Update on the diagnosis and treatment of CNO in children: a clinician’s perspective
Bibliographic record
Abstract
Chronic non-bacterial osteomyelitis (CNO) is caused by aseptic inflammation of bones, primarily driven by the innate immune system. CNO may display different clinical presentations (acute vs chronic, uni- vs multifocal) and is accompanied by other inflammatory disorders in up to a third of patients. Once considered a rare disorder, it has become clear that many patients were underdiagnosed. With increasing awareness and the development of total-body MRI protocols, CNO recognition and diagnosis have greatly improved. Our knowledge of the clinical manifestations and outcomes of CNO has been refined in recent years, especially thanks to the recruitment of large international series. Similarly, new insights into the pathogenesis have been gained by the development of mice models and identification of rare monogenic diseases that resemble CNO. Unfortunately, these advances have not been paralleled in the therapeutic management. In the absence of prospective controlled trials, therapeutic strategies still rely on low-level evidence studies. About half of the patients respond to first-line therapies, but a more refractory and/or chronic disease course requires additional treatments. This narrative review aims to provide the practicing physician with an update on CNO pathogenesis, clinical presentation, associated inflammatory conditions, and diagnostic investigations, and includes a concise summary of current therapeutic recommendations. CONCLUSION: While major progresses have been made in the recognition and management of CNO, significant challenges remain, in particular regarding the treatment of refractory patients, and those with associated inflammatory disorders. WHAT IS KNOWN: • Many physicians caring for children will encounter patients suffering of (suspected) CNO. CNO diagnosis requires exclusion of numerous conditions included in the differential diagnosis, which may be challenging. WHAT IS NEW: • We provide an updated review of recent findings in the field CNO, including imaging and diagnostic strategies, associated inflammatory diseases and long-term outcomes data. • We focus particularly on the challenges encountered by clinicians in the diagnosis and treatment of these patients. • We highlight knowledge gaps in the understanding and treatment of CNO, that should stimulate future research.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".