A study to assess changes in myocardial perfusion after treatment with spinal cord stimulation and percutaneous myocardial laser revascularisation; data from a randomised trial
Bibliographic record
Abstract
BACKGROUND: Spinal cord stimulation (SCS) and percutaneous myocardial laser revascularisation (PMR) are treatment modalities used to treat refractory angina pectoris, with the major aim of such treatment being the relief of disabling symptoms. This study compared the change in myocardial perfusion following SCS and PMR treatment. METHODS: Subjects with Canadian Cardiovascular Society class 3/4 angina and reversible perfusion defects as assessed by single-photon emission computed tomographic myocardial perfusion scintigraphy were randomised to SCS (34) or PMR (34). Twenty-eight subjects in each group underwent repeat myocardial perfusion imaging 12 months post intervention. Visual scoring of perfusion images was performed using a 20-segment model and a scale of 0 to 4. RESULTS: The mean (standard deviation) baseline summed rest score (SRS) and stress scores (SSS) were 4.6 (5.7) and 13.6 (9.0) in the PMR group and 6.1 (7.4) and 16.8 (11.6) in the SCS group. At 12 months, SRS was 5.5 (6.0) and SSS 15.3 (11.3) in the PMR group and 6.9 (8.2) and 15.1 (10.9) in the SCS group. There was no significant difference between the two treatment groups adjusted for baseline (p = 1.0 for SRS, p = 0.29 for SSS). CONCLUSION: There was no significant difference in myocardial perfusion one year post treatment with SCS or PMR.
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".