Angiogenic Gene Therapy (AGENT) Trial in Patients With Stable Angina Pectoris
Bibliographic record
Abstract
BACKGROUND: The angiogenic response to myocardial ischemia can be augmented in animal models by gene transfer with the use of a replication defective adenovirus (Ad) containing a human fibroblast growth factor (FGF) gene. METHODS AND RESULTS: The objectives of the Angiogenic GENe Therapy (AGENT) trial were to evaluate the safety and anti-ischemic effects of 5 ascending doses of Ad5-FGF4 in patients with angina and to select potentially safe and effective doses for subsequent study. Seventy-nine patients with chronic stable angina Canadian Cardiovascular Society class 2 or 3 underwent double-blind randomization (1:3) to placebo (n=19) or Ad5-FGF4 (n=60). Safety evaluations were performed at each visit and exercise treadmill testing (ETT) at baseline and at 4 and 12 weeks. Single intracoronary administration of Ad5-FGF4 seemed to be safe and well tolerated with no immediate adverse events. Fever of <1-day duration occurred in 3 patients in the highest-dose group. Transient, asymptomatic elevations in liver enzymes occurred in 2 patients in lower-dose groups. Serious adverse events during follow-up (mean, 311 days) were not different between placebo and Ad5-FGF4. Overall, patients who received Ad5-FGF4 tended to have greater improvements in exercise time at 4 weeks (1.3 versus 0.7 minutes, P=NS, n=79). A protocol-specified, subgroup analysis showed the greatest improvement in patients with baseline ETT < or =10 minutes (1.6 versus 0.6 minutes, P=0.01, n=50). CONCLUSIONS: Results show evidence of favorable anti-ischemic effects with Ad5-FGF4 compared with placebo, and it appears to be safe. Angiogenic gene transfer with Ad5-FGF4 shows promise as a new therapeutic approach to the treatment of angina pectoris.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".