Reduced rate of diagnostic coronary imaging following Rubidium PET vs Thallium SPECT, as alternatives to Technetium SPECT myocardial perfusion imaging
Bibliographic record
Abstract
1735 Objectives Rubidium-82 (RB) cardiac PET imaging is believed to have greater accuracy compared to Thallium-201 (TL) SPECT. This study was performed to evaluate downstream diagnostic and revascularization procedure utilization, following Rb-82 PET compared to TL-SPECT as alternative to Tc-99m SPECT myocardial perfusion imaging (MPI) during a period of short supply. Methods Matched cohorts consisting of 902 pairs of patients receiving either RB-PET or TL-SPECT scans during the Tc-99m isotope crisis (July 2009 to August 2010) were individually matched by Morise Risk Score. These patients were cross-referenced with Institute databases of CCTA, CABG, CATH (diagnostic catheterization) and PCI (therapeutic catheterization) patients to assess the rates of downstream procedures following nuclear imaging. Downstream diagnostic testing was defined as any CCTA or CATH occurring within 180 days following the PET or SPECT scan. Downstream revascularization was defined as any CABG or PCI occurring within the same interval. Proportions of patients undergoing diagnostic and revascularization events were compared between RB-PET and TL-SPECT using the z-statistic. Results A significantly smaller proportion of RB-PET patients underwent downstream diagnostic testing (5.1% PET vs 7.1% SPECT, p = 0.04). Revascularization rates did not differ significantly between the two scan groups (9.8% PET vs 8.4% SPECT, p = 0.16). Conclusions Rubidium PET MPI may reduce downstream diagnostic testing compared to Thallium SPECT without significantly altering subsequent revascularization rates, suggesting that RB-PET may be a preferred alternative to Thallium-201 SPECT when Tc-99m isotope supply is not available.
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 | 0.001 | 0.005 |
| 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 | 0.001 | 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".