Angiogenic Precursor Cell Treatment of Critical Limb Ischemia Decreases Ulcer Size, Amputation and Death Rate: Re-Examination of phase II ACP NO-CLI Trial Data
Bibliographic record
Abstract
Introduction: Critical limb ischemia has a prevalence in the US of 1.33%, with mortality 15-20% and major amputation 10-40% per year. Stem cell treatment has emerged as a treatment option for the 45% of patients for whom revascularization procedures are not possible. Objective: This study re-examines the data of the Phase II clinical treatment of no option Critical limb ischemia with Hemostemix’ angiogenic cell precursors, focusing upon ulcer wound healing, amputation and death rate of this cohort. Methods: Primary endpoints were changes in ulcer size and major amputation or death within one year of treatment. The secondary endpoint was change in pain level. Results: From 2015 to 2021, 67 patients with no option Critical limb ischemia were allocated to treatment with ACP-01 (46/67) or placebo (21/67). From this data, only patients who presented with wound ulcers before administration of ACP-01 were reviewed (21 treatment, 8 placebo). Ulcer size in the treated group decreased from a mean of 1.46 cm2 to 0.48 mm2 (p = 0.01) by 3 months. There was no significant decrease in the size of the ulcers of the placebo group (p < 0.54). At one year there were no complications related to treatment. The treatment group had one amputation (4.8%) and one death (4.8%); the placebo group had 2 amputations (25%) and 1 death (12.5%). Change in pain was not significant in either group at 3 months, but at 1 year was improved in the placebo group (p = 0.01). Conclusion: The administration of ACP-01 within a program of careful patient follow up is safe and associated with reduced ulcer size and decreased rate of amputation and death. Consideration should be given to re-administration of stem cell treatments every 3-6 months to optimize improvement of Critical limb ischemia. Further studies, more appropriately powered, are warranted.
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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".