OBJECTIVE: Intensive insulin therapy in the critically ill reduces mortality but carries the risk of increased hypoglycemia. Point-of-care blood glucose analysis is standard; however, anemia causes falsely high values and potentially masks hypoglycemia. Permissive anemia is practiced routinely in most intensive care units. We hypothesized that point-of-care glucometer error due to anemia is prevalent, can be corrected mathematically, and correction uncovers occult hypoglycemia during intensive insulin therapy. DESIGN: The study has both retrospective and prospective phases. We reviewed data to verify the presence of systematic error, determine the source of error, and establish the prevalence of anemia. We confirmed our findings by reproducing the error in an in vitro model. Prospective data were used to develop a correction formula validated by the Monte Carlo method. Correction was implemented in a burn intensive care unit and results were evaluated after 9 mos. SETTING: Burn and trauma intensive care units at a single research institution. PATIENTS/ SUBJECTS: Samples for in vitro studies were taken from healthy volunteers. Samples for formula development were from critically ill patients who received intensive insulin therapy. INTERVENTIONS: Insulin doses were calculated based on predicted serum glucose values from corrected point-of-care glucometer measurements. MEASUREMENTS AND MAIN RESULTS: Time-matched point-of-care glucose, laboratory glucose, and hematocrit values. We previously found that anemia (hematocrit <34%) produces systematic error in glucometer measurements. The error was correctible with a mathematical formula developed and validated, using prospectively collected data. Error of uncorrected point-of-care glucose ranged from 19% to 29% (p < .001), improving to < or = 5% after mathematical correction of prospective data. Comparison of data pairs before and after correction formula implementation demonstrated a 78% decrease in the prevalence of hypoglycemia in critically ill and anemic patients treated with insulin and tight glucose control (p < .001). CONCLUSIONS: A mathematical formula that corrects erroneous point-of-care glucose values due to anemia in intensive care unit patients reduces the prevalence of hypoglycemia during intensive insulin therapy.
OBJECTIVE: Intensive insulin therapy in the critically ill reduces mortality but carries the risk of increased hypoglycemia. Point-of-care blood glucose analysis is standard; however, anemia causes falsely high values and potentially masks hypoglycemia. Permissive anemia is practiced routinely in most intensive care units. We hypothesized that point-of-care glucometer error due to anemia is prevalent, can be corrected mathematically, and correction uncovers occult hypoglycemia during intensive insulin therapy. DESIGN: The study has both retrospective and prospective phases. We reviewed data to verify the presence of systematic error, determine the source of error, and establish the prevalence of anemia. We confirmed our findings by reproducing the error in an in vitro model. Prospective data were used to develop a correction formula validated by the Monte Carlo method. Correction was implemented in a burn intensive care unit and results were evaluated after 9 mos. SETTING: Burn and trauma intensive care units at a single research institution. PATIENTS/ SUBJECTS: Samples for in vitro studies were taken from healthy volunteers. Samples for formula development were from critically ill patients who received intensive insulin therapy. INTERVENTIONS:Insulin doses were calculated based on predicted serum glucose values from corrected point-of-care glucometer measurements. MEASUREMENTS AND MAIN RESULTS: Time-matched point-of-care glucose, laboratory glucose, and hematocrit values. We previously found that anemia (hematocrit <34%) produces systematic error in glucometer measurements. The error was correctible with a mathematical formula developed and validated, using prospectively collected data. Error of uncorrected point-of-care glucose ranged from 19% to 29% (p < .001), improving to < or = 5% after mathematical correction of prospective data. Comparison of data pairs before and after correction formula implementation demonstrated a 78% decrease in the prevalence of hypoglycemia in critically ill and anemicpatients treated with insulin and tight glucose control (p < .001). CONCLUSIONS: A mathematical formula that corrects erroneous point-of-care glucose values due to anemia in intensive care unit patients reduces the prevalence of hypoglycemia during intensive insulin therapy.
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