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Record W4313482893 · doi:10.1136/bcr-2022-252471

Chronic recurrent multifocal osteomyelitis with a comprehensive approach to differential diagnosis of paediatric skull pain

2023· article· en· W4313482893 on OpenAlexafffund
Ross Fraleigh, Xing‐Chang Wei, Weiming Yu, Paivi Miettunen

Bibliographic record

VenueBMJ Case Reports · 2023
Typearticle
Languageen
FieldMedicine
TopicOsteomyelitis and Bone Disorders Research
Canadian institutionsUniversity of CalgaryAlberta Children's Hospital
FundersAlberta Children's Hospital FoundationChildren's Hospital Foundation
KeywordsMedicineChronic recurrent multifocal osteomyelitisDifferential diagnosisSkullOsteomyelitisFrontal boneBiopsyLangerhans cell histiocytosisBone painEosinophilic granulomaRadiologyHistiocytosisDermatologySurgeryPathologyDiseaseOsteitis

Abstract

fetched live from OpenAlex

A girl in middle childhood was referred to rheumatology with a 1-month history of progressive skull pain, preceded by fleeting musculoskeletal symptoms. Apart from a scaly rash on her scalp, she was well, with moderately elevated inflammatory markers. Skull imaging (radiographs, CT and MRI) revealed osteolytic lesions, soft tissue swelling and pachymeningeal enhancement at frontal and temporal convexities. Langerhans cell histiocytosis, bone infection/inflammation or malignancy was considered. Skin and bone biopsies eventually ruled out mimicking diseases and confirmed the diagnosis of chronic recurrent multifocal osteomyelitis (CRMO). She was treated with intravenous pamidronate (IVPAM) for 9 months, with rapid resolution of pain and gradual resolution of bony abnormalities. She remains in remission at 15-month follow-up. While CRMO can affect any bone, skull involvement is extremely rare, with a broad differential diagnosis. We recommend bone biopsy to confirm skull CRMO. The patient achieved excellent clinical and radiological response to IVPAM.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.039
GPT teacher head0.324
Teacher spread0.286 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2023
Admission routes2
Has abstractyes

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