Algorithm for complementary and alternative medicine practice and research in type 2 diabetes

Abstract

Objective: To develop a model to direct the prescription of nutritional and botanical medicines in the treatment of type 2 diabetes for both clinical and research purposes.

Methods: Available literature on nutritional and botanical medicines was reviewed and categorized as follows: antioxidant/anti-inflammatory; insulin sensitizer; and beta-cell protectant/insulin secretagogue. Literature describing laboratory assessment for glycemic control, insulin resistance, and beta-cell reserve was also reviewed and a clinical decision tree was developed.

Results: Clinical algorithms were created to guide the use of nutritional and botanic medicines using validated laboratory measures of glycemic control, insulin sensitivity, and beta-cell reserve. Nutrient and botanic medicines with clinical trial research support include coenzyme Q10, carnitine, alpha-lipoic acid, N-acetylcysteine, vitamin D, vitamin C, vitamin E, chromium, vanadium, omega-3 fatty acids, cinnamon (Cinnamomum cassia), fenugreek (Trigonella foenum-graecum), and gymnema (Gymnema sylvestre).

Conclusions: Clinical algorithms can direct supplementation in clinical practice and provide research models for clinical investigation. Algorithms also provide a framework for integration of future evidence as it becomes available. Research funding to investigate potentially beneficial practices in complementary medicine is critically important for optimal patient care and safety.