Abstract
BACKGROUND: The Canadian Pediatric Society (CPS) has endorsed an algorithm for the screening and immediate management of babies at risk of neonatal hypoglycemia that provides time-dependent glucose concentration action thresholds. The objective of this study was to evaluate the impact of glucose analytic error (bias and imprecision) on the misclassification of glucose meter results from a neonatal intensive care unit (NICU) using the CPS guidelines. METHODS: A simulation dataset of true glucose values (N = 100 000) was derived by finite mixture model analysis of NICU glucose data (N = 23 749). Bias and imprecision were added to create measured glucose values. The percentages of measured glucose values that were misclassified at CPS action thresholds were determined by Monte Carlo simulation. RESULTS: Measurement biases ranging from -20 to +20 mg/dL combined with coefficients of variation 0% to 20% were evaluated to predict misclassification rates at 32, 36, and 47 mg/dL. The models demonstrated low risk of false normoglycemia-at 5% CV and +10 mg/dL bias: 0.8% to 5% misclassification at the 32 and 47 mg/dL thresholds due to bias. The models demonstrated risk of false hypoglycemia-at 5% CV and -10 mg/dL bias: 3% to 12.5% misclassification at 32 and 47 mg/dL thresholds due to both bias and imprecision. CONCLUSION: Using CPS action thresholds, the simulation model predicted the proportion of neonates at risk of inappropriate clinical action-both of omission or "failure to treat" and commission or "overtreatment" in response to NICU glucose meter results at specific bias and imprecision values.