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Record W4309116026 · doi:10.1159/000527079

What Went Wrong with VEGF-A in Peripheral Arterial Disease? A Systematic Review and Biological Insights on Future Therapeutics

2022· review· en· W4309116026 on OpenAlexaboutno aff
Stavroula Kastora, Jonathan Eley, Martin Gannon, Ross Melvin, Euan N. Munro, Sotirios A. Makris

Bibliographic record

VenueJournal of Vascular Research · 2022
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAngiogenesis and VEGF in Cancer
Canadian institutionsnot available
FundersNational Institute for Health and Care Research
KeywordsMedicineAnimal studiesContext (archaeology)Systematic reviewVascular endothelial growth factorInternal medicineAngiogenesisPathologyVEGF receptorsMEDLINEBiology

Abstract

fetched live from OpenAlex

BACKGROUND: 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. METHODS: 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. FINDINGS: 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. INTERPRETATION: 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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.049
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.049
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0100.007
Bibliometrics0.0080.007
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.103
GPT teacher head0.396
Teacher spread0.293 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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".

Quick stats

Citations16
Published2022
Admission routes1
Has abstractyes

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