Volume 11 Supplement 2
System for automated discontinuous venous blood withdrawal for glucose determination of patients in the intensive care unit
© BioMed Central Ltd. 2007
Published: 22 March 2007
Intensive insulin therapy to establish normoglycaemia reduces mortality and morbidity in critically ill patients. Frequent glucose monitoring is restricted in critically ill patients due to the high workload that has to be performed by the staff. Hence the usage of an automated discontinuous venous blood sampling system might be an alternative to improve the adjustment of the insulin therapy. The primary aim of the study was to investigate whether the glucose concentration in manually withdrawn blood samples correlates with automated withdrawn blood samples.
In a 12-hour trial, six volunteers were investigated (male/female 5/1; age 28.2 ± 2.2 years, BMI 22.5 ± 1.3, nondiabetics). A 75 g OGTT was performed to enable a better dynamic range of the glucose values. Two venous cannulae were inserted into the dorsal hands for reference measurement and for connection to the automated blood sampling system. To reduce the volunteer's health risk, pressure, air bubble sensor and flushing fluid monitoring were integrated into the system. Blood samples were obtained frequently in 15/30-minute intervals. Roche Microsamplers and the OMNI S6 glucose analyser were used for determination of the blood readings.
The automated blood sampling system performed its operation in all volunteers over the whole trial period. The median Pearson coefficient of correlation between manual and automated withdrawn blood was 0.983 (0.862–0.995). Furthermore, the results (173 data pairs) were analysed via the recently published 'Insulin Titration Error Grid Analysis' and 99.4% were suggesting an acceptable treatment. The results of the traditional 'Error Grid Analysis' showed that 96% of the data were in zone A and 4% in zone B.
The automated discontinuous blood withdrawing system provides reproducible blood samples from peripheral venous blood. In combination with a glucose sensor and an algorithm it might be used in future as a closed loop system for insulin and glucose infusion at the ICU.