Atypical Presentation of Paget-Schroetter Syndrome: Case Report and Management
Bibliographic record
Abstract
Upper extremity deep vein thrombosis (UEDVT) is a rare condition that makes early clinical evaluation and treatment important prior to the formation of deep vein thrombosis (DVT). Typical risk factors include male sex, young age, repetitive arm over abduction and hyperextension, indwelling catheters, cervical first rib, and thoracic outlet syndrome. One common cause of UEDVT is Paget-Schroetter syndrome (PSS). If untreated, pulmonary complications such as venous thromboembolic disease and pulmonary embolism (PE) may develop. We present a case of a 34-year-old Caucasian female who presented to the emergency department with sudden, acute right arm pain after blow-drying her hair, consistent with UEDVT. CT angiography (CTA) demonstrated moderate thromboembolic disease within segmental and subsegmental branches of the left upper, left lower, and right lower lobes. Ultrasonography (US) of the upper extremity showed non-compressibility of the right axillary and basilic vein, a finding consistent with acute DVT. Peripheral angiogram revealed imaging consistent with undiagnosed thoracic outlet syndrome secondary to effort thrombosis. The patient deferred surgical intervention and agreed to begin long-term anticoagulation therapy. PSS requires immediate recognition and treatment to prevent possible long-term neurologic and vascular compromise. Despite the patient lacking the typical population demographics, PSS should be considered given the patient's symptoms and presentation. Recognition of UEDVT despite classic signs and symptoms consistent with known risk factors is imperative upon clinical suspicion. Delay in clinical management may lead to fatal complications. We aim to highlight a case of PSS along with alternative pathways for treatment delivery.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 0.004 |
| 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".