Focus on focus: Lack of coherence between systemic and microvascular indices of oedema formation

Background: Fluid therapy remains a cornerstone of therapy in shock states. However, fluid overloading ultimately results in oedema formation which is related to excess morbidity and mortality. Handheld microscopes are now frequently used to study the sublingual microcirculation. As a corollary, these devices measure focal distance, or surface to capillary distance. Physiologically, this could represent a microvascular index of oedema formation and could have the potential to guide fluid therapy. This potential tool should be investigated, especially given the frequently reported lack of coherence between systemic and microvascular parameters in the critically ill. Therefore, we set out to assess the correlation between microvascular focal distance and systemic indices of oedema formation, specifically fluid balance and weight gain. Methods: Following ex vivo testing of focal distance measurement reliability, we conducted a prospective observational cohort study in patients admitted to the intensive care unit of our university teaching hospital. We determined surface to capillary distance using sidestream dark field (SDF) and incident dark field (IDF) imaging by assessing the focal distance point or object distance range at which a sharp recording could be made. Measurements were performed in post-cardiac surgery patients and in patients following emergency admission at two time points separated by at least several hours. Data on fluid balance, weight and weight gain were collected simultaneously. Results: Sixty patients were included. The focal setting, focus point for SDF and the object distance range for IDF did not differ significantly between time points. Focus was not correlated with difference in fluid balance or weight gain. Conclusions: There is a lack of coherence between surface to capillary distance as determined by SDF or IDF imaging and fluid balance or weight gain. Thus, focal distance as a microvascular index of oedema formation cannot currently be used as a proxy for systemic indices of oedema formation. However, given the lack of coherence, further research should determine whether focal distance may provide better guidance for fluid therapy than traditional markers of overzealous fluid administration

Minimally invasive prediction of ScvO2 in high-risk surgery:The introduction of a model Index of Oxygenation

INTRODUCTION: The purpose of this study was to examine the trilateral relationship between cardiac index (CI), tissue oxygen saturation (StO2) and central venous oxygen saturation (ScvO2) and subsequently develop a model to predict ScvO2 on minimal invasive manner in patients undergoing major elective surgery.METHODS: The continuous data of thirty-three high-risk noncardiac surgical patients from a randomized controlled trial (NCT01342900) were analyzed on a between- and within-patient basis using regression on group means, random-effects Generalized Least Squares (GLS) regression. Trend concordance was assessed using a four-quandrant plot. We developed a model Index of Oxygenation (IO) to predict ScvO2 based on CI, StO2, heart rate (HR), fraction of inspired oxygen (FiO2) and mean arterial pressure (MAP). The dataset was split by randomizing each patient into an estimation or validation subsample. Randomization was stratified by type of surgery. IO was validated using random-effects GLS regression, a Bland-Altman analysis and four-quadrant concordance.RESULTS: The patients were monitored for an average duration on 227.5 minutes, giving 7509 observations in total. We could not establish a positive significant association between StO2 and CI using regression analyses (slope of -1.08 (p=0.15; 95%CI -2.54 to 0.377; within-R2 0.01; figure1.) Trending concordance is non-existent (on a 5-minute basis: 56%) or very weak (on a 60-minute basis: 73%; figure 2). CI was found to be strongly associated with ScvO2 on a within-patient basis, but lacks predictive power in explaining between-patient differences. StO2, in contrast, was significantly associated with between-patient ScvO2 differences, but does not follow (short term) within-patient ScvO2 variability (figure 3). The mean difference or bias between ScvO2 and IO is 1.07% (95% limits of agreement -14.7% to 16.9%). Concordance for 5-minute and 60-minute trends was 71% and 90%, respectively. The IO model was translated into a linear prediction, which was then scaled back to the mean (78.5) and SD (6.49) of ScvO2 in the estimation sample, according to the following formula (the brackets denote standardized variables): Figure 4 displays the complete intraoperative ScvO2 data and the IO prediction for two patients in the validation sample.CONCLUSIONS: StO2 cannot be considered a flow dependent variable during high-risk surgery. We hypothesize that StO2 is a gauge of microcirculatory functioning more than a measure of systemic oxygen balance. IO is a better estimator is ScvO2 than either CI or StO2 alone and could potentially be used for minimally invasive monitoring of systemic oxygenation.<br/

Minimally invasive prediction of ScvO2 in high-risk surgery: The introduction of a model Index of Oxygenation

INTRODUCTION: The purpose of this study was to examine the trilateral relationship between cardiac index (CI), tissue oxygen saturation (StO2) and central venous oxygen saturation (ScvO2) and subsequently develop a model to predict ScvO2 on minimal invasive manner in patients undergoing major elective surgery. METHODS: The continuous data of thirty-three high-risk noncardiac surgical patients from a randomized controlled trial (NCT01342900) were analyzed on a between- and within-patient basis using regression on group means, random-effects Generalized Least Squares (GLS) regression. Trend concordance was assessed using a four-quandrant plot. We developed a model Index of Oxygenation (IO) to predict ScvO2 based on CI, StO2, heart rate (HR), fraction of inspired oxygen (FiO2) and mean arterial pressure (MAP). The dataset was split by randomizing each patient into an estimation or validation subsample. Randomization was stratified by type of surgery. IO was validated using random-effects GLS regression, a Bland-Altman analysis and four-quadrant concordance. RESULTS: The patients were monitored for an average duration on 227.5 minutes, giving 7509 observations in total. We could not establish a positive significant association between StO2 and CI using regression analyses (slope of -1.08 (p=0.15; 95%CI -2.54 to 0.377; within-R2 0.01; figure1.) Trending concordance is non-existent (on a 5-minute basis: 56%) or very weak (on a 60-minute basis: 73%; figure 2). CI was found to be strongly associated with ScvO2 on a within-patient basis, but lacks predictive power in explaining between-patient differences. StO2, in contrast, was significantly associated with between-patient ScvO2 differences, but does not follow (short term) within-patient ScvO2 variability (figure 3). The mean difference or bias between ScvO2 and IO is 1.07% (95% limits of agreement -14.7% to 16.9%). Concordance for 5-minute and 60-minute trends was 71% and 90%, respectively. The IO model was translated into a linear prediction, which was then scaled back to the mean (78.5) and SD (6.49) of ScvO2 in the estimation sample, according to the following formula (the brackets denote standardized variables):  Figure 4 displays the complete intraoperative ScvO2 data and the IO prediction for two patients in the validation sample. CONCLUSIONS: StO2 cannot be considered a flow dependent variable during high-risk surgery. We hypothesize that StO2 is a gauge of microcirculatory functioning more than a measure of systemic oxygen balance. IO is a better estimator is ScvO2 than either CI or StO2 alone and could potentially be used for minimally invasive monitoring of systemic oxygenation

Focus on focus: lack of coherence between systemic and microvascular indices of oedema formation

Background: Fluid therapy remains a cornerstone of therapy in shock states. However, fluid overloading ultimately results in oedema formation which is related to excess morbidity and mortality. Handheld microscopes are now frequently used to study the sublingual microcirculation. As a corollary, these devices measure focal distance, or surface to capillary distance. Physiologically, this could represent a microvascular index of oedema formation and could have the potential to guide fluid therapy. This potential tool should be investigated, especially given the frequently reported lack of coherence between systemic and microvascular parameters in the critically ill. Therefore, we set out to assess the correlation between microvascular focal distance and systemic indices of oedema formation, specifically fluid balance and weight gain. Methods: Following ex vivo testing of focal distance measurement reliability, we conducted a prospective observational cohort study in patients admitted to the intensive care unit of our university teaching hospital. We determined surface to capillary distance using sidestream dark field (SDF) and incident dark field (IDF) imaging by assessing the focal distance point or object distance range at which a sharp recording could be made. Measurements were performed in post-cardiac surgery patients and in patients following emergency admission at two time points separated by at least several hours. Data on fluid balance, weight and weight gain were collected simultaneously. Results: Sixty patients were included. The focal setting, focus point for SDF and the object distance range for IDF did not differ significantly between time points. Focus was not correlated with difference in fluid balance or weight gain. Conclusions: There is a lack of coherence between surface to capillary distance as determined by SDF or IDF imaging and fluid balance or weight gain. Thus, focal distance as a microvascular index of oedema formation cannot currently be used as a proxy for systemic indices of oedema formation. However, given the lack of coherence, further research should determine whether focal distance may provide better guidance for fluid therapy than traditional markers of overzealous fluid administration. RESULTS: Sixty patients were included. Focal setting, focus point for SDF and an object distance range for IDF did not differ significantly between time points. Focus was not correlated with difference in fluid balance or weight gain. CONCLUSIONS: There is a lack of coherence between surface to capillary distance as determined by SDF or IDF imaging and fluid balance or weight gain. Thus, focal distance as a microvascular index of edema formation cannot currently be used as a proxy for systemic indices of edema formation. However, given the lack of coherence, further research should determine whether focal distance may provide better guidance for fluid therapy than traditional markers of overzealous fluid administration