Right Precordial Leads and Lead aVR at Exercise Electrocardiography: Does It Change Test Results?
Bibliographic record
Abstract
BACKGROUND: A recent study on exercise testing (ET) suggested that ST-segment changes in the right precordial leads (RPL) may increase its sensitivity substantially. However, this study looked at a highly selected population of patients who all underwent thallium-201 scintigraphy and coronary angiography. The present study evaluated the clinical utility of ST-segment changes in the RPL and lead aVR in an unselected population of patients undergoing ET. METHODS: A total of 906 consecutive patients who received ET were included in the study. ET was done using the Bruce Protocol with a 12-lead electrocardiogram (ECG) substituting V(4)R and V(6)R for V(1) and V(6). Leads V(1) and V(6) were selected for omission as these two leads hardly ever manifest changes in isolation. Substituting two leads would obviate the need for a more complex recording system, thus improving clinical utility. RESULTS: On the basis of horizontal/downsloping ST-segment depression (STD) of 1.0 mm or more (the usually accepted criterion for a positive ET), 159 (17.5%) patients had a positive ET. In those patients with a negative ET (545 patients), 4 patients (0.7%) manifested STD and 5 patients (0.9%) manifested ST-segment elevation (STE) in leads V(4)R and/or V(6)R, respectively. Of note, 44.7% of the positive ET group had STE in lead aVR. CONCLUSION: The use of ST-segment changes in RPL during exercise stress testing does not appreciably change the test results of a standard ET. If one was to consider an additional marker, STE in aVR may be more useful, as it shows a stronger correlation with positive tests and does not require the recording of additional leads.
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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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".