Rare Case of Acute Renal Artery Thrombosis in Nephrotic Syndrome: The Unusual Presentations and Outcomes of Endovascular Manual Aspiration Thrombectomy
Bibliographic record
Abstract
Renal artery thrombosis is a rare condition that requires early diagnosis and urgent intervention to prevent renal infarction and permanent renal damage. Possibility of renal artery thrombosis should be considered in patients with underlying hypercoagulable state presented with acute unremitting flank pain, nausea and vomiting. We report a case of a 35-year-old man with underlying nephrotic syndrome who presented with three days history of acute non-localized and non-resolving abdominal pain and vomiting. He was initially referred to general surgery for acute intestinal obstruction. Contrast-enhanced computed tomography (CECT) abdomen revealed acute left renal infarction secondary to total thrombotic occlusion of the left renal artery. The patient was treated with endovascular manual aspiration thrombectomy resulting in partial revascularization of left renal artery with restoration of renal function, complete resolution of symptom and good clinical outcomes. This case report serves as a reminder for physicians to include renal infarction in the differential diagnosis when evaluating a patient with acute abdomen, particularly in patient with hypercoagulable state. This case also aligns with other experiences demonstrating positive outcomes after endovascular thrombectomy, even in the presence of prolonged renal ischemia time of more than 72 hours.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 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".