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Previous studies have shown an association between the frequency of self-monitored blood glucose (SMBG) and hemoglobin A1c. Randomized controlled trials (RCTs) have shown this to be a causal correlation for insulin-using patients. Several studies have used linear regression, but a straight line will descend into negative hemoglobin A1c values (an impossibility). This study developed a cause-and-effect-based nonlinear model to predict the outcome of RCTs on this subject, tested this model with clinical data, and offered this model in place of linear regression, especially for the still-debated case of noninsulin-using patients.

journal of diabetes science and technology

A Cause-and-Effect-Based Mathematical Curvilinear Model That Predicts the Effects of Self-Monitoring of Blood Glucose Frequency on Hemoglobin A1c and is Suitable for Statistical Correlations