End‐Recovery QTc: A Useful Metric for Assessing Genetic Variants of Unknown Significance in Long‐QT syndrome
Bibliographic record
Abstract
INTRODUCTION: Genetic variants represent benign single-nucleotide polymorphisms, disease causing mutations or variants of unknown significance (VUS). Resting, exercise, and recovery QTc intervals have been utilized to detect long-QT syndrome (LQTS) mutations. We sought to provide clinical data that may assist in classifying the presented VUS as disease causing/benign and to determine whether resting and/or end-recovery QT parameters can evaluate the significance of VUS. METHODS AND RESULTS: Twenty-six patients with a VUS in genes associated with LQTS (15 females, age 38 ± 16 years) and 26 age and gender matched controls (age 37 ± 20 years) were included. There were 10 VUS (5 KCNQ1, 4 KCNH2, 1 KCNE1) in 12 families. All but 1 VUS was associated with sudden cardiac death (SCD), aborted SCD or Torsade de pointes. A Schwartz score of ≥3.5 was observed in at least 1 family member with each VUS. Resting QTc was marginally longer in VUS patients compared with controls (458 ± 48 vs 437 ± 25, P = 0.052). A prolonged resting QTc (>470 ms males, >480 ms females) identified 6 VUS carriers and 1 control. VUS carriers had a substantially longer end-recovery QTc (502 ± 68 vs 427 ± 17, P < 0.01) with an end-recovery QTc > 445 ms in 20/26 VUS patients compared to 2/26 controls (P < 0.01). The area under the receiver operating characteristic curve for resting QTc was 0.68 (95% CI, 0.53-0.83, P = 0.03) compared to the end-recovery QTc of 0.88 (95% CI, 0.76-0.99, P < 0.0001). CONCLUSION: Variants in the current study appear to be disease causing. The end-recovery QTc is a useful metric when interpreting LQT VUS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".