Supplementary Material for: What Went Wrong with VEGF-A in Peripheral Arterial Disease? A Systematic Review and Biological Insights on Future Therapeutics
Bibliographic record
Abstract
<b><i>Background:</i></b> Of the 200 million patients worldwide affected by peripheral arterial disease (PAD), 4% will inevitably require major limb amputation. Previous systematic reviews presented a conflicting body of evidence in terms of vascular endothelial growth factor (VEGF) family member effects upon PAD natural progression. Despite that, modulation of intrinsic angiogenesis mechanisms targeting the VEGF family members still confers an attractive therapeutic target. The aim of the present study was to evaluate current evidence of VEGF modulation in the context of PAD. <b><i>Methods:</i></b> This is a systematic literature review conducted according to the PRISMA guidelines and registered under PROSPERO database [CRD42021285988]. Independent literature search was performed up to April 1, 2022, on six databases. A total of 22 eligible studies were identified [N: 3, interventional patient studies; N: 19, animal studies]. Animal studies were appraised by the SYRCLE risk of bias tool, while human participant studies were assessed by the Newcastle Ottawa scale. Overall, quality of evidence was deemed fair for both animal and human studies. Main study outcomes were percentage change of injured vessel lumen stenosis and neointimal area formation upon VEGF modulation (inhibition or activation) in comparison with control group. <b><i>Findings:</i></b> Nineteen animal models and three human participant studies were included in the systematic review and assessed separately. Positive modulation of VEGF-A in animal models resulted in a median decrease of 65.58% [95% CI 45.2; 71.87] in lumen stenosis [14 studies]. Furthermore, positive modulation of VEGF-A was found to reduce neointimal area proliferation by a median decrease of 63.41% [95% CI 41.6; 79.59] [14 studies]. Median end of study duration was 28 days [range: 14–84 days]. Data were insufficient to assess these outcomes with respect to VEGF-B or VEGF-C modulation. The limited number of available human studies presented inadequate outcome assessment despite their overall fair NOS grading. <b><i>Interpretation:</i></b> VEGF-A-positive modulation decreases lumen stenosis and neointimal hyperplasia in PAD simulation animal models. Previously identified variability among outcomes was found to strongly stem from the variability of experimental designs. Clinical applicability and safety profile of VEGF-A in the context of PAD remain to be defined by a robust and uniformly designed body of further animal model-based experiments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 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) | 0.114 | 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 teacher head, 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".