High Doses of Vascular Endothelial Growth Factor 165 Safely, but Transiently, Improve Myocardial Perfusion in No-Option Ischemic Disease
Bibliographic record
Abstract
UNLABELLED: Gene therapy can induce angiogenesis in ischemic tissues. The aim of this study was to assess safety, feasibility, and results, both clinical and on myocardial perfusion, of gene therapy in refractory angina. This was a phase I/II, prospective, temporal-controlled series, clinical trial. Thirteen patients were maintained for minimum 6 months under optimized clinical management, and then received intramyocardial injections of 2000 μg plasmid vascular endothelial growth factor 165 and were followed by single-photon emission computed tomography (SPECT), treadmill tests, Minnesota quality of life questionnaire (QOL), and New York Heart Association (NYHA) functional plus Canadian Cardiovascular Society (CCS) angina classifications. There were no deaths, early or late. During the optimized clinical treatment, we observed worsening of rest ischemia scores on SPECT (p<0.05). After treatment, there was a transitory increase in myocardial perfusion at the third-month SPECT under stress (pre-operative [pre-op] 18.38 ± 7.51 vs. 3 months 15.31 ± 7.30; p<0.01) and at the sixth month under rest (pre-op 13.23 ± 7.98 vs. 6 months: 16.92 ± 7.27; p<0.01). One year after, there were improvements in treadmill test steps (pre-op 2.46 ± 2.07 vs.12 months 4.15 ± 2.23; p<0.01) and oxygen consumption (pre-op 7.66 ± 4.47 vs.12 months 10.89 ± 4.65; p<0.05), QOL (pre-op 48.23 ± 18.35 vs.12 months 28.31 ± 18.14; p<0.01) scores, and CCS (pre-op 3 [3-3.5] vs.12 months 2 [1-2.5]; p<0.01) and NYHA (pre-op 3 [3-3] vs. 2 [2-2] vs. 12 months 2 [1-2]; p<0.01) classes. Gene therapy demonstrated to be feasible and safe in this advanced ischemic cardiomyopathy patient sample. There were improvements in clinical evaluation parameters, and a transitory increase in myocardial perfusion detectable by SPECT scintigraphy. CLINICAL TRIAL REGISTRATION: NCT00744315 http://clinicaltrials.gov/
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".