Riccardo Candido

Algorithms for personalized therapy of type 2 diabetes: results of a web-based international survey

Objective In recent years increasing interest in the issue of treatment personalization for type 2 diabetes (T2DM) has emerged. This international web-based survey aimed to evaluate opinions of physicians about tailored therapeutic algorithms developed by the Italian Association of Diabetologists (AMD) and available online, and to get suggestions for future developments. Another aim of this initiative was to assess whether the online advertising and the survey would have increased the global visibility of the AMD algorithms. Research design and methods The web-based survey, which comprised five questions, has been available from the homepage of the web-version of the journal Diabetes Care throughout the month of December 2013, and on the AMD website between December 2013 and September 2014. Participation was totally free and responders were anonymous. Results Overall, 452 physicians (M=58.4%) participated in the survey. Diabetologists accounted for 76.8% of responders. The results of the survey show wide agreement (>90%) by participants on the utility of the algorithms proposed, even if they do not cover all possible needs of patients with T2DM for a personalized therapeutic approach. In the online survey period and in the months after its conclusion, a relevant and durable increase in the number of unique users who visited the websites was registered, compared to the period preceding the survey. Conclusions Patients with T2DM are heterogeneous, and there is interest toward accessible and easy to use personalized therapeutic algorithms. Responders opinions probably reflect the peculiar organization of diabetes care in each country.

Strategies Used by Patients with Type 1 Diabetes to Avoid Hypoglycemia in a 24×1-Hour Marathon: Comparison with the Amounts of Carbohydrates Estimated by a Customizable Algorithm

OBJECTIVES The preferred countermeasure to avoid exercise-related hypoglycemia was investigated in a group of patients with type 1 diabetes participating in a stressful event, a 24×1-hour relay marathon. The carbohydrates actually consumed were compared to those estimated for each patient by applying a customizable algorithm, Exercise Carbohydrates Requirement Estimating Software (ECRES), based on patients usual therapy and diet and on the exercise characteristics. METHODS Glycemia was tested at the start, middle and end of the races. Usual therapies and diets and the adopted countermeasures were recorded in detail. RESULTS We studied 19 patients who walked/ran 10.4±2.8 km with a heart rate of 167±11 beats per minute. Of the 19 patients, 7 patients reduced the administered insulin (premeal bolus or basal infusion rate). Glycemia fell by the end of the races (p=0.006; median -1.8 mmol⋅L-1; interquartile range -0.4 mmol⋅L-1 to -5.3 mmol⋅L-1), despite 9 patients being hyperglycemic at the start. Of the patients, 14 concluded the race with glycemia on target, and 4 patients were hyperglycemic. Amounts of carbohydrates actually consumed (median 30 g; interquartile range 0 g to 71 g) were not significantly different from those estimated by ECRES (median 38 g; interquartile range 24 g to 68 g), the 2 quantities being significantly related (R=0.64; p=0.003). ECRES estimated lower carbohydrate levels (-13 g) than the amounts actually consumed by the 4 patients who concluded their exercises with hyperglycemia. CONCLUSIONS Patients preferred to consume extra carbohydrates to avoid the possible exercise-induced hypoglycemia. ECRES would provide satisfactory estimates of the carbohydrate requirements, even for a stressful condition, and almost equal to the quantities consumed following medical advice.