MétaCan
Menu
Back to cohort
Record W3164938161 · doi:10.1186/s12887-021-02716-x

Rickets manifestations in a child with metaphyseal anadysplasia, report of a spontaneously resolving case

2021· review· en· W3164938161 on OpenAlexaff
Patricia Diaz Escagedo, Mélissa Fiscaletti, Patricia Vit Olivier, Chloé Hudon, Valancy Miranda, Marie‐Claude Miron, Philippe M. Campeau, Nathalie Alos

Bibliographic record

VenueBMC Pediatrics · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnective tissue disorders research
Canadian institutionsCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsRicketsMedicineShort staturePediatricsToddlerDifferential diagnosisMetaphysisInternal medicineSurgeryPathologyVitamin D and neurology

Abstract

fetched live from OpenAlex

INTRODUCTION: Rickets is not an unusual diagnosis for pediatricians even currently in developed countries. Children typically present with leg bowing, enlargement of wrists, rachitic rosary (swelling of costochondral junctions) and/or waddling gait. But not every child with growth delay and enlarged metaphyses is diagnosed with rickets. Metaphyseal anadysplasia (MAD) is a disorder of variable severity with metaphyseal flaring and irregularities, without vertebral abnormalities. MAD is characterized by an early onset and a regressive course in late childhood without treatment, despite persistent short stature. Autosomal dominant or recessive variants in the matrix metalloproteinase 13 gene (MMP13) are responsible for these transient metaphyseal changes. CASE PRESENTATION: We report a new pathogenic heterozygous variant in MMP13 (NM_002427.4: c.216G>C, p.Gln72His) in a toddler, initially thought to have rickets, and his father, with MAD phenotypes. Additionally, we review the seven reported MMP13 variants. CONCLUSION: One should keep a wide differential diagnosis in cases of suspected rickets, including skeletal dysplasias which might have a regressive course.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.516
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.035
GPT teacher head0.349
Teacher spread0.314 · 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 teacher head, not a consensus.

Study designCase report
Domainnot available
GenreReview

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

Citations4
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueBMC PediatricsSame topicConnective tissue disorders researchFrench-language works237,207