1 / 23

Individualization Strategies for Older Patients with Diabetes

Explore frameworks and tools for personalizing medical decisions in older diabetic patients, optimizing glycemic control and health outcomes. Discover key subgroups, evidence from intervention trials, implications of glucose control, and reducing cardiovascular risk. Learn about classifying and managing comorbid conditions, assessing clinical complexity, and care guidelines for older patients. Explore tools for guiding individualization and future directions in diabetes care. For more information, contact ehuang@medicine.bsd.uchicago.edu.

maryrwhite
Download Presentation

Individualization Strategies for Older Patients with Diabetes

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Individualization Strategies for Older Patients with Diabetes Elbert S. Huang, MD MPH FACP University of Chicago

  2. Framework for Studying Individualization of Medical Decisions

  3. General Framework for Glycemic Control Decision A1C < 8% Course of Diabetes with A1C < 8% Health Outcomes A1C <7% Course of Diabetes with A1C < 7% Health Outcomes

  4. Individualization of Medical Decisions A1C < 8% Course of Diabetes with A1C < 8% Health Outcomes Subgroup 1 A1C <7% Course of Diabetes with A1C < 7% Health Outcomes A1C < 8% Course of Diabetes with A1C < 8% Health Outcomes Subgroup 2 A1C <7% Course of Diabetes with A1C < 7% Health Outcomes

  5. Evidence Regarding the Presence of Key Subgroups

  6. Intervention TrialMedian follow-up 10.0 years Intervention Trial + Post-trial monitoringMedian follow-up 16.8 years RR=0.88 (0.79-0.99) P=0.029 Conventional Sulfonylurea/Insulin Conventional Sulfonylurea/Insulin Trial in New Onset Diabetes (UKPDS) Lancet 1998;352(9131):837-53; NEJM 2008; 359:1577-1589

  7. Trials in Long-Duration of Diabetes N Engl J Med. 2008;358(24):2545-59. N Engl J Med. 2008;358(24):2560-72. N Engl J Med. 2009;360(2):129-39.

  8. Impact of intensive glucose-lowering therapy by coronary calcification (VADT) Reaven P, et al. Diabetes. 2009 Nov;58(11):2642-8.

  9. Implications of Being Sicker – Expected Benefits of Glucose Control Decline Huang ES, et al. Ann Intern Med. 2008; 149(1): 11-19.

  10. Reduction in Cardiovascular Risk Associated with A1C≤6.5% by TIBI Subgroup TIBI = Total Illness Burden Index Models adjusted for age and sex Greenfield S, et al. Ann Intern Med. December 2009;151(12):854-860

  11. Classifying Older Adults with Diabetes by Comorbid Conditions (NSHAP) Laiteerapong N, Iveniuk J, John P, Das A, Laumann EO, Huang ES. Prev Chronic Dis. 2012 May;9:E100.

  12. Clinical Complexity Groups (HRS) Blaum CS, et al. Med Care. 2010 April; 48(4): 327-334.

  13. Care Guidelines for Older Patients

  14. California Healthcare Foundation/AGS - 2003 Brown AF, et al. J Am Geriatr Soc 2003;51(Suppl. Guidelines): S265–S280

  15. Kirkman et al, Diabetes Care and JAGS Dec 2012

  16. Tools for Individualizing Diabetes Care in Clinical Practice

  17. Variables/Tools for Guiding Individualization • Individual variables • Age • Duration of diabetes • Cardiovascular disease • Mortality prediction models • Comorbidity alone (TIBI, NSHAP) • Comorbidity and functional status (HRS) • Diabetes simulation models • Decision support tools for clinical practice

  18. Comorbidity and Functional Status Index (JAMA 2006;295(7):801-808) JAMA. 2006;295(7):801-808

  19. Probability of death in 4-years

  20. Traditional Model of Diabetes Complications Advance in disease progression one year Retinopathy Module Nephropathy Module Alive Simulate natural history of diabetes progression according to patient characteristics Assign initial patient characteristics Neuropathy Module Mortality Module Coronary Heart Disease Module Dead Stroke Module Select next patient

  21. Conceptual Framework for Personalized Decision Support Wilkinson, Nathan, Huang. Curr Diab Rep. 2013 Apr;13(2):205-12

  22. Future Directions • Individualization of diabetes care is frequently cited but what it means varies • What is the best way to individualize care? • No clear consensus on categorization of older patients • Numerous variables to consider (life expectancy, duration of diabetes, pre-existing cardiovascular disease) • Need trials of competing algorithms and decision support tools

  23. Thank You ehuang@medicine.bsd.uchicago.edu

More Related