Infected popliteal pseudoaneurysm in a youth basketball player: A case report and brief review of the literature
Bibliographic record
Abstract
INTRODUCTION: An infected popliteal pseudoaneurysm has never been described in the pediatric population. Physicians need to be aware of its presentation and management, in order to diagnose and treat this medical condition adequately. METHODS: We describe the case of a 14-year-old boy who developed myositis and cellulitis centered at the popliteal fossa after playing basketball. A treatment of intravenous cefazolin was started. 5 days later, he experienced a knee pain flare-up, which turned out to be a popliteal pyomyositis with a pseudoaneurysm of the popliteal artery. A saphenous vein graft bypass of the popliteal artery and an excision of the popliteal pseudoaneurysm were performed. Intravenous cefazolin was continued for 6 weeks and prophylactic acetylsalicylic acid for 6 months. RESULTS AND CONCLUSION: This case highlighted the importance of repeating radiologic investigations if a patient suffering from soft tissue infection has persistent pain after several days of appropriate antibiotics. A popliteal pseudoaneurysm can be diagnosed with ultrasound imaging and treated with a popliteal-popliteal bypass. Our patient needed a catheter-guided dilation of the anastomosis at the vein graft 6 months post-surgery, and then evolved favorably and went back to playing basketball 6 months post-dilation.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".