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Record W4388591171 · doi:10.1016/j.bonr.2023.101725

Burosumab for the treatment of cutaneous-skeletal hypophosphatemia syndrome

2023· article· en· W4388591171 on OpenAlexafffund
Lillian Abebe, Kim Phung, Marie‐Eve Robinson, Richelle C. Waldner, Sasha Carsen, Kevin Smit, Andrew Tice, Joanna Lazier, Christine M. Armour, Marika Pagé, Saunya Dover, Frank Rauch, Khaldoun Koujok, Leanne M. Ward

Bibliographic record

VenueBone Reports · 2023
Typearticle
Languageen
FieldMedicine
TopicParathyroid Disorders and Treatments
Canadian institutionsUniversity of AlbertaShriners Hospitals for Children - CanadaUniversity of OttawaMcGill UniversityChildren's Hospital of Eastern Ontario
FundersShriners Hospitals for ChildrenUniversity of Ottawa
KeywordsHypophosphatemiaRicketsHypophosphatemic RicketsOsteomalaciaMedicineFibroblast growth factor 23Fibroblast growth factorInternal medicineEndocrinologyVitamin D and neurologyCalciumReceptor

Abstract

fetched live from OpenAlex

Cutaneous-skeletal hypophosphatemia syndrome (CSHS) is a rare bone disorder featuring fibroblast growth factor-23 (FGF23)-mediated hypophosphatemic rickets. We report a 2-year, 10-month-old girl with CSHS treated with burosumab, a novel human monoclonal antibody targeting FGF23. This approach was associated with rickets healing, improvement in growth and lower limb deformity, and clinically significant benefit to her functional mobility and motor development. This case report provides evidence for the effective use of FGF23-neutralizing antibody therapy beyond the classic FGF23-mediated disorders of X-linked hypophosphatemia and tumor-induced osteomalacia.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.023
GPT teacher head0.297
Teacher spread0.274 · 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 designNon-randomized trial
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

Citations8
Published2023
Admission routes2
Has abstractyes

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