Genetic polymorphisms of vein wall remodeling in chronic venous disease: a narrative and systematic review
Bibliographic record
Abstract
Chronic venous disease encompasses a spectrum of disorders caused by an abnormal venous system. They include chronic venous insufficiency, varicose veins, lipodermatosclerosis, postthrombotic syndrome, and venous ulceration. Some evidence suggests a genetic predisposition to chronic venous disease from gene polymorphisms associated mainly with vein wall remodeling. The literature exploring these polymorphisms has not been reviewed and compiled thus far. In this narrative and systematic review, we present the current evidence available on the role of polymorphisms in genes involved in vein wall remodeling and other pathways as contributors to chronic venous disease. We searched the EMBASE, Medline, and PubMed databases from inception to 2013 for basic science or clinical studies relating to genetic associations in chronic venous disease and obtained 38 relevant studies for this review. Important candidate genes/proteins include the matrix metalloproteinases (extracellular matrix degradation), vascular endothelial growth factors (angiogenesis and vessel wall integrity), FOXC2 (vascular development), hemochromatosis (involved in venous ulceration and iron absorption), and various types of collagen (contributors to vein wall strength). The data on associations between these genes/proteins and the postthrombotic syndrome are limited and additional studies are required. These associations might have future prognostic and therapeutic implications.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".