A probabilistic model for predicting hypoglycemia in type 2 diabetes mellitus: The Diabetes Outcomes in Veterans Study (DOVES).

BACKGROUND To develop and validate a method for estimating hypoglycemia risk in stable, insulin-treated subjects with type 2 diabetes mellitus. METHODS Subjects (n = 195) monitored their blood glucose levels 4 times daily for 8 weeks. An 8-week mean blood glucose value (GLUMEAN) with standard deviation (GLUSD) was derived for each patient. Subjects were then randomly allocated to a derivation or validation set. For the derivation set, we developed a logistic function based on GLUMEAN and GLUSD to describe the 8-week risk of hypoglycemia (blood glucose < or =60 mg/dL [3.3 mmol/L]). This function was used to assign a predicted probability of hypoglycemia to each subject in the validation set. Subjects were assigned to risk quartiles and followed up for up to 52 weeks. RESULTS We evaluated 195 subjects, 95% of whom were men and 69% of whom were non-Hispanic white. For 72 derivation subjects, GLUMEAN and GLUSD were highly influential determinants of hypoglycemia during intensified monitoring. The 123 validation subjects were followed up for 39.7 +/- 7.1 weeks (mean +/- SD). The occurrence of long-term hypoglycemia differed significantly across risk quartiles (19.4%, 36.7%, 61.3%, and 77.4%, respectively; P<.001). Receiver operating characteristic curve analysis showed that the area for the probability function (0.746 +/- 0.046) was significantly higher than the area for hemoglobin A1c (0.549 +/- 0.052) because their 95% confidence intervals did not overlap. The function also identified subjects who developed long-term hypoglycemia at a rate exceeding the median frequency. CONCLUSIONS Self-monitoring of blood glucose is superior to hemoglobin A1c measurement in predicting long-term hypoglycemia in persons with type 2 diabetes. The risk of hypoglycemia associated with treatment intensification may be offset by strategies that reduce glucose variability.