ArticlePediatric cardiology2018
Hypertrophic Cardiomyopathy Genotype Prediction Models in a Pediatric Population.
Article in Pediatric cardiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed, 12 citations in OpenAlex.
- Prediction of Genotype Positivity in Patients With Hypertrophic Cardiomyopathy Using Machine Learning.Circulation. Genomic and precision medicine · 2021Trial
- Genotype-Phenotype Associations in Pediatric Hypertrophic Cardiomyopathy: A Study From the Pediatric Cardiomyopathy Registry.JACC. Heart failure · 2026Article
- Integrating ECG Into the Mayo Score Enhances Genotype Prediction in Hypertrophic Cardiomyopathy.Journal of the American Heart Association · 2026Article
- Genetic testing and counseling for hypertrophic cardiomyopathy: An evidence-based practice resource of the National Society of Genetic Counselors.Journal of genetic counseling · 2025Review
- Integration of multi-omics and machine learning strategies identifies immune related candidate biomarkers in inflammation-associated hypertrophic cardiomyopathy.Frontiers in immunology · 2025Article
- Childhood Hypertrophic Cardiomyopathy: A Disease of the Cardiac Sarcomere.Frontiers in pediatrics · 2021Review
- Deep Learning Analysis of Echocardiographic Images to Predict Positive Genotype in Patients With Hypertrophic Cardiomyopathy.Frontiers in cardiovascular medicine · 2021Article
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The Toronto Hypertrophic Cardiomyopathy (HCM) Genotype Score and Mayo HCM Genotype Predictor are risk assessment models developed to estimate a patient's likelihood of testing positive for a pathogenic variant causative of HCM. These models were developed from adult populations with HCM based on factors that have been associated with a positive genotype and have not been validated in external populations. The purpose of this study was to evaluate the overall predictive abilities of these models in a clinical pediatric HCM setting. A retrospective medical record review of 77 pediatric patients with gene panel testing for HCM between September 2005 and June 2015 was performed. Clinical and echocardiographic variables used in the developed models were collected and used to calculate scores for each patient. To evaluate model performance, the ability to discriminate between a carrier and non-carrier was assessed by area under the ROC curve (AUC) and overall calibration was evaluated by the Hosmer-Lemeshow goodness-of-fit statistic. Discrimination assessed by AUC was 0.72 (P < 0.001) for the Toronto model and 0.67 (P = 0.004) for the Mayo model. The Toronto model and the Mayo model showed P values of 0.36 and 0.82, respectively, for model calibration. Our findings suggest that these models are useful in predicting a positive genetic test result in a pediatric HCM setting. They may be used to aid healthcare providers in communicating risk and enhance patient decision-making regarding pursuit of genetic testing.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.