Familial Hypercholesterolemia
Conditions
Brief summary
The purpose of this study is to validate the use of the FH Foundation FIND FH® Algorithm as a clinical decision support tool. FIND FH (Flag/Identify/Network/Engage) is a national initiative that utilizes machine learning and data mining techniques to identify individuals whose profiles are consistent with FH patients. The algorithm will be tested in adults with at least one cardiovascular comorbidity. Study subjects will be asked to provide either a saliva, buccal or venous blood sample for DNA and biomarker analysis
Interventions
OTHERGenetic testing
Targeted next-generation sequencing for familial hypercholesterolemia causative mutations
Sponsors
The Familial Hypercholesterolemia Foundation
Lancaster General Hospital
University of Pennsylvania
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
Yes
Inclusion criteria
* Age 18 years or older * At least one cardiovascular co-morbidity or receiving treatment for a cardiovascular comorbidity * Algorithm score 0-1 * Most recent encounter with a provider within five years of query date
Exclusion criteria
* Any medical or psychological conditions that, in the opinion of the investigator, would compromise the subject's safety or successful participation in the study, or confound study data
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Likelihood of having FH-causing mutation | 12 months | Proportion of subjects with causative mutation in higher algorithm score groups |
Countries
United States
Outcome results
None listed