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Record W4409017979 · doi:10.1016/j.gimo.2025.103428

Real-world treatment with elosulfase alfa in patients with MPS IVA is associated with improved endurance over time

2025· article· en· W4409017979 on OpenAlexaff
Barbara K. Burton, Karolina M. Stępień, Philippe M. Campeau, Jaim Sutton, Abigail Hunt, Pascal Reisewitz, David A. Hinds

Bibliographic record

VenueGenetics in Medicine Open · 2025
Typearticle
Languageen
FieldMedicine
TopicLysosomal Storage Disorders Research
Canadian institutionsCentre Hospitalier Universitaire Sainte-Justine
FundersBioMarin Pharmaceutical
KeywordsMedicine

Abstract

fetched live from OpenAlex

Purpose To assess the real-world effectiveness of enzyme replacement therapy (ERT; elosulfase alfa) on endurance in the treatment of mucopolysaccharidosis type IVA (MPS IVA) using cross-sectional data. Methods The 6-minute walk test (6MWT) distances of ERT-treated and untreated participants from the Morquio A Registry Study and Morquio A Clinical Assessment Program were described for age groups of interest (5 to <7 years, 9 to <11 years, 14 to <16 years, and 20 to <30 years). Linear and quantile univariate regression were performed to explore variables associated with 6MWT (ERT, sex, age, standing height, body weight, region, and race). Multivariate regression analyses were performed using covariates identified in univariate analyses ( P < .10), adjusting for confounders. Results A total of 471 participants were included; baseline characteristics were similar within age groups. Median 6MWT distances were numerically greater in ERT-treated versus untreated participants within each age group. Quantile regression adjusting for multiple factors indicated a consistent trend of improved 6MWT with ERT treatment. Standing height was also associated with longer 6MWT in the multivariate quantile analysis, except in participants aged 5 to <7 years. Conclusion This analysis assessed associations between ERT exposure and endurance to confirm the real-world, long-term effectiveness of elosulfase alfa in participants with MPS IVA.

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)0.000
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 score0.037
Threshold uncertainty score0.932

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
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 head0.018
GPT teacher head0.325
Teacher spread0.307 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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