Marked functional improvement in a pediatric patient treated with hemodialysis for scleroderma related renal failure
Bibliographic record
Abstract
Systemic sclerosis (SSc) is a rare autoimmune disease characterized by fibrosis and vasculopathy of the skin and visceral organs. Scleroderma renal crisis (SRC), the most acute and life threatening complication, occurs in 10–20% of adult patients with SSc and has not been reported in children. A 10‐year‐old girl was diagnosed with SSc when she presented with weakness and skin thickening. She had positive ANA and anti‐Scl 70. Renal function, urinalysis, and blood pressure were normal. She was treated with steroids, penicillamin and methotrexate as well as amlodipine for Raynaud's phenomenon, but her diffuse skin thickening and contractures progressed and she became wheelchair bound and had poor growth despite nutrition through a G‐tube. At age 15 (weight 28 kg), when evaluated for abdominal pain, she was found to have acute renal failure (BUN 54 mg/dl, creatinine 2.2 mg/dl) and hypertension. Despite therapy with enalapril, serum creatinine continued to rise and she became oligoanuric, requiring initiation of hemodialysis. BP was controlled with enalapril and dialysis but she remained dialysis dependent. Steroid therapy was discontinued and replaced by low dose cyclosporine. Enalapril was replaced by losartan because of leukopenia and BP remained normal. Over the next 2 years, she was treated with hemodialysis and did not experience any complications. She progressively had an outstanding overall clinical improvement, marked skin softening, and was able to walk independently. Renal function did not improve. 28 months after the SRC, she received LRD renal transplant. Immunosuppression included cyclosporine, mycophenolate and prednisone. Creatinine 2 months post‐transplant is 0.7 mg/dl. SRC in children may progress to end‐stage renal disease but can be treated successfully with dialysis and transplantation without significant complications.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".