Development of a Risk Calculator to Predict Sudden Cardiac Death in Children With Hypertrophic Cardiomyopathy
Conditions: Hypertrophic Cardiomyopathy, Sudden Cardiac Death
Sponsor: The Hospital for Sick Children

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Development of a Risk Calculator to Predict Sudden Cardiac Death in Children with 
Hypertrophic Cardiomyopathy 
 
INVESTIGATOR: 
 
Seema Mital, MD, Principal Investigator 
Labatt Family Heart Centre  
416-813-7418 
 
 
1. STUDY OVERVIEW 
1.1 GOAL 
A retrospective cohort study to discriminate risk for sudden cardiac death (SCD) in patients with 
Hypertrophic cardiomyopathy (HCM). 
1.2 BACKGROUND  
Hypertrophic cardiomyopathy (HCM) is a commonly inherited heart muscle disease, which can 
present in childhood, adolescence or adulthood.  It accounts for 42% of childhood 
cardiomyopathy and has an incidence of 0.47/100,000 children1. It is a frequent cause of sudden 
cardiac death (SCD) with those aged between 8-16 years at highest risk2,3. 
For adults with HCM, identified risk factors for SCD include non-sustained ventricular 
tachycardia (VT)4,5, left ventricular (LV) hypertrophy (>3cm)6 presence of LV outflow tract 
obstruction7, family history of sudden death2, and hypotensive response of blood pressure on 
exercise testing8.  
However, the risk factors are less clear in the pediatric population. Historically along with the 
risk factors listed above, myocardial bridging was thought to be associated with a poor outcome 
in children with HCM9.Other screening tools have included the use of ECG measurements of R 
and S wave height on ECG along with septal hypertrophy by echocardiogram to predict those at 
risk for SCD10.  HCM is inherited in an autosomal dominant pattern, the most frequently 
encountered HCM-associated mutations occur in MYH7 and MYBPC3 genes. To date no 
correlation has been found between specific genotype and outcome in patients with HCM11. Loar 
et al reported a significant increase in ventricular hypertrophy in genotype positive patients12. As 
LV wall thickness remains one of the SCD risk factors in adults, one could postulate therefore 
that being genotype positive may increase the risk of SCD. Analysis of data from SickKids 
Hospital (Toronto, ON) in pediatric HCM revealed that mutations in MYH7 gene and a higher 
number of pathogenic mutations in one or more genes were associated with a higher incidence of 
major adverse cardiac events13. Emerging imaging tools such as Cardiac MRI to determine the 
presence of Late Gadolinium enhancement may also predict those who have developed 
myocardial fibrosis and are at risk for SCD14,15. 
The European Society of Cardiology (ESC) recently published guidelines on the diagnosis and 
management of HCM in adults16 which led to the development of a clinical risk calculator to 
predict the risk of SCD at 5 years in adults >16 years old17. This model uses age, maximum LV 

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wall thickness (mm), left atrial size (mm), maximum LVOT gradient (mmHg), family history of 
sudden cardiac death, non-sustained VT, unexplained syncope. No such tool exists for children 
where findings such as being genotyped may have additional risk. 
Exercise restriction and β Blocker therapy remains the mainstay of treatment to reduce the risk of 
SCD in children with HCM18. Implantation of an implantable cardioverter defibrillator (ICD) is a 
potentially life-saving therapy for children with HCM, therefore the ability to predict which 
children are at risk from SCD and who would benefit from an ICD may change the current state 
of practice. The ESC currently recommends implantation of an ICD after a life-threatening 
ventricular arrhythmia in children or in those who have two or more major risk factors; however 
these risk factors have not been clearly defined16. 
1.3 OBJECTIVES 
1. To develop and validate a SCD risk calculator that is age-appropriate for children with 
HCM that includes clinical and genetic factors  
 
 
2. RESEARCH PLAN 
2.1 STUDY DESIGN 
This is a retrospective cohort study of pediatric HCM patients using chart and registry review 
methodology.  
2.2 SUBJECT SELECTION 
2.2.1 Inclusion Criteria 
HCM patients ≤18 years of age at first presentation will be included. This includes phenotype 
positive patients, and phenotype negative gene positive patients considered at risk. Phenotype 
positive patients are patients with a clinical diagnosis of HCM based on signs, symptoms, family 
history, EKG and/or echocardiographic features (septal or LV posterior wall thickness z-score 
(PWd) > +2.0 or ratio of hypertrophied region to PWd > 1.3 in the absence of anatomic LVOT 
obstruction) of HCM.  
2.2.2 Exclusion Criteria 
(i) 
Neuromuscular, metabolic, syndromic (other than Noonan Syndrome and related RAS-
opathies) or endocrine (including infants of diabetic mothers) causes of HCM 
 
(ii) 
Other treatable causes of LVH (systemic hypertension, anatomic defect causing LVOT 
obstruction e.g. aortic stenosis, subAS, subaortic membrane) 
 
2.2.3 Subject screening 
Eligible subjects who were seen since 1990 will be identified through review of the following 
data sources:  

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(i) 
Electronic Medical Records (and paper charts where needed) 
(ii) 
Other relevant cardiac databases (ie. echocardiography, heart failure)  
Patients will be screened for eligibility from participating sites. This is a multi-centre study led 
by SickKids Hospital (Toronto), participating institutions include Stollery Children’s Hospital 
(Edmonton), BC Children’s Hospital (Vancouver), Stanford Children’s Health (Palo Alto), 
Children’s Hospital of Philadelphia, Texas Children’s Hospital (Houston), Morgan Stanley 
Children’s Hospital (New York), Children’s Medical Center of Dallas, University of Michigan 
Medical Center (Ann Arbor), Cincinnati Children’s Hospital, Children’s Hospital of Eastern 
Ontario (Ottawa), The Royal Children’s Hospital (Melbourne). REB/IRB approval and service & 
data transfer agreements will be put in place at each participating centre above as well as new 
centres that get added.  
3. DATA COLLECTION 
3.1 Specific data fields for the initial retrospective review 
We will be collecting information on:  
- 
Screening and demographics: Variables include eligibility screening and basic 
demographics such as month/year of birth and gender.  
- 
Medical history, family history, cardiac work-up: This information will be captured at the 
time of first evaluation of HCM (+/-12 months), last reported evaluation and event 
driven. Events include death, transplant, SCD, aborted SCD, mechanical circulatory 
support, cardiac surgery, device implantation (e.g. ICD). Data variables to be collected 
include family history of HCM and sudden cardiac death, history of syncope & history of 
aborted SCD. Cardiac imaging (echo, cMRI) & other cardiac tests (Holter, exercise) 
measurements will be captured along with date of test. Management recommendations 
including exercise restrictions and prescribed medications will also be collected.  
- 
Genetic testing: Results of clinical genetic testing will be captured including test used, 
gene affected and familial inheritance.  
Please refer to appendices for detailed case report forms.  
4. DATA STORAGE AND CONFIDENTIALITY 
All efforts will be made to protect the privacy of individuals in the study. All subjects will be 
given de-identified study IDs. The link between study ID and the patient identifiers will be 
maintained locally in a separate, password protected spreadsheet with access limited to study 
coordinators. De-identified data will be stored using an external REDCap study database that is a 
web-based program that runs on a dedicated server located within SickKids Hospital. The server, 
back-up client software, and back-up tapes are supported through SickKids Center for 
Computational Medicine. The database protects privacy by allowing only site-specific access to 
research staff from any site to only view the information captured at their sites with the exception 
of the central repository located at SickKids which will manage all de-identified data.  

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5. STATISTICAL ANALYSIS 
5-year SCD risk score will be calculated, and discrimination and accuracy assessments will be 
performed. Three risk groups (low, medium, high) will be constructed using the calculated risk 
score. Kaplan-Meier methods with log-rank tests will be used to compare freedom from SCD; 
competing risk models will be applied to analyze aborted SCD events. C-statistic will be used to 
quantify the discriminatory ability of the risk scoring, the discrepancy between predicted and 
observed risk will be also assessed. A revised calculator will be generated from the test cohort 
using additional variables if needed. This calculator will then be tested in a validation cohort to 
determine its ability to predict SCD events. We anticipate screening 3,000 HCM patients across 
all sites of which 70-80% are anticipated to be eligible for inclusion in this analysis. We 
anticipate that this number will provide enough power based on anticipated SCD event rate of 
6% (n=100-150) to develop a new calculator.  
6. CLINICAL RELEVANCE 
Children with HCM remain at high risk for SCD. Current clinical risk factors are largely 
extrapolated from the adult population where a model has been developed to predict those who 
are at risk of SCD at 5 years16,17. The ability to predict those at risk for SCD in the pediatric 
population using a prediction model may guide frequency of patient surveillance in those who 
are at higher risk and may inform indications for ICD insertion for primary prevention. 
Ultimately this may improve long term outcomes in this population. 
7. TIMELINE 
We anticipate 12 months for data collection after REB approval and approval of MTAs, 12 
months for data analysis and write-up of risk calculator.  
8. BUDGET 
Funding for data collection and analysis is supported through the Ted Rogers Centre for Heart 
Research Cardiac Precision Medicine Program at the Hospital for Sick Children. 
 
 
 
 
 
 
 
 
 

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