Aneurysmal degeneration of vein conduit used for vascular reconstruction—Case report and literature review
Bibliographic record
Abstract
INTRODUCTION: Popliteal artery aneurysms (PAA) are the most prevalent form of peripheral arterial aneurysms. Greater saphenous vein grafts and endoaneurysmorrhaphy remains the mainstay therapy for open repair of PAA. True aneurysmal degeneration of lower extremity infrainguinal autologous vein grafts are relatively rare and its etiology is not completely understood. CASE PRESENTATION: We present a case of a 57-year-old man with recurrent autologous venous graft aneurysmal dilatations following a surgical popliteal artery aneurysm repair. DISCUSSION: The pathogenesis of true aneurysmal graft dilatation remains speculative with possible pathogenesis including progression of underlying atherosclerosis, systemic dilating diathesis, autologous venous graft varicosities, low-grade infections and post-stenotic dilatations. Management of venous graft aneurysms should be subjected to the same criteria as other aneurysms. Diagnosis requires a high index of suspicion. The initial study of choice is duplex ultrasonography as it can diagnose the aneurysm and distinguish it from other popliteal masses, provide accurately measurements and identify thrombus within the aneurysm. Once diagnosed, surgical repair should be performed as soon as possible as graft dilatation tends to occur overtime and is typically followed by a rapid increase in size over a short period of time. CONCLUSION: Aneurysmal degeneration of autologous saphenous venous graft following PAA repairs occur infrequently. Its etiology remains largely speculative. Accurate diagnosis and early surgical intervention can prevent progression of aneurysmal dilatation and minimize the potential of complications.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".