AHA Unofficial SHAPE Satellite Symposium 2017 Presentation

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. Let’s Begin with
the End

3. Goal:
Eradicate Heart
Attacks(Unpredicted CVD Events)

4. Now Let’s See
Where We Are

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. 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. Unpredicted

8. In >50% of victims,
the first symptom of
asymptomatic
atherosclerosis is a
sudden cardiac
death or acute MI.

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. 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. How Do We Get There?
A heart-attack free
future

12. Let’s Draw an Analogy
Heart Attack
vs. Hurricane

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. 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. Heart Attack vs. Hurricane
THE GALVESTON HORROR

16. Heart Attack vs. Hurricane
THE GALVESTON HORROR

17. Heart Attack vs. Hurricane
THE GALVESTON HORROR

18. Heart Attack vs. Hurricane
THE GALVESTON HORROR

19. Heart Attack vs. Hurricane
THE GALVESTON HORROR

20. Heart Attack vs. Hurricane
THE GALVESTON HORROR

21. Heart Attack vs. Hurricane
THE GALVESTON HORROR

22. Heart Attack vs. Hurricane
10-year Risk Prediction vs. 10-day Risk Prediction

25. What has SHAPE done?

26. Naghavi et. al. Circulation Journal
The Vulnerable Patient Consensus Statement

27. Naghavi et. al. Circulation Journal
The Vulnerable Patient Consensus Statement

28. SHAPE Task Force Meeting

30. SHAPE Guidelines Published

32. Coronary Artery Calcium Score
32

33. The Writing Sub-Committee of the SHAPE Task Force (left to right): Drs Budoff, Falk, Rumberger, Naghavi,
Fayad, Hecht, and Berman

34. 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.

35. 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

36. 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

37. Heart Attack vs. Hurricane
10-year Risk Prediction vs. 10-day Risk Prediction

38. Long term predictions do not
trigger immediate preventive
actions.
Preventive cardiology needs a
short-term predictor.

39. Heart Attack vs. Hurricane

40. Machine Learning Vulnerable
Patient Project.

41. http://shapesociety.org/videos-2/

42. http://shapesociety.org/videos/

43. 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.

44. What a great idea, what are you
waiting for?
Funding!

45. Will Super Intelligent Computers Replace
Physicians?

47. Will Super Intelligent Computers
Replace Physicians?
Absolutely Yes
When and in What Areas?
Umm let’s discuss

48. Inspired by IBM Watson

49. Google DeepMind
49

50. Machine vs. Cardiologist