Recurrence of Paget-Schroetter Syndrome: A Rare Case Report and Review of Literature
Bibliographic record
Abstract
Paget-Schroetter syndrome (PSS) is a primary upper extremity deep vein thrombosis (DVT) that occurs with no significant risk factors, mostly in a young and healthy patient. Treatment of this disease is discussed heavily in the literature and the optimal treatment method is still being debated. Here, we present a patient with PSS treated with balloon angioplasty, thrombolysis and treatment with an oral thrombin inhibitor (apixaban) who developed recurrence of PSS. A 38-year-old white male with no past medical history, presented to an urgent care center with sudden onset axillary pain and an axillary lump that was treated with outpatient antibiotics. Extensive deep venous thrombosis was diagnosed with computed tomography (CT) and ultrasound. He underwent percutaneous pharmacomechanical thrombectomy. Postprocedural angiogram showed significant improvement in the caliber of the axillary and subclavian veins where they crossed the first rib. He was discharged on apixaban and underwent removal of his first rib 1 month later. He returned 3 weeks later with recurrence of right arm pain and swelling. Repeat ultrasound showed thrombus in the right arm and venogram confirmed 80% stenosis at the subclavian vein as it enters the innominate vein. He was again treated with placement of a thrombolytic catheter and overnight thrombolysis of the central venous circulation on the right-side upper extremity balloon angioplasty of the subclavian vein, axillary vein, and basilic vein. He is disease-free for 6 months. Recurrence of PSS after surgical removal of rib, thrombectomy, thrombolysis while using apixaban is very rare. This is the first case to our knowledge presented with recurrent PSS treated with apixaban, early rib resection, balloon angioplasty and thrombectomy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".