Utility of Treadmill Testing in Identification and Genotype Prediction in Long-QT Syndrome
Bibliographic record
Abstract
BACKGROUND: The clinical diagnosis of long-QT syndrome (LQTS) remains challenging when ECG abnormalities are borderline or intermittent. Despite issues with access, cost, and heterogeneity of LQTS mutations, genetic testing remains the diagnostic gold standard for diagnosis of LQTS. We sought to develop a provocative testing strategy to unmask the LQTS phenotype and relate this to the results of genetic testing. METHODS AND RESULTS: From 1995 to 2008, 159 consecutive patients with suspected LQTS underwent provocative testing that consisted of a modified Bruce protocol treadmill exercise test, with ECGs recorded supine at rest, immediately on standing, and at 1-minute intervals during exercise, at peak exercise, and at 1-minute intervals during the recovery phase. Similar testing was carried out on a stationary bike in a gradual and burst exercise fashion. LQTS was confirmed with genotyping in all 95 affected LQTS patients and excluded with negative family screening in 64 control subjects. Patients were studied before and after initiation of beta-blockers. Of 159 patients, 50 had an LQT1 mutation and 45 had an LQT2 mutation. In the LQTS group, 44.3% of patients had a normal-to-borderline resting QTc interval. LQTS patients exhibited a greater prolongation in QTc with postural change than unaffected patients (LQT1: 40 ms [IQR, 42]; LQT2: 35 ms [IQR, 46]; and LQTS-negative: 21 ms [IQR, 37]; P=0.029). During exercise, LQT1 patients had marked QTc prolongation compared with LQT2 and LQTS-negative patients (LQT1: 65 ms [60], LQT2: 3 ms [46], LQTS negative: 5 ms [41]; P<0.0001). QT hysteresis was more pronounced in patients with LQT2 mutations compared with LQT1 and LQT-negative patients (LQT2: 40 ms [10], LQT1: 15 ms [40]; LQTS-negative: 20 ms [20]; P<0.001). beta-Blockade normalized the QTc changes seen with standing and QT hysteresis. CONCLUSIONS: The presence and genotype of LQTS can be predicted by a combination of postural and exercise changes in the QT/RR relationship. beta-Blockade normalized these changes. Routine exercise testing is useful in predicting and directing genetic testing in LQTS.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".