Single-Session Treatment of Upper Extremity Deep Venous Thrombosis and Central Venous Catheter Malfunction Using the ClotTriever System
Bibliographic record
Abstract
Intravenous catheters account for the majority of cases of upper extremity deep vein thrombosis (UEDVT), with a higher incidence in patients suffering from malignancy. Sequelae of UEDVT are similar to that of lower extremity DVT, comprising post-thrombotic syndrome and pulmonary embolism. While there are several treatment options for UEDVT including systemic anticoagulation, catheter-directed thrombolysis, and percutaneous mechanical thrombectomy, due to the absence of consistent guidelines regarding its management, treatment is often individualized based on patient characteristics, clinical factors, and technical considerations. We present a case of a 49-year-old female suffering from breast cancer with a central venous catheter (CVC) who came to the clinic with UEDVT and CVC malfunction and was successfully treated with mechanical thrombectomy using the ClotTriever System (Inari Medical, Irvine, CA). To our knowledge, this is the first report of the ClotTriever System being used to treat UEDVT and simultaneously salvage the CVC in a single session.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".