Head-to-head comparison of two continuous glucose monitoring systems on a cardio-surgical ICU.

In critical illness hypo-and hyperglycemia have a negative influence on patient outcome. Continuous glucose monitoring (CGM) could help in early detection of hypo-and hyperglycemia. A requirement for these new methods is an acceptable accuracy and precision in clinical practice. In this pilot study we prospectively evaluated the accuracy and precision of two CGM sensors (subcutaneous sensor: Sentrino®, Medtronic and intravasal sensor: Glucoclear®, Edwards) in 20 patients on a cardio-surgical ICU in a head to head comparison. CGM data were recorded for up to 48 h and values were compared with blood-gas-analysis (BGA) values, analysed with Bland-Altman-plots and color-coded surveillance error-grids. Shown are means ± standard deviations. In total 270/255 intravasal/subcutaneous pairs with BGA-values were analysed. The average runtime of the sensors was 28.4 ± 6.4 h. Correlation with BGA values yielded a correlation coefficient of 0.76 (subcutaneous sensor) and 0.92 (intravasal sensor). The Bland Altman Plots revealed an accuracy of 2.5 mg/dl, and a precision of + 43.0 mg/dl to - 38.0 mg/dl (subcutaneous sensor) and an accuracy of - 6.0 mg/dl, and a precision of + 12.4 mg/dl to - 24.4 mg/dl (intravasal sensor). No severe hypoglycemic event, defined as BG level below 40 mg/dl, occurred during treatment. Both sensors showed good accuracy in comparison to the BGA values, however they differ regarding precision, which in case of the subcutaneous sensor is considerable high.

Detection of thoracic vascular structures by electrical impedance tomography: a systematic assessment of prominence peak analysis of impedance changes.

OBJECTIVE: Electrical impedance tomography (EIT) is a non-invasive and radiation-free bedside monitoring technology, primarily used to monitor lung function. First experimental data shows that the descending aorta can be detected at different thoracic heights and might allow the assessment of central hemodynamics, i.e. stroke volume and pulse transit time. APPROACH: First, the feasibility of localizing small non-conductive objects within a saline phantom model was evaluated. Second, this result was utilized for the detection of the aorta by EIT in ten anesthetized pigs with comparison to thoracic computer tomography (CT). Two EIT belts were placed at different thoracic positions and a bolus of hypertonic saline (10 ml, 20%) was administered into the ascending aorta while EIT data were recorded. EIT images were reconstructed using the GREIT model, based on the individual's thoracic contours. The resulting EIT images were analyzed pixel by pixel to identify the aortic pixel, in which the bolus caused the highest transient impedance peak in time. MAIN RESULTS: In the phantom, small objects could be located at each position with a maximal deviation of 0.71 cm. In vivo, no significant differences between the aorta position measured by EIT and the anatomical aorta location were obtained for both measurement planes if the search was restricted to the dorsal thoracic region of interest (ROIs). SIGNIFICANCE: It is possible to detect the descending aorta at different thoracic levels by EIT using an intra-aortic bolus of hypertonic saline. No significant differences in the position of the descending aorta on EIT images compared to CT images were obtained for both EIT belts.

Perioperative assessment of regional ventilation during changing body positions and ventilation conditions by electrical impedance tomography.

BACKGROUND: Lung-protective ventilation is claimed to be beneficial not only in critically ill patients, but also in pulmonary healthy patients undergoing general anaesthesia. We report the use of electrical impedance tomography for assessing regional changes in ventilation, during both spontaneous breathing and mechanical ventilation, in patients undergoing robot-assisted radical prostatectomy. METHODS: We performed electrical impedance tomography measurements in 39 patients before induction of anaesthesia in the sitting (M1) and supine position (M2), after the start of mechanical ventilation (M3), during capnoperitoneum and Trendelenburg positioning (M4), and finally, in the supine position after release of capnoperitoneum (M5). To quantify regional changes in lung ventilation, we calculated the centre of ventilation and 'silent spaces' in the ventral and dorsal lung regions that did not show major impedance changes. RESULTS: Compared with the awake supine position [2.3% (2.3)], anaesthesia and mechanical ventilation induced a significant increase in silent spaces in the dorsal dependent lung [9.2% (6.3); P<0.05]. Capnoperitoneum and the Trendelenburg position led to a significant increase in such spaces [11.5% (8.9)]. Silent space in the ventral lung remained constant throughout anaesthesia. CONCLUSION: Electrical impedance tomography was able to identify and quantify on a breath-by-breath basis circumscribed areas, so-called silent spaces, within healthy lungs that received little or no ventilation during general anaesthesia, capnoperitoneum, and different body positions. As these silent spaces are suggestive of atelectasis on the one hand and overdistension on the other, they might become useful to guide individualized protective ventilation strategies to mitigate the side-effects of anaesthesia and surgery on the lungs.