Literature DB >> 24203263

Variations in the pre-ejection period induced by ventricular extra systoles may be feasible to predict fluid responsiveness.

Simon Tilma Vistisen1, Kristian Kjær Andersen, Christian Alcaraz Frederiksen, Hans Kirkegaard.   

Abstract

Monitoring that can predict fluid responsiveness is an unsettled matter for spontaneously breathing patients. Based on the convincing results with dynamic monitoring based on preload variations induced by mechanical ventilation, we hypothesised that the extra systolic post-ectopic beat could constitute a similar intermittent preload shift inducing a brief variation in blood pressure and that the magnitude of this variation could predict the hemodynamic response to volume expansion in sedated pigs. Ten pigs were sedated and hemodynamically monitored and four intravascular volume shifts were made: blood depletion (25% of estimated blood volume; 660 ml), retransfusion (of 500 ml depleted blood), and two sequential volume expansions (500 ml colloid each). Between volume shifts, supraventricular and ventricular extra systoles were induced by a pacemaker. Hemodynamic variables such as pulse pressure (PP) and pre-ejection period (PEP) were determined for each heart beat and the hemodynamic changes in the post-ectopic beats compared to sinus beats was extracted (e.g. ∆PP and ∆PEP) and used to predict fluid responsiveness of subsequent volume expansions which was determined by receiver operating characteristic (ROC) curves. Ventricular extra systoles were generally useful for fluid responsiveness prediction (ROC areas >0.65). ∆PEP variables best predicted fluid responsiveness: ∆PEP derived from arterial pressure curve and ECG had ROC area of 0.84 and sensitivity of 0.77 and specificity of 0.71; ∆PEP derived from plethysmographic curve and ECG had ROC area of 0.79 and sensitivity of 0.71 and specificity of 0.70. However, ∆PP was not a useful variable in this study (ROC area <0.65). Hemodynamic analysis of post ectopic beats may be a feasible method for fluid responsiveness prediction.

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Year:  2013        PMID: 24203263     DOI: 10.1007/s10877-013-9528-4

Source DB:  PubMed          Journal:  J Clin Monit Comput        ISSN: 1387-1307            Impact factor:   2.502


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