RESUMEN
OBJECTIVE: To investigate whether the pleth variability index, a noninvasive and continuous tool, can predict fluid responsiveness in mechanically ventilated patients with circulatory insufficiency. DESIGN: Prospective study. SETTING: Surgical intensive care unit of a university hospital. PATIENTS: Forty mechanically ventilated patients with circulatory insufficiency in whom volume expansion was planned by attending physician. Exclusion criteria included spontaneous respiratory activity, cardiac arrhythmia, known intracardiac shunt, severe hypoxemia (Pao2/Fio2 <100 mm Hg), contraindication for passive leg raising, left ventricular ejection fraction of <50%, and hemodynamic instability during the procedure. INTERVENTIONS: Fluid challenge with 500 mL of 130/0.4 hydroxyethyl-starch if respiratory variations in arterial pulse pressure were ≥ 13% or with passive leg raising if variations in arterial pulse pressure were <13%. MEASUREMENTS AND MAIN RESULTS: Pleth variability index, variations in arterial pulse pressure, and cardiac output estimated by echocardiography were recorded before and after fluid challenge. Fluid responsiveness was defined as an increase in cardiac output of ≥ 15%. Twenty-one patients were responders and 19 were nonresponders. Mean ± sd pleth variability index (28% ± 13% vs. 11% ± 4%) and arterial pulse pressure variation (22% ± 11% vs. 5% ± 2%) values at baseline were significantly higher in responders than in nonresponders. The pleth variability index threshold value of 17% allowed discrimination between responders and nonresponders with a sensitivity of 95% (95% confidence interval, 74% to 100%) and a specificity of 91% (95% confidence interval, 70% to 99%). The pleth variability index at baseline correlated (r = .72, p < .0001) with the percentage change in cardiac output induced by fluid challenge, suggesting that a higher pleth variability index at baseline will correlate with a higher percentage change in cardiac output after volume expansion. CONCLUSIONS: The pleth variability index can predict fluid responsiveness noninvasively in intensive care unit patients under mechanical ventilation.