Catheter-Directed Thrombectomy in Acute Renal Vein Thrombosis
Bibliographic record
Abstract
Introduction: Renal vein thrombosis (RVT) is a rare condition that can lead to severe complications including acute kidney injury or renal failure. Malignancy and nephrotic syndrome are the most common etiologies accounting for up to 66% and 20% of cases, respectively. The standard treatment for RVT is anticoagulation, but in the presence of declining renal function or contraindications, catheter-directed thrombectomy (CDT) can be considered. Case Description: A 64-year-old female with CKD stage IIIa, hypertension and nephrolithiasis presented with acute left flank pain, AKI (creatinine 1.35mg/dL) and a 7cm left renal subcapsular hematoma with large RVT. Urinalysis revealed trace blood and protein with urine ACR of 8.2mg/mmol. On day three, kidney function declined to creatinine of 2.1mg/dL. Due to the rapid decline in kidney function and renal hematoma, precluding anticoagulation, CDT was performed. The clot was successfully retrieved and renal flow was restored. The creatinine approached baseline within a few days. Interestingly, the pathology demonstrated fragments of renal cell carcinoma within the thrombus despite no clear evidence of malignancy on CT or MRI imaging. Discussion: We present the successful use of CDT for acute RVT secondary to renal cell carcinoma for diagnostic and therapeutic purposes. CDT permits rapid recannulization of the renal vein and facilitates faster renal recovery. Direct access permits interventions including venoplasty or stent placement for persistent stenosis or elastic recoil. To our knowledge, there are no previously reported cases of thrombectomy for acute RVT secondary to tumor thrombus. CDT is a potentially safe and effective treatment option for acute RVT, especially in the setting of declining renal function or contraindications to anticoagulation.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".