P.055 Novel pipeline for triage of variant of uncertain significance reclassification in epilepsy genomics
Bibliographic record
Abstract
Background: Increased availability of genetic testing has led to increased burden of follow up of variants of uncertain significance (VUS). As of January 2025, 327 VUS were identified patients at BC Children’s Hospital. We propose a pipeline to triage and follow up of patients with identified VUS to clarify diagnosis through paternal testing. Methods: Of the 327 patients with VUS, 13 patients with high clinical suspicion for a genetic disorder were identified by their neurologist. Initial chart review for each patient was performed. Clinical phenotype data and the patient’s variant were inputted into the online tool Franklin. This program generates a variant interpretation based on 17/ 28 criteria in ACMG scoring. For each patient the variant would be assumed to be de novo in order to determine if parental testing could change variant classification. Results: 5/13 of the patients had suggested reclassification of variants. 6/13 of the patients would have reclassification of variant to likely pathogenic/pathogenic if the variant was found to be de novo, suggesting a need for paternal testing. Conclusions: This highlights a novel clinical pipeline to improve expediency and triaging of VUS reclassification for paternal testing in epilepsy genomics.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.020 | 0.006 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".