Thursday, September 19, 2019

A Bayesian Approach to the Diagnosis of Hypertrophic Cardiomyopathy During Athlete Screening

Screening athletes for causes of sudden cardiac death (SCD) is difficult. The conditions that cause SCD are rare and sometimes difficult to diagnose, especially in athletes under 35 years old. Many hundreds of athletes must be screened to find even a single case of a potentially lethal heart condition. In many series of SCD in athletes, hypertrophic cardiomyopathy (HCM) is a leading cause (1). There are characteristics of HCM that can be detected by the history (syncope, family history), physical exam (a systolic murmur louder on Valsalva maneuver) and by electrocardiogram (EKG).  In addition, it can be detected easily on echocardiography (echo), even a quick screening echo.  Therefore, since HCM can be deadly and since it can be detected using information available at a routine screening, the diagnosis must be made. Would an additional tool, such as Bayesian analysis, be helpful in diagnosing HCM during an athlete screening session?

Bayes Theorem is useful when trying to make a diagnosis under uncertainty.  It closely follows clinical medicine; as information is received, the probability of the diagnosis is revised either upward or downward. Bayes Theorem requires three inputs: a pretest probability (or prevalence of disease), the sensitivity of a finding or a test and the specificity of the finding or test.  It works as follows. A patient comes to a doctor’s office and a disease is suspected. The history is taken and the patient reports a symptom. The doctor knows the prevalence of the disease in the population and looks up the sensitivity and specificity of the finding in picking out the disease entity.  The numbers are put in Bayes formula and a posttest probability is calculated. In other words, the patient is suspected of having a disease, reports a symptom consistent with the disease and the doctor’s suspicion of the disease then increases. If the patient has a physical finding consistent with a disease, then the posttest probability just calculated now becomes the pretest probability and the sensitivity and specificity of the physical finding are used to find a new posttest probability.  If the patient then has an abnormal EKG, then previous posttest probability and the sensitivity and specificity of the EKG abnormality are used to revise the estimate of disease probability, and so on.  As new information is obtained, the previous probability of disease is used to come up with a new estimate- exactly as is done in an office setting- as new information comes to light, the probability of disease goes either up or down. This approach was used by Diamond and Forrester (2) to calculate the probability of coronary artery disease and has been used many times since then. This same method can help diagnose HCM during screening of athletes.

The prevalence of HCM is well known (3). The generally accepted prevalence is that 1 person out of 500 people (0.2%) in the population will have HCM.  This has recently been revised and the new estimate is 1 person out of 200 people (0.5%) may have HCM.  For the purposes of the screening tool, both numbers are used to provide a range of probabilities. 

A detailed history and physical are the cornerstones of the cardiovascular screening of athletes. Every athlete fills out a standard American Heart Association questionnaire and a physical examination is performed.  For the purpose of diagnosing HCM, two items on the questionnaire are of interest.  A prior history of unexplained syncope may be associated with HCM.  This has been studied and it has been determined that the sensitivity for unexplained syncope in diagnosing HCM is 35% and the specificity is 85% (4). Since HCM is a genetic disease and runs in families, the family history is very important.  A family history of unexplained SCD has a sensitivity of 42% and a specificity of 79% in diagnosing HCM (4).  A family history of HCM carries a sensitivity of 44% and a specificity of 99% (5). Findings on physical examination can also determine the presence of HCM.  The classic murmur of HCM is a harsh systolic murmur that gets louder with Valsalva maneuver. The sensitivity of a systolic murmur, louder with Valsalva, is 65% while the specificity is 96% (4). The history and physical examination may not be able to definitively diagnose HCM (the sensitivities are quite low), but if these factors are present, the probability of HCM increases and additional testing is warranted.

The next test during an athletic screening is the EKG.  While controversial and not performed routinely in all parts of the world, the EKG should be done if one suspects HCM.  Many patients with HCM have abnormal and bizarre EKGs.  An EKG is abnormal if it meets the findings of the 2013 Seattle criteria and the updated 2017 International criteria.  The sensitivity of an abnormal EKG in diagnosing HCM using the Seattle/International criteria is 93% with a specificity of 96% (6).  

Lastly, an echo is often done during screening of athletes.  Usually an echo is performed if there is a reasonable probability that a condition which may cause SCD is present.  An echo is often used to rule in or rule out a diagnosis of HCM.  While the differentiation between HCM and an athlete’s heart on echo can be difficult, at screening one needs to determine if the heart is hypertrophied or not and whether additional testing is necessary.  There are many criteria used to diagnose HCM on echo, but three criteria are the generally accepted starting points in making the diagnosis: interventricular septal wall to posterior wall ratio greater than or equal to 1.3, systolic anterior motion (SAM) of the mitral valve and maximal interventricular septal thickness >1.5 cm (7).  These three parameters are easily obtained on echo during a screening session for athletes; they don’t require additional expertise by the echo tech or echo reader. An interventricular septal wall to posterior wall ratio greater than or equal to 1.3 has a sensitivity of 76% and a specificity of 93% (7). Systolic anterior motion of the mitral valve has a sensitivity of 82% and a specificity of 99% (7). Maximal interventricular septal thickness >1.5 cm has a sensitivity of 87% and a specificity of 97% (8). 

Table of Sensitivities and Specificities in Diagnosing HCM
Sensitivity
Specificity
Unexplained syncope
0.35
0.82
Family History of unexplained SCD
0.42
0.79
Family History of HCM
0.44
0.99
Systolic murmur increased w/Valsalva
0.65
0.96
Abnormal EKG - Seattle/International Criteria
0.93
0.96
Septal/Posterior wall ratio => 1.3
0.76
0.93
SAM
0.82
0.99
Interventricular septum > 1.5 cm
0.87
0.97
                                                                                                            

How does the Bayes calculator work? Currently, it is a spreadsheet and the relevant factors (ex, family history HCM) are set to a default of 0.  If a factor is positive, then the 0 is replaced by a 1 and a new posttest probability is displayed.

Take for example an athlete whose only positive finding is a prior history of unexplained syncope, the physical is normal and the EKG is normal. In this case, the baseline probability of HCM goes from 0.2% - 0.5% to 0.4% - 1%. This is still quite a low probability and if one is wondering whether to do an echo, it may acceptable to skip additional testing. 
1/500
1/200
Prevalence of HCM
0.002
0.005
Unexplained syncope
1
1
Family History of unexplained SCD
0
0
Family History of HCM
0
0
Systolic murmur increased w/Valsalva
0
0
Abnormal EKG - Seattle/International Criteria
0
0


Post Test Probability
0.004
0.010


Now if the same athlete has a history of unexplained syncope and an abnormal EKG by Seattle/International criteria, then the probability of HCM goes to 8%- 18%. This is now in an intermediate range and doing an echo would be prudent.


1/500
1/200
Prevalence of HCM
0.002
0.005
Unexplained syncope
1
1
Family History of unexplained SCD
0
0
Family History of HCM
0
0
Systolic murmur increased w/Valsalva
0
0
Abnormal EKG - Seattle/International Criteria
1
1


Post Test Probability
0.083
0.185

If an echo is done and the interventricular septum is greater than 1.5 cm, the posttest probability goes to 72-87%, all but cinching a diagnosis of HCM.

1/500
1/200
Prevalence of HCM
0.002
0.005
Unexplained syncope
1
1
Family History of unexplained SCD
0
0
Family History of HCM
0
0
Systolic murmur increased w/Valsalva
0
0
Abnormal EKG - Seattle/International Criteria
1
1


Post Test Probability
0.083
0.185
Echo
Septal/Posterior wall ratio => 1.3
0
0
SAM
0
0
Interventricular septum > 1.5 cm
1
1
Post Test Probability (+ echo)
0.724
0.868
Post Test Probability ( - echo)
0.016
0.040


The calculator may be helpful in another way. For example, take an athlete who has a family history of HCM and an abnormal EKG. The posttest probability is quite high (67-84%). If, however, the athlete has a negative echo, the posttest probability of a negative echo drops to 27 to 48%. While the probability at this time is lower, this athlete should not be ignored, the probability of HCM is still close to 50%. This scenario represents an athlete who should be followed over time and have repeated echoes.  Even though he doesn’t have HCM at present, he is at risk and may develop it in the future. Young athletes with abnormal EKGs and normal echoes may represent an early phase of the disease and it may be evident years later (9). The calculator may help identify these athletes.

Other causes of SCD in athletes are even less prevalent than HCM. In addition, they do not have the same clues on history and physical examination. The EKG can have subtle abnormalities or it can be normal. The echo can be diagnostic, but oftentimes additional testing (stress testing or cardiac MRI for example) is necessary to diagnose one of these conditions. These tests are not part of a screening evaluation for athletes. Take arrhythmogenic right ventricular dysplasia (ARVD) as an example. The prevalence is 1 in 5000 (ten times higher than HCM) (10). Sensitivities and specificities are known for common EKG abnormalities in ARVD (11).  The pretest probability of ARVD is very low due to the low prevalence, about 0.02%. Even if the EKG is abnormal, the posttest probability is only 1.3%, still quite low. The Bayesian approach may not be helpful.

ARVD
1/5000
Prevalence
0.000200
Positive Family History- ARVD in first degree relative
0
Inverted T waves in V1, V2 and V3 or beyond in patient > 14 yrs old, w/o RBBB
1
Epsilon wave in V1, V2, V3, w/o RBBB
1




Post Test Probability
0.013598

Using the Bayes calculator may be helpful in diagnosing HCM during a routine athlete screening and in identifying athletes who need to be followed closely over time.  The tool uses commonly available variables during a typical athlete screening session and takes only a few minutes to use. However, it has not been prospectively validated. 

Steven Georgeson, MD FACC FACP
Medicor Cardiology
Atlantic Medical Group
Bridgewater NJ USA
References:
1.    Circ 1996;94:850-856
2.    NEJM 1979;300:1350-1358
3.    NEJM 2018;379:655-668
4.    Heart 2004;90:570-575
5.    Am J Card 2014;114:1383-1389
6.    Br J Sports Med 2018;52:667-673
7.    JACC Imaging 2008;1:787-800
8.    JACC 1993;22:498-505
9.    NEJM 2008;358:152-161
10.NEJM 2107;376:61-72
11.Circ 2009;120:477-487


Monday, September 9, 2019

The Magnificent Seven


Today we pay homage to the number seven. The number is seven is special, cropping up in diverse aspects of life and across the years of history. For example, one can sail the seven seas. There were seven wonders in the ancient world. “The Magnificent Seven” was a movie from 1960, one of the best westerns of all time. “The Magnificent Seven” is also the name of a song by the Clash, chronicling the seven hours of the workday in London in the 1980’s. Seven-card stud is a form of poker. Mickey Mantle wore number seven! How is seven significant in the cardiology realm?

In 2010, the American Heart Association (AHA) defined and set national goals for cardiovascular health. The goal, “By 2020 to improve the cardiovascular health of all Americans by 20% while reducing deaths from cardiovascular disease and stroke by 20%”.  The AHA defined seven health factors or behaviors that were associated with cardiovascular health. The AHA called these factors Life’s Simple 7 and they are: physical activity, blood cholesterol, healthy diet, blood pressure, healthy weight, blood glucose(sugar) and smoking.  Each factor was broken into three categories: parameters associated with ideal cardiovascular health, parameters associated with intermediate cardiovascular health and those associated with poor cardiovascular health.  In addition, points are awarded for falling into each category: 0 points for poor health, 1 point for intermediate and 2 points for ideal health.  Here are the categories:

Health Factor or Behavior
Poor Cardiovascular Health
(Warning)


(0 points)
Intermediate Cardiovascular
Health
(Needs Improvement)

(1 point)
Ideal Cardiovascular Health
(Excellent)


(2 points)
1. Physical Activity
Little to none
1-149 min/week moderate exercise or < 74 min/week vigorous exercise
150 or more min/week moderate exercise or 75 or more min/week vigorous exercise
2. Cholesterol
=> 240 mg/dl
200-239 mg/dl
or treated to goal
< 200 mg/dl
3. Healthy Diet
Portions per day:
   5 cups fruit/vege
   4 oz whole wheat
   < 1500 mg of            sodium

Portions per week:
   2-3 servings fish
   < 450 calories       from sugared drinks
0-1 components
2-3 components
4-5 components
4. Blood Pressure
Systolic => 140
Diastolic => 90
Systolic 120-139
Diastolic 80-89
Systolic < 120
Diastolic < 80
5. Healthy Weight
Body mass index (BMI)
BMI => 30
BMI 25-29.9
BMI < 25
6. Blood Glucose
Blood sugar while fasting
=> 126 md/dl
100-125 mg/dl
< 100 mg/dl
7. Smoking
Current smoker
Quit < 12 months ago
Never smoked or quit > 12 months ago


It is now nine years into the AHA campaign. Has there been an impact from Life’s Simple 7?  The overall rates of heart disease and stroke have been declining for a number of years. However, the death rates for heart disease and stroke, which had been declining as well, have leveled off and may even be increasing. Some of this may be explained in the context of Life’s Simple 7. The percentage of adults who meet ideal status for smoking, blood pressure and cholesterol have been increasing. Unfortunately these gains are offset as the percentage of adults whose BMI and glucose in the ideal range have been decreasing (leading to the obesity and diabetes epidemic).  In fact the prevalence of obesity increased from 22% in the 1990’s to 35% in 2012, while diabetes tripled (2.5% in 1990 to 7.2% in 2013). However, following Life’s Simple 7 can improve longevity. One study followed 7600 adults for about 6 years. The study found that participants who met 5 or more of the ideal metrics had an 88% reduction in heart deaths compared to those who met none of the ideal metrics. An analysis from 2014 showed that heart disease improved by only 6% since 2010, far short of the goal of 20% reduction by 2020. Yet following Life’s Simple 7 can help keep the heart strong. Many studies have looked at congestive heart failure and Life’s Simple 7.  A healthy lifestyle score was developed summing the points in each category (the range is from 0 to 14).  An inadequate score was 0 to 8, an intermediate score was 9 or 10 and an ideal score was 11 to 14.  Participants with an intermediate score had a 47% lower chance of congestive heart failure compared to those with an inadequate score. Individuals with an ideal score had a 55% lower chance of heart failure. In addition, those with intermediate and ideal scores had better preservation of the heart’s structure and function (lower risk for a thickened heart and weakening of the heart muscle).

It certainly seems that adhering to the lifestyle promoted by Life’s Simple 7 will go a long way towards reducing heart disease and improving longevity.  So, don’t gamble with your life. Don’t bet on the cards falling your way. Instead, follow Life’s Simple 7 (or the Magnificent Seven) for years of a heart healthy life.