Gene therapy of coronary artery disease with phvegf165--early outcome.
Bibliographic record
Abstract
BACKGROUND: Gene therapy is a new, experimental method of treatment in patients with coronary artery disease (CAD). AIM: To determine the safety and efficacy of gene encoding vascular endothelial growth factor (VEGF165) administered directly into the myocardium as the single treatment or combined with coronary artery by-pass grafting (CABG). METHODS: VEGF gene transfer was performed in 22 patients (20 male, 2 female, ages from 48 to 73 years old). A 200 micro g of the plasmid encoding VEGF165 was injected into the ischaemic myocardium which could not be surgically revascularised in patients undergoing CABG (n=14), and 400 micro g - in patients without CABG (n=8). The value of ejection fraction (EF), myocardial perfusion, angiogram, ventriculography, and nitroglycerine consumption as well as quality of life were evaluated pre- and postoperatively. RESULTS: The majority of patients had no complications and no fatal outcome was observed. Two patients developed acute myocardial infarction. Left ventricular function values improved and the majority of patients were free from angina 6 months after surgery. Patients reported improved quality of life and a reduction in nitroglycerine usage. A reduction in the ischaemic defects detected by SPECT was also observed. In some patients angiography revealed improved collateral filling. CONCLUSIONS: Direct myocardial administration of genes encoding VEGF165 can be an effective method of treatment in patients with chronic and advanced CAD either as a supplementary treatment or as a single therapy.
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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) | 0.000 | 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) | 0.001 | 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".