title: A model of mild hypoglycemia.
abstract: OBJECTIVE
  To investigate the impact associated with mild hypoglycemia among patients with type 2 diabetes (T2DM) in the United States and to identify risk factors among different subpopulations.
  
  
  METHODS
  We performed a literature search to gather available data allowing estimation of rates of mild hypoglycemia. Because risk factors are interdependent, risk factors included in the model were based on those reported within multivariate analyses or judged to be biologically plausible by the medical community. Based on literature search results, we built a mathematical model predicting the rates of mild hypoglycemia in individual patients as a function of the patient's antidiabetic medications, hemoglobin A1c levels, duration of diabetes, kidney function, and body mass index.
  
  
  RESULTS
  We estimated an overall average rate of mild hypoglycemia among US patients with T2DM of 2.2 ± 0.8 events per person per year. Patients taking oral antidiabetic medications only had an average rate of 1.9 ± 0.8 events per person per year. The average rate for all patients taking insulin, including those combining it with other antidiabetic medications, was 4.9 ± 2.0 events per person per year. Mild hypoglycemia rates increased with age, with 80-year-old patients experiencing 1.5 times the risk of 40-year-old patients. Based on published values for direct and indirect medical costs for mild hypoglycemia events, we determined that the economic impact in the US of mild hypoglycemic events is approximately $900 million per year, roughly equal to that of severe hypoglycemic events. One of the key limitations to our model is that it applies to the US population under standard medical care and not to clinical trials and does not include certain known risk factors such as rigorous exercise.
  
  
  CONCLUSIONS
  Understanding the benefit versus risk of glycemic control and hypoglycemia is fundamental to the successful management of patients with T2DM. Our validated hypoglycemia model is an important step in addressing this issue and may be helpful to researchers, clinicians, and payers to determine the patients who are at the highest risk for hypoglycemia, whether a patient is experiencing events at 'higher-than-expected' rates, and the corresponding economic burden.
authors.affiliation: Evidera , San Francisco, CA , USA.
authors.forename: Stuart
authors.initials: S
authors.lastname: Samuel
authors.forename: Devesh
authors.initials: D
authors.lastname: Goswami
authors.forename: Kenny
authors.initials: K
authors.lastname: Shum
authors.forename: Kristina S
authors.initials: KS
authors.lastname: Boye
authors.forename: Badri
authors.initials: B
authors.lastname: Rengarajan
authors.forename: Bradley
authors.initials: B
authors.lastname: Curtis
authors.forename: Sarah E
authors.initials: SE
authors.lastname: Curtis
mesh_terms: D000328:Adult; D017668:Age of Onset; D000368:Aged; D000369:Aged, 80 and over; D015992:Body Mass Index; D003924:Diabetes Mellitus, Type 2 / Q000188:drug therapy*; D005260:Female; D006442:Glycated Hemoglobin / Q000032:analysis; D006801:Humans; D007003:Hypoglycemia / Q000175:diagnosis / Q000453:epidemiology / Q000503:physiopathology; D007004:Hypoglycemic Agents / Q000627:therapeutic use*; D007677:Kidney Function Tests; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D015203:Reproducibility of Results; D018570:Risk Assessment / Q000379:methods; D012307:Risk Factors; D012720:Severity of Illness Index; D014481:United States
chemical_list: D006442:Glycated Hemoglobin; D007004:Hypoglycemic Agents
keywords: Archimedes Model; Hypoglycemia; Mild hypoglycemia; Model; Type 2 diabetes