beats). Arterial pressure waveforms were recorded and stroke volume variation was computed from the new and from the standard algorithm. The new stroke volume variation algorithm is designed to restore the respiratory component of the arterial pressure waveform despite multiple ectopic heart beats. Cardiac output was measured before and after 56 fluid boluses (7 mL/kg of 6% hydroxy ethyl starch) performed at different volemic states. A positive response to fluid boluses (>15% increase in cardiac output) was observed in 21 of 56 boluses. The new stroke volume variation was higher in responders than in nonresponders (19% ± 5% vs. 12% ± 3%, p < .05), whereas the standard stroke volume variation was similar in the two groups (29% ± 8% vs. 26% ± 11%, p = .4). Receiver operating characteristic curve analysis showed that the new stroke volume variation was an accurate predictor of fluid responsiveness (sensitivity = 86%, specificity = 85%, best cutoff value = 14%, area under the curve = 0.892 ±, whereas the standard stroke volume variation was not (area under the curve = 0.596 ± 0.077). In contrast to the standard stroke volume variation, the new stroke volume variation algorithm was able to predict fluid responsiveness in animals with multiple ventricular extrasystoles.

Citation

Maxime Cannesson, Nam Phuong Tran, Max Cho, Feras Hatib, Frederic Michard. Predicting fluid responsiveness with stroke volume variation despite multiple extrasystoles. Critical care medicine. 2012 Jan;40(1):193-8

Mesh Tags

PMID: 21926593

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