Chemolysis of a Uric Acid Stone in a Horseshoe Kidney
Bibliographic record
Abstract
Chemolysis of kidney stone is not unheard of. However, to our knowledge, there is no previous report of chemolysis of a kidney stone in a horseshoe kidney. We report the first ever case of chemolysis of a stone in a horseshoe kidney. As part of his visible haematuria workup 4 years ago, a 66-year-old gentleman with a history of gout was found to have a horseshoe kidney. In early 2017, he was seen in the urology clinic with some non-specific abdominal pain without a recent history of visible haematuria, lower urinary tract symptoms, and urinary tract infections. His CT KUB (computed tomography of kidneys, ureters and bladder), revealed a 1.3cm stone in his horseshoe kidney [Figure 1 and 2]. At the same time, his CT KUB has also picked up some retroperitoneal lymphadenopathy in the abdomen and pelvis which were suspicious of lymphoma. His serum uric acid level was noted to be normal. Subsequently, he underwent a laparoscopic right iliac lymph node biopsy which confirmed nodal marginal zone non-Hodgkin's B-cell lymphoma. He was reviewed by the haematology team and they decided to adopt a watch and wait approach to his disease with quarterly CT CAP (computed tomography of chest, abdomen and pelvis) scans. During this period of time, he had several gout attacks and he was started on allopurinol i.e. 100mg once a day. He also considerably increased his daily fluid intake. 6 months after his initial CT KUB, he was found to be completely stone free on his CT scan [Figure 3 and 4].
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| 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".