Urinary N-telopeptide as a Biomarker of Disease Activity in Patients with Chronic Nonbacterial Osteomyelitis Who Have Not Received Bisphosphonates
Bibliographic record
Abstract
Chronic nonbacterial osteomyelitis (CNO) is a rare autoinflammatory disease that causes bone destruction, soft tissue swelling, and bone pain1. Diagnosis and treatment are hindered by a lack of a reliable laboratory test to assess disease activity. Bone inflammation in CNO is associated with increased osteoclastic activity and bone resorption, causing focal accelerated breakdown of bone collagen. This may be measured through elevated urinary N-terminal telopeptide (NTx). Miettunen, et al reported rapid decline of urinary NTx in children with CNO after pamidronate treatment and subsequent rise of NTx was correlated with disease flare2. The initial NTx from patients with CNO was not different from that of healthy children. Correlation of NTx with disease activity in patients with CNO not treated with pamidronate has not been investigated. We sought to determine if NTx values correlate with CNO disease activity in children treated without a bisphosphonate. Children with a CNO diagnosis made by a pediatric rheumatologist as well as their nonadult healthy siblings were recruited from the rheumatology clinics after written informed consent was obtained (approved by Seattle Children’s Hospital, IRB 14426, and University of Iowa, IRB 200308051). Inclusion criteria consisted of a clinical diagnosis of CNO, … Address correspondence to Dr. Y. Zhao[4][1], 4800 Sand Point Way NE, Seattle, WA 98105, USA. Email: yongdong.zhao{at}seattlechildrens.org. [1]: #ref-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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".