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Record W4386053111 · doi:10.9778/cmajo.20220108

Genetic testing for familial hypercholesterolemia in Quebec, Canada: a single-centre retrospective cohort study

2023· article· en· W4386053111 on OpenAlexaffvenueabout
Amanda Guérin, Iulia Iatan, Isabelle L. Ruel, Linda Fri Ngufor, Jacques Genest

Bibliographic record

VenueCMAJ Open · 2023
Typearticle
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsMcGill University Health CentreUniversity of British Columbia
Fundersnot available
KeywordsFamilial hypercholesterolemiaMedicineLDL receptorPCSK9Apolipoprotein BCohortGenetic testingRetrospective cohort studyInternal medicinePediatricsCholesterolLipoprotein

Abstract

fetched live from OpenAlex

Background: Familial hypercholesterolemia (FH) is associated with premature atherosclerotic cardiovascular disease caused by elevated low-density lipoprotein cholesterol (LDL-C) levels. We determined the impact of a full next-generation sequencing (NGS) genetic panel on reclassification of patients with a clinical diagnosis of FH in Quebec compared to the partial genetic panel currently offered by the Quebec Ministère de la Santé et des Services sociaux (Ministry of Health and Social Services) (MSSS), which includes 11 variants that are common in French Canadians. Methods: We conducted a retrospective cohort study in a subgroup of patients in the Canadian FH Registry seen at the McGill University Health Centre Preventive Cardiology/Lipid Clinic, Montréal, between September 2017 and September 2021 who were clinically diagnosed with severe hypercholesterolemia, probable FH or definite FH according to the Canadian definition of FH. Next-generation sequencing of the LDLR, APOB and PCSK9 genes, and multiplex ligation-dependent probe amplification of the LDLR gene to detect genetic variants, were performed. Results: Among 335 consecutive patients with heterozygous FH (184 men [54.9%] and 151 women [45.1%]), the baseline LDL-C level was 6.96 (standard deviation 1.79) mmol/L. Patients identified through cascade screening were 11 years younger on average than index patients, and smaller proportions presented to the clinic with cardiovascular risk factors. A pathogenic FH variant was identified in 169 (73.8%) of the 229 patients who underwent genetic testing; the majority had variants in the LDLR (146 [86.4%]) or APOB (24 [14.2%]) gene. The genetic panel offered by the MSSS accounted for only 48% of the variants identified with the full NGS panel. Of the 229 patients, 90 (39.3%, 95% confidence interval 32.9%–46.0%) were reclassified from a clinical diagnosis of probable FH to definite FH after genetic screening with a full FH panel. Interpretation: Genetic testing in patients suspected of having FH provided diagnostic certainty and permitted many patients with a clinical diagnosis of probable FH to be reclassified as having definite FH. Genetic screening allows for increased identification of patients with FH and may therefore help reduce the burden of cardiovascular disease and mortality rates among Canadians with FH. Trial registration:ClinicalTrials.gov, no. NCT02009345

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.038
GPT teacher head0.285
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2023
Admission routes3
Has abstractyes

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