Management of bone disease in cystinosis: Statement from an international conference
Bibliographic record
Abstract
Cystinosis is an autosomal recessive storage disease due to impaired transport of cystine out of lysosomes. Since the accumulation of intracellular cystine affects all organs and tissues, the management of cystinosis requires a specialized multidisciplinary team consisting of pediatricians, nephrologists, nutritionists, ophthalmologists, endocrinologists, neurologists' geneticists, and orthopedic surgeons. Treatment with cysteamine can delay or prevent most clinical manifestations of cystinosis, except the renal Fanconi syndrome. Virtually all individuals with classical, nephropathic cystinosis suffer from cystinosis metabolic bone disease (CMBD), related to the renal Fanconi syndrome in infancy and progressive chronic kidney disease (CKD) later in life. Manifestations of CMBD include hypophosphatemic rickets in infancy, and renal osteodystrophy associated with CKD resulting in bone deformities, osteomalacia, osteoporosis, fractures, and short stature. Assessment of CMBD involves monitoring growth, leg deformities, blood levels of phosphate, electrolytes, bicarbonate, calcium, and alkaline phosphatase, periodically obtaining bone radiographs, determining levels of critical hormones and vitamins, such as thyroid hormone, parathyroid hormone, 25(OH) vitamin D, and testosterone in males, and surveillance for nonrenal complications of cystinosis such as myopathy. Treatment includes replacement of urinary losses, cystine depletion with oral cysteamine, vitamin D, hormone replacement, physical therapy, and corrective orthopedic surgery. The recommendations in this article came from an expert meeting on CMBD that took place in Salzburg, Austria, in December 2016.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.017 | 0.017 |
| Insufficient payload (model declined to judge) | 0.007 | 0.005 |
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".