Methods for prediction of fluid responsiveness are needed during shock resuscitation. Fluid therapy remains a cornerstone in the treatment of shock and influences the outcomes directly. Excess or insufficient fluid administration is associated with increased morbidity and mortality. Prediction of fluid responsiveness means that a hemodynamic variable is used to determine how likely a patient is to respond to fluid bolus with a significant increase in their cardiac output. Depending on the response to fluids, patients are either responders or non-responders. Clinicians often rely on static indices of preload, like central venous pressure and pulmonary artery occlusion pressure, as a guide for fluid therapy. Unfortunately, whilst easy for use, these indices are of minimal value as predictors of fluid responsiveness. More recent research highlights hemodynamic variables related to cardiopulmonary interactions during mechanical ventilation. These dynamic indices, viz. stroke volume variation and pulse pressure variation, show a significantly better predictive value. To maximize the predictive value of dynamic indices, several conditions must be fulfilled. Another method for prediction of fluid responsiveness is represented by the functional hemodynamic tests: a heterogenous group of bedside tests for preload responsiveness. Fluid challenges remain popular, although repetitive use can be harmful. Hemodynamic tests, like passive leg raising or end-expiratory occlusion, modify the preload without fluid administration. Regardless of the test used, monitoring of cardiac output is needed to evaluate the heart's response to changes in preload. This review gives an overview of the methods for fluid responsiveness prediction, including those explored in the COVID-19 context.
There is a vast body of evidence in favour of individualising fluid therapy using dynamic hemodynamic indices like stroke volume variation (SVV). Patients with implanted intra-aortic balloon pump (IABP) are excluded from this approach because of pulse contour artifacts caused by the pump. The aim of this work is to test whether SVV can be used for fluid responsiveness prediction in these patients. Patients after cardiac surgery with implanted IABP were included in this study. SVV was measured after placing the IABP on standby mode for one minute. Cardiac output (CO) measurement was obtained via Swan-Ganz catheter before and after a 6 ml/kg fluid challenge. Fluid responsiveness was defined as increase of CO by at least 10%. SVV above 8.5% showed a good correlation with fluid responsiveness. Sensitivity was 95 (95% CI 85 to 100) and specificity 82 (95% CI 72 to 92). SVV had an area under the ROC curve 0.91 (95% CI 0.81 to 1.0) SVV is a good predictor of fluid responsiveness in patients with IABP. SVV should not be excluded as a fluid therapy guide for these patients. Placing the pump on standby for one minute allows obtaining an accurate measurement of this important variable.
There is a vast body of evidence in favor of individualising fluid therapy using dynamic hemodynamic indices like stroke volume variation (SVV). Patients with implanted intra-aortic balloon pump (IABP) are excluded from this approach because of pulse contour artifacts caused by the pump. The aim of this work is to test whether SVV can be used for fluid responsiveness prediction in these patients. Materials and methods: Patients after cardiac surgery with implanted IABP were included in this study. SVV was measured after placing the IABP on standy mode for one minute. Cardiac output (CO) measurement was obtained via Swan-Ganz catheter before and after a 6 ml/kg fluid challenge. Fluid responsiveness was defined as increase of CO by at least 10%. Results: SVV above 8.5% showed a good correlation with fuid responsiveness. Sensitivity was 95 (95% CI 85 to 100) and specificity 82 (95% CI 72 to 92). SVV had an area under the ROC curve 0.91 (95% CI 0.81 to 1.0) Conclusion: SVV is a good predictor of fluid responsiveness in patients with IABP. SVV should not be excluded as a fluid therapy guide for these patients. Placing the pump on standby for one minute allows obtaining an accurate measurement of this important variable.
BackgroundThe first surge of coronavirus disease 2019 (COVID-19) cases in Bulgaria occurred in the fall of 2020. To accommodate the rising number of critically ill patients, new intensive care units were formed in several hospitals. Here we describe the clinical presentation, patient characteristics, treatments and outcomes of mechanically ventilated COVID-19 patients in a newly formed COVID-19 ICU at a tertiary cardiac center in Sofia, Bulgaria.MethodsThis is a retrospective observational study of mechanically ventilated COVID-19 patients admitted to Sveta Ekaterina University Hospital in Sofia, Bulgaria, between November 4th, 2020 and January 6th, 2021. Data were collected from electronic and written patient records and charts.ResultsWe identified 38 critical care patients admitted with respiratory failure and treated with mechanical ventilation at our COVID-19 ICU during this period. The median age was 66 (IQR 57-76, range 27-89) and 74% were male. Most patients, 36 (95%), had at least one comorbidity. The most common comorbidities were hypertension, valvular heart disease, ischemic heart disease and diabetes mellitus. Overall, 27 (71%) patients had a concomitant cardiac disease other than hypertension and 24% were recent cardiac surgical patients. Inotropic support was required in 29 (76%) patients, renal replacement therapy in 12 (32%) patients and prone positioning and ECMO were used in 5 (13%) and 2 (5%) patients respectively. The median duration of mechanical ventilation was 7.5 (IQR 5-14) days overall and 9 (IQR 6-13) days for survivors. At 30-days 28 (74%) of patients had died. Overall, 32 (84%) patients died in hospital and only 6 (16%) patients were discharged home.ConclusionsDuring the first major surge of COVID-19 cases in Bulgaria, despite the wave arriving later than in other countries, the healthcare system was largely unprepared. In our setting, mortality in critically ill patients requiring mechanical ventilation was very high at 85%. There may be several factors contributing to these results, namely the predominance of cardiovascular comorbidities in our patient population, the strained ICU capacity and the lack of medical personnel to provide adequate intensive care to such complex patients.
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