Abstract 1775: Prognostic Value of Exercise and Dobutamine Positron Emission Tomography
Bibliographic record
Abstract
Introduction Positron emission tomography (PET) is commonly performed using vasodilator stress, but exercise and dobutamine stress is available to patients with contraindications to vasodilators. Vasodilator PET appears to have prognostic value, however the prognostic value of PET using stressors which induce myocardial ischemia have not been well evaluated. Hypothesis To evaluate the prognostic value of myocardial demand ischemia induced by treadmill exercise and dobutamine PET. Methods 124 patients (mean age = 61.29 ± 10.73 years; 87 men) had treadmill exercise or dobutamine Rb-82 or N-13 ammonia PET. Images were assessed qualitatively using a 17-segment model and a semi-quantitative visual score (five-point scale) to calculate the summed stress score (SSS). Images were categorized as normal (SSS<4), abnormal (SSS ≥ 4) or inconclusive (SSS< 4 and suboptimal treadmill exercise or dobutamine stress). Follow-up was performed to ascertain outcomes (cardiac death, nonfatal MI and/or late revascularization. Results Of the 124 patients, 46 (37.1%) had a normal PET, 15 (12.1%) had an inconclusive study, and 63 (50.1%) had an abnormal PET (mean follow up 2.8 ± 1.4 years). There were no deaths or non-fatal MI but 1 late revascularization (annual event rate = 1.7%) in the group with a normal PET. Abnormal PET MPI group had 15 cardiac events (1 cardiac death, 4 nonfatal MI, and 10 late revascularization) with an annual event rate of 13.0% (p = 0.002). Conclusions Though small, this study suggests that myocardial PET perfusion defects resulting from demand ischemia induced by treadmill exercise and dobutamine stress may have prognostic value.
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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 | 0.000 | 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) | 0.004 | 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".