Case of New Onset Acute Leukemia Complicated by Renal Calculi and Gout Attack: A Case Report
Bibliographic record
Abstract
Increased level of uric acid could be due to several etiologies, mainly non-balanced diet, and if uncontrolled can cause serious outcomes. Hyperuricemia’s major adverse effects in an individual can include nephropathy, nephrolithiasis and uric acid depositions in joints. On the other hand, hyperuricemia can be the result of several underlying disorders, of which are the hematologic malignancies. A case presented to our institution with generalized fatigue found to have multiple electrolytes abnormalities. On further investigation, the patient was diagnosed with acute leukemia, hyperuricemia and kidney calculus and acute gouty arthritis concurrently, and treated with surgery, corticosteroid and uric acid lowering agents and pain management. Diagnosis and rapid management of acute leukemia associated with hyperuricemia is crucial to avoid the complication of uric acid accumulation in different body organs. World J Nephrol Urol. 2021;10(1):18-20 doi: https://doi.org/10.14740/wjnu424
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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) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".