Publications and Courses

Our reference manuals and training videos help clinicians and clinical research professionals to more effectively manage the cardiometabolic health of patients and clients, and to design and conduct clinical trials in a manner that ensures high quality data delivered on time and within budget.

Diet and Prevention of Type 2 Diabetes: Beyond Weight Loss and Exercise


$49.00    88 minutes

About the Course

Type 2 diabetes mellitus is an enormous public health concern worldwide that affects nearly 30 million people in the United States alone.  Diet is a vital tool not only for managing diabetes, but also for preventing it.  This webinar aims to deliver important information for healthcare providers, dietitians and research scientists to improve their understanding of the relationships between dietary factors and diabetes risk.  The course will provide the latest scientific evidence on:

  • Module 1: Epidemiology and pathophysiology of type 2 diabetes mellitus (T2D)
  • Module 2: Predictors of T2D risk and effects of interventions on incidence
  • Module 3: Summary of the associations and mechanisms through which diet may affect type 2 diabetes risk, with an emphasis on insulin sensitivity and glycemic load

Interpreting Efficacy Results from Cardiovascular Outcomes Trials


$29.00    57 minutes

About the Course

The course will provide a review of the following concepts:

  • Comparing measures of cardiovascular event incidence between groups
    1. Relative risk
    2. Hazard ratio
    3. Odds ratio
  • Comparing event rates and treatment effects
    1. Relative risk reduction
    2. Absolute risk reduction
    3. Number needed to treat (or harm)
  • Pitfalls in making comparisons between cardiovascular outcomes trials, including the three key questions
    1. Who was treated (risk profile)?
    2. What outcomes were assessed?
    3. Over how long a period?
  • Additional factors to consider in the interpretation of findings from cardiovascular outcomes trials
    1. Evaluating the roles of chance, bias and confounding
    2. Factors affecting validity and generalizability
    3. Assessing the potential for type I and type II statistical errors