Prevalence and Associated Clinical Characteristics of Exercise-Induced ST-Segment Elevation in Lead aVR
Bibliographic record
Abstract
BACKGROUND: Exercise-induced ST-segment elevation (STE) in lead aVR may be an important indicator of prognostically important coronary artery disease (CAD). However, the prevalence and associated clinical features of exercise-induced STE in lead aVR among consecutive patients referred for exercise stress electrocardiography (ExECG) is unknown. METHODS: All consecutive patients receiving a Bruce protocol ExECG for the diagnosis of CAD at a tertiary care academic center were included over a two-year period. Clinical characteristics, including results of coronary angiography, were compared between patients with and without exercise-induced STE in lead aVR. RESULTS: Among 2227 patients undergoing ExECG, exercise-induced STE ≥1.0mm in lead aVR occurred in 3.4% of patients. Patients with STE in lead aVR had significantly lower Duke Treadmill Scores (DTS) (-0.5 vs. 7.0, p<0.01) and a higher frequency of positive test results (60.2% vs. 7.3%, p<0.01). Furthermore, patients with STE in lead aVR were more likely to undergo subsequent cardiac catheterization than those without STE in lead aVR (p<0.01, odds ratio = 4.2). CONCLUSIONS: Among patients referred for ExECG for suspected CAD, exercise-induced STE in lead aVR was associated with a higher risk DTS, an increased likelihood of a positive ExECG, and referral for subsequent coronary angiography. These results suggest that exercise-induced STE in lead aVR may represent a useful ECG feature among patients undergoing ExECG in the risk stratification of patients.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".