Localization of maximal ST segment displacement in various ischemic settings by orthogonal ECG: Implications for lead selection and the mechanism of ST shift.
Bibliographic record
Abstract
BACKGROUND: ST segment deviation conveys crucial information concerning diagnosis, therapy and prognosis during acute coronary syndromes, but the understanding of the genesis of different ST shift polarities and the rationale for optimal lead placement during ischemic monitoring are incomplete. PATIENTS AND METHODS: Ninety-nine continuous recordings were made with orthogonal X, Y and Z leads in 35 patients during ST elevation myocardial infarction (MI), in 30 patients during single vessel, elective coronary angioplasty (PTCA), and in 34 patients with unstable angina or acute non-Q wave MI. Each lead was sampled at 500 Hz, and dominant QRS-T complexes were averaged every 47 s. In PTCA, 10 s averages were analyzed. Trend plots of ST + 60 ms for each lead and ST vector angles phi and theta were constructed and edited. ST shift polarity (depression or elevation) and vector orientation (phi and theta) were noted for the greatest ST shift 50 microV or greater on any lead for each patient. Coronary angiographical data were consulted when available. RESULTS: By constructing polar plots of phi and theta, it was evident that ST depression vectors were confined to a small, lateral cardiac region despite a variety of coronary lesions, while ST elevation vectors were oriented according to the territory of the occluded artery (difference of direction means, P<0.002). CONCLUSION: ST depression in acute coronary syndromes is maximal over the left thorax regardless of coronary lesion location, indicating that the mechanism of ST depression is not fully understood. In ambulatory monitoring where ST depression is expected, a lateral lead may suffice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 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".