The role of thrombectomy and diffusion-weighted imaging with MRI in post-transplant renal vein thrombosis: a case report
Bibliographic record
Abstract
BACKGROUND: Surgical thrombectomy in the context of acute renal vein thrombosis (RVT) post-transplantation has had limited success, with considerable variation in the surgical techniques used. Unfortunately, it is usually followed by allograft nephrectomy within a few days if rapid allograft recovery does not ensue. We report a case of acute RVT in which nephrectomy was not performed despite a prolonged requirement for dialysis post-thrombectomy, but with recovery of renal function 2 weeks later. We also report the findings of serial MRI with diffusion-weighted imaging (DW-MRI) throughout the patient's recovery, which provided novel insights into allograft microvascular perfusion changes post-thrombectomy. CASE PRESENTATION: A 65-year old patient underwent living-unrelated kidney transplantation complicated by acute RVT. Surgical thrombectomy and irrigation led to a delayed, but significant, recovery of renal function. Serial non-contrast DW-MRI scanning was used to non-invasively assess microvascular renal blood flow post-operatively. Unlike standard Doppler ultrasonography, DW-MRI documented reduced microvascular perfusion initially, with gradual but incomplete recovery that mirrored the partial improvement in renal function. CONCLUSIONS: Our findings suggest that surgical thrombectomy may be more effective than previously described if followed by careful patient observation. Moreover, diffusion-weighted MRI appears to provide important insights into the pathophysiology of delayed graft function and deserves further investigation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".