Does Professional Continuous Glucose Monitoring Help In Improving Hemoglobin A1C In People With Diabetes ? A Clinical Practice Experience

Program: Abstracts - Orals, Featured Poster Presentations, and Posters
Session: SUN 839-872-Diabetes & Obesity Management
Sunday, June 16, 2013: 1:45 PM-3:45 PM
Expo Halls ABC (Moscone Center)

Poster Board SUN-870
Nisha Acharya*1, James F Bena2, Shristi Kunwar1, Purnima Tripathy1 and Marwan Hamaty1
1Cleveland Clinic Foundation, Cleveland, OH, 2Quantitative Health Sciences, Cleveland Clinic Foundation, Cleveland, OH
Background: Professional continuous glucose monitoring (P-CGM) helps identifying glucose patterns beyond self-monitoring of blood glucose (SMBG) and hemoglobinA1c (A1C).  P-CGM has shown to be superior to SMBG in lowering A1C, detecting and reducing severe hypoglycemia in people with type 1 diabetes (DM), particularly when compliance was high. The benefit of P-CGM in clinical practice setting is unknown. Methods: Retrospective data collection identified 51 patients with DM who had P-CGM at our diabetes center. We compared baseline and post-CGM A1C. We explored the contribution of confounding factors to A1C changes, such as type of DM, medications used to treat DM, number of follow up visits, change in BMI, frequency of hypoglycemia, frequency of medication changes and whether medication change was made based on P-CGM data. Wilcoxon signed rank test was used to compare change in A1C, BMI from baseline to final visit.  Associations between change in A1C and categorical factors were performed using Wilcoxon rank sum tests, while associations with ordered and continuous measures were assessed using Spearman correlations. Result: Of 51 patients 31 (60.8%) were female, mean age was 48 yrs (range 19-83), 42 (82.4%) had type 1 DM, 42 of them were on insulin therapy and 9 were on oral agents and insulin. Mean follow up duration was 270.1 days (range 74.2-451). All patients had change in regimen once or more during follow up period. Regimen changes based on CGM data were made in 46 (90.2%) patients. There was significant decrease in post CGM A1C, median -0.4 (range -3.0 to 3.6), p = 0.001. Patient with the highest baseline A1C had the largest decreases in A1C, r = - 0.41, 95% CI (-0.67, -0.15), p = 0.003. No statistically significant association was seen between change in A1C and all other variables (BMI change r = 0.07 (-0.22, 0.36), p = 0.64, hypoglycemia r = 0.19 (-0.14, 0.51), p = 0.25 , frequency of medication change r = 0.23 (-0.05, 0.51), p = 0.11, number of follow up r = 0.10 (-0.19, 0.39), p = 0.48, diabetes regimen p = 0.29). Conclusion: P-CGM-derived information seemed to have contributed to improving A1C among our patients, independent of frequency of visits, medication changes and without increasing the frequency of hypoglycemia. P-CGM should be used routinely for patients with unexplained glucose patterns.

Nothing to Disclose: NA, JFB, SK, PT, MH

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