To what degree is amelioration of angina following coronary revascularization associated with improvement in myocardial perfusion?
Bibliographic record
Abstract
OBJECTIVE: To examine the association between changes in chest pain and changes in perfusion following revascularization as assessed by clinical evaluation and myocardial perfusion imaging (MPI) in patients with stable angina. DESIGN: In a prospective series of 380 patients (58.8 +/- 8.8 years) referred to angiography because of known or suspected stable angina, changes in chest discomfort and changes in perfusion after 2 years were assessed in 144 patients, who underwent revascularization, and 236, who did not. The decision to treat invasively was made without knowledge of the result of MPI. RESULTS: In revascularized patients, the presence of typical/atypical angina was reduced from 93% to 36% and the improvement was associated with improvement in perfusion. A small improvement in perfusion induced a high frequency of change from angina to no pain, whereas a further reduction caused little extra change. In non-revascularized patients the change in chest discomfort was not related to changes in perfusion, which were rarely present. CONCLUSION: Alleviation of chest discomfort 2 years after revascularization is associated with improvements in perfusion. This association appeared to be an all-or-nothing phenomenon. Non-revascularized patients also exhibited improvements in chest discomfort despite insignificant changes in perfusion.
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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 | 0.009 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".