The prognostic value of single photon emission computed tomography (SPECT) myocardial perfusion imaging is independent of left ventricular size
Bibliographic record
Abstract
Many variables have been shown to impact accuracy and prognostic power of myocardial perfusion imaging (MPI); however, effects of left ventricular size have not been extensively studied. In particular, perfusion defects in smaller hearts could be overlooked due to partial volume averaging, potentially reducing the prognostic power of MPI. We determined stress total perfusion deficit (TPD) and rest end diastolic volume (REDV) from single photon emission computed tomography (SPECT) MPI in consecutive patients without pathologically dilated left ventricles. Area under the curve (AUC) and Cox regression analysis were used to assess prediction of subsequent major adverse cardiac events [MACE-death, hospitalized acute myocardial infarction (AMI), hospitalized unstable angina, late revascularization]. Analyses were stratified by sex and REDV tertile. The analytic population included 2,503 patients (965 men and 1,538 women). Outcomes were assessed over an average of 6.4±2.3 years. MACE was observed in 254 (26.3%) of 965 men and 261 (17.0%) of 1,538 women. Stress TPD showed significant AUCs for stratifying MACE risk regardless of sex and REDV tertile (all P<0.05). In Cox regression analysis, increasing stress TPD (but not REDV) was associated with MACE in both men and women. There was no significant TPD*REDV interaction. In conclusion, we found the prognostic power of SPECT MPI to be independent of left ventricular size.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".