As in Real Estate, Location Is What Matters: A Case Report of Transplant Ureteral Obstruction Due to an Inguinal Hernia
Bibliographic record
Abstract
BACKGROUND: Kidney allograft dysfunction is common and often reversible but can lead to allograft loss if not promptly evaluated. Transplant ureteral obstruction in an inguinal hernia is a rare cause of allograft dysfunction, but early recognition may prevent allograft loss. CASE PRESENTATION: We present a case of a man with acute kidney allograft dysfunction who received a deceased donor kidney transplant 6 years earlier for end-stage kidney disease secondary to polycystic kidney disease. Abdominal ultrasounds revealed hydronephrosis without full visualization of the transplant ureter. Abdominal computed tomography revealed moderate hydronephrosis of the transplant kidney due to obstructed herniation of the transplant ureter in a right inguinal hernia. A stent was inserted into the transplant ureter to prevent further allograft dysfunction and facilitate hernia repair. CONCLUSIONS: Transplant ureteral obstruction is a rare cause of acute kidney allograft dysfunction, and its detection can be challenging. The recognition of transplant ureteral obstruction is vital to timely management for preventing allograft loss.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".