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AHA SHAPE Symposium 2017 Dr. Naghavi Presentation

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AHA Unofficial SHAPE Satellite Symposium 2017 Presentation

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AHA SHAPE Symposium 2017 Dr. Naghavi Presentation

  1. 1. Morteza Naghavi, M.D. Founder and Executive Chairman of SHAPE The 2nd Machine Learning Vulnerable Patient Symposium Towards Developing an Artificial Intelligence-Based Forecast System for Predicting Short-Term CVD Events A Satellite Event in Conjunction with 2017 Annual Scientific Sessions of American Heart Association
  2. 2. Let’s Begin with the End
  3. 3. Goal: Eradicate Heart Attacks(Unpredicted CVD Events)
  4. 4. Now Let’s See Where We Are
  5. 5. Last year2,626,418 people died in the US 614,348 (23.4%) of them died due to heart disease and 133,033 (5.1%) due to stroke Total 747,381 (28.5%)
  6. 6. Unlike Cancer • Unlike in cancer where oncologists deal with hundreds of different pathologies and specific therapeutic strategies, in CVD over 50% of cases we deal with one pathology: Atherosclerosis (The number 1 killer of mankind)
  7. 7. Unpredicted
  8. 8. In >50% of victims, the first symptom of asymptomatic atherosclerosis is a sudden cardiac death or acute MI.
  9. 9. Men Women 0 10 20 30 40 50 60 70 Patients Diagnosed with CHD (%) Murabito et al Circulation 1993 Sudden Cardiac Death or Acute MI as Initial Presentation of CHD 62% 42%
  10. 10. Add 10yrs to Life Expectancy of Mankind Early detection and treatment of atherosclerosis to prevent acute CVD events is likely to increase life expectancy in excess of 10 years. That’s HUGE!!! A Vaccination Type Impact on Public Health
  11. 11. How Do We Get There? A heart-attack free future
  12. 12. Let’s Draw an Analogy Heart Attack vs. Hurricane
  13. 13. Imagine if the weatherman says there is a 7.5% chance of a category 5 hurricane in the next 10 years. Do you think people would take immediate preventive actions like boarding up their windows, buying hurricane supplies, or even changing their daily routines?
  14. 14. Imagineif heart attack and stroke were predicted similar to hurricanes Harvey and Irma with sufficient short-term alerts to at-risk people to take preventive actions.
  15. 15. Heart Attack vs. Hurricane THE GALVESTON HORROR
  16. 16. Heart Attack vs. Hurricane THE GALVESTON HORROR
  17. 17. Heart Attack vs. Hurricane THE GALVESTON HORROR
  18. 18. Heart Attack vs. Hurricane THE GALVESTON HORROR
  19. 19. Heart Attack vs. Hurricane THE GALVESTON HORROR
  20. 20. Heart Attack vs. Hurricane THE GALVESTON HORROR
  21. 21. Heart Attack vs. Hurricane THE GALVESTON HORROR
  22. 22. Heart Attack vs. Hurricane 10-year Risk Prediction vs. 10-day Risk Prediction
  23. 23. What has SHAPE done?
  24. 24. Naghavi et. al. Circulation Journal The Vulnerable Patient Consensus Statement
  25. 25. Naghavi et. al. Circulation Journal The Vulnerable Patient Consensus Statement
  26. 26. SHAPE Task Force Meeting
  27. 27. SHAPE Guidelines Published
  28. 28. Coronary Artery Calcium Score 32
  29. 29. The Writing Sub-Committee of the SHAPE Task Force (left to right): Drs Budoff, Falk, Rumberger, Naghavi, Fayad, Hecht, and Berman
  30. 30. Atherosclerosis Test Very Low Risk3 Negative Test • CACS =0 • CIMT <50th percentile Lower Risk Moderate Risk Positive Test • CACS ≥1 • CIMT 50th percentile or Carotid Plaque Moderately High Risk High Risk Very High Risk No Risk Factors5 + Risk Factors • CACS <100 & <75th% • CIMT <1mm & <75th% & no Carotid Plaque • Coronary Artery Calcium Score (CACS) or • Carotid IMT (CIMT) & Carotid Plaque4 • CACS 100-399 or >75th% • CIMT 1mm or >75th% or <50% Stenotic Plaque • CACS >100 & >90th% or CACS 400 • 50% Stenotic Plaque6 LDL Target <160 mg/dl <130 mg/dl <130 mg/dl <100 Optional <100 mg/dl <70 Optional <70 mg/dl Re-test Interval 5-10 years 5-10 years Individualized Individualized Individualized All >75y receive unconditional treatment2 Apparently Healthy Population Men>45y Women>55y1 ExitExit Myocardial IschemiaTest NoAngiography Follow Existing Guidelines Yes The 1st SHAPE Guidelines Step 1 Step 2 Step 3 Optional CRP>4mg ABI<0.9 1: No history of angina, heart attack, stroke, or peripheral arterial disease. 2: Population over age 75y is considered high risk and must receive therapy without testing for atherosclerosis. 3: Must not have any of the following: Chol>200 mg/dl, blood pressure >120/80 mmHg, diabetes, smoking, family history, metabolic syndrome. 4: Pending the development of standard practice guidelines. 5: High cholesterol, high blood pressure, diabetes, smoking, family history, metabolic syndrome. 6: For stroke prevention, follow existing guidelines.
  31. 31. Existing Guidelines (Status Quo): • Screen for Risk Factors of Atherosclerosis • Treat Risk Factors of Atherosclerosis The SHAPE Guidelines: • Screen for Atherosclerosis (the Disease) Regardless of Risk Factors • Treat based on the Severity of the Disease and its Risk Factors SHAPE v.s. Status Quo
  32. 32. Number (per year) Estimated Impact of SHAPE (Sensitivity Analysis Range) Estimated Change in Cost CVD Deaths 910,600 ↓10% (5%-25%) ($1.2 b) MI (prevalence) 7,200,000 ↓ 25% (5%-35%) ($18.0 b) Chest Pain Symptoms (ER visits) 6,500,000 ↓ 5% (2.5%-25%) ($4.1 b) Hospital Discharge for Primary Diagnosis of CVD 6,373,000 ↑ 10% (5%-25%) $3.8 b Hospital Discharge for Primary Diagnosis of CHD 970,000 ↓ 10% (5%-25%) ($9.9 b) Cholesterol Lowering Therapy ↑ 50 % (50%-65%) 8.00 b CV Imaging 8,700,000 ↑ 10% (5%-25%) $358 m Angiography 6,800,000 ↑ 15% - CTA (2.5%-25%) $600 m PCI (percutaneous coronary interventions per year) 657,000 ↓ 10% (5%-50%) ($580 m) CABS (coronary artery bypass surgeries per year) 515,000 ↓ 5% (2.5%-50%) ($672 m) Total Δ in Cost ($21.5 b) Cost Effectiveness of the SHAPE Guidelines
  33. 33. Heart Attack vs. Hurricane 10-year Risk Prediction vs. 10-day Risk Prediction
  34. 34. Long term predictions do not trigger immediate preventive actions. Preventive cardiology needs a short-term predictor.
  35. 35. Heart Attack vs. Hurricane
  36. 36. Machine Learning Vulnerable Patient Project.
  37. 37. http://shapesociety.org/videos-2/
  38. 38. http://shapesociety.org/videos/
  39. 39. The Big Idea: Developing an Artificial Intelligence-based Forecast System for Prediction of Heart Attacks within 12 Months Use machine learning to create new algorithms to detect who will experience a CHD event within a year (The Vulnerable Patient). Algorithms will be based on banked biospecimen and information collected days up to 12 months prior to the event. We will utilize existing cohorts such as MESA, Heinz Nixdorf Recall Study, Framingham Heart Study, BioImage Study and the Dallas Heart Study. External validation to test for discrimination and calibration will be conducted using other longitudinal observational studies that provide adjudicated cardiovascular event information such as the MiHeart, JHS, DANRISK and ROBINSCA. Additionally, we will use machine learning to characterize individuals who, despite high conventional risk, have lived over 80 years with no CHD events (The Invulnerable). We expect to discover new targets for drug and possibly vaccine development. We will make the algorithms available as an open source tool to collect additional data over time and increase its predictive value.
  40. 40. What a great idea, what are you waiting for? Funding!
  41. 41. Will Super Intelligent Computers Replace Physicians?
  42. 42. Will Super Intelligent Computers Replace Physicians? Absolutely Yes When and in What Areas? Umm let’s discuss
  43. 43. Inspired by IBM Watson
  44. 44. Google DeepMind 49
  45. 45. Machine vs. Cardiologist

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