Genicular Artery Embolization for Recurrent Hemarthrosis of the Knee Following Total Knee Arthroplasty: A Single Centre Experience
Bibliographic record
Abstract
PURPOSE: To retrospectively review the safety and efficacy of genicular artery embolization procedures performed at our institution in patients presenting with recurrent knee hemarthrosis following total knee arthroplasty (TKA). MATERIALS AND METHODS: A total of 13 consecutive patients (average age: 68; range 51-84, 62% female) were identified who underwent 14 genicular artery embolization procedures after presenting with recurrent hemarthrosis after TKA. Patient charts were retrospectively reviewed for demographic information, pre-embolization investigations, and details of embolization procedure including complications, technical success, and clinical success. Each patient had failed initial conservative therapy and all patients had a diagnostic aspiration performed by the referring physician prior to the procedure. The average time between TKA and embolization in our cohort was 21 months. RESULTS: All procedures performed were technically successful, defined as elimination of periprosthetic hypervascular blush. An average of 3.6 genicular vessels were embolized in each patient; 355 to 500 µm polyvinyl alcohol (PVA) particles were used in each case. There were no cases of transient cutaneous ischemia, skin erythema, or skin necrosis. Clinical success was obtained in 85.7% of cases, defined by elimination of the presenting clinical symptoms (knee pain and swelling) during continued follow-up by the referring clinician. CONCLUSION: Particle embolization is a safe and effective treatment for recurrent hemarthrosis after arthroplasty and our experience suggests that utilizing particle sizes of greater than 300 µm appears to be important in order to avoid cutaneous ischemic 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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".