A Machine Learning Model to Aid Detection of Familial Hypercholesterolemia.

The purpose of this study was to derive an algorithm to identify people with suspected monogenic FH for subsequent confirmatory genomic testing and cascade screening. Detecting individuals with FH could be improved by considering additional predictors, with the top 5 most important variables included triglyceride, LDL-C, apolipoprotein A1 concentrations, self-reported statin use, and an LDL-C PolyGenic Score . This would reduce the sequencing burden in a 2-stage population screening strategy for FH

• JACC Adv. 2023 May 24;2(4):100333.
• PMID: 3893823
• doi: 10.1016/j.jacadv.2023.100333
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