Autologous CD34+ cell therapy improves exercise capacity, angina frequency and reduces mortality in no-option refractory angina: a patient-level pooled analysis of randomized double-blinded trials
Bibliographic record
Abstract
Aims: Autologous CD34+ (auto-CD34+) cells represent an attractive option for the treatment of refractory angina. Three double-blinded randomized trials (n = 304) compared intramyocardial (IM) auto-CD34+ cells with IM placebo injections to affect total exercise time (TET), angina frequency (AF), and major adverse cardiac events (MACE). Patient-level data were pooled from the Phase I, Phase II ACT-34, ACT-34 extension, and Phase III RENEW trials to determine the efficacy and safety of auto-CD34+ cells. Methods and results: Treatment effects for TET were analysed using an analysis of covariance mixed-effects model and for AF using Poisson regression in a log linear model with repeated measures. The Kaplan-Meier rate estimates for MACE were compared using the log-rank test. Autologous CD34+ cell therapy improved TET by 46.6 s [3 months, 95% confidence interval (CI) 13.0 s-80.3 s; P = 0.007], 49.5 s (6 months, 95% CI 9.3-89.7; P = 0.016), and 44.7 s (12 months, 95% CI - 2.7 s-92.1 s; P = 0.065). The relative frequency of angina was 0.78 (95% CI 0.63-0.98; P = 0.032), 0.66 (0.48-0.91; P = 0.012), and 0.58 (0.38-0.88; P = 0.011) at 3-, 6- and 12-months in auto-CD34+ compared with placebo patients. Results remained concordant when analysed by treatment received and when confined to the Phase III dose of 1 × 105 cells/kg. Autologous CD34 + cell therapy significantly decreased mortality (12.1% vs. 2.5%; P = 0.0025) and numerically reduced MACE (38.9% vs. 30.0; P = 0.14) at 24 months. Conclusion: Treatment with auto-CD34+ cells resulted in clinically meaningful durable improvements in TET and AF at 3-, 6- and 12-months, as well as a reduction in 24-month mortality in this patient-level meta-analysis.
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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 | 0.020 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.017 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".