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Record W2981793802 · doi:10.1002/ajmg.a.61378

Growth patterns for untreated individuals with MPS I: Report from the international MPS I registry

2019· article· en· W2981793802 on OpenAlexaff
David Viskochil, L. Clarke, Luisa Bay, Hillary A. Keenan, Joseph Muenzer, Nathalie Guffon

Bibliographic record

VenueAmerican Journal of Medical Genetics Part A · 2019
Typearticle
Languageen
FieldMedicine
TopicLysosomal Storage Disorders Research
Canadian institutionsBC Children's HospitalUniversity of British Columbia
FundersSanofi GenzymeSanofi
KeywordsMedicineInternal medicine

Abstract

fetched live from OpenAlex

Mucopolysaccharidosis Type I (MPS I), caused by deficiency of α-L-iduronidase results in progressive, multisystemic disease with a broad phenotypic spectrum including patients with severe (Hurler syndrome) to attenuated (Hurler-Scheie and Scheie syndromes) disease. Disordered growth is common with either phenotype. The study objectives were to construct sex- and age-specific estimated length/height and head circumference growth curves for untreated individuals with severe and attenuated disease and compare them with clinical reference standards. Untreated individuals in the MPS I Registry with at least one observation for length/height and/or head circumference and assigned phenotype as of May 2017 were included. Median growth for 463 untreated individuals with severe disease deviated from reference growth curves by ~6 months of age and fell below the third percentile by 4 years of age. Median head circumference was above reference curves from 3 to 4 months through 3 years of age. Among 207 individuals with untreated attenuated disease, median height fell below the third percentile by 9 years of age with divergence from reference curves by 2 years of age. MPS I-specific growth curves will be useful in evaluation of long-term outcomes of therapeutics interventions and will provide a foundation for understanding the pathogenesis of skeletal disease in MPS I.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.301
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.314
Teacher spread0.295 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations26
Published2019
Admission routes1
Has abstractyes

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