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Course of joint range of motion in children with spinal muscular atrophy receiving disease-modifying treatment

2025· other· en· W7106244599 on OpenAlexaff

Bibliographic record

VenueUtrecht University Repository (Utrecht University) · 2025
Typeother
Languageen
Field
Topic
Canadian institutionsMcMaster University
Fundersnot available
KeywordsRange of motionSMA*WristElbowSpinal muscular atrophyCohortKnee JointCohort study

Abstract

fetched live from OpenAlex

Abstract Background Progressive decreases in joint range of motion (ROM) is a well-recognized complication in the natural history of spinal muscular atrophy (SMA). How joint ROM evolves in children with SMA receiving disease-modifying treatment (DMT) needs to be documented. Purpose To examine the longitudinal course of joint range of motion in young children with SMA receiving disease-modifying therapy. Methods We included children with SMA (with 2 or 3 SMN2 copies) who started treatment within the first 18 months of life in a prospective national tertiary cohort study. Our examination consisted of joint range of motion of the knee, elbow and wrist; the longitudinal course was studied using linear mixed-effects models. Results We analysed 165 visits of 39 children (median age 22 months (interquartile range [6–45])) with treated SMA over a 3-year follow-up period. The median age at start of treatment was 2 months [0–8]. We found an average yearly decline in knee extension mobility of 3°. The overall course of range of motion for elbow and wrist remained stable. Conclusion The course of joint mobility in children with SMA, who started treatment with DMT in the first 18 months of life, is characterised by a decline in knee extension and a stable range of motion of wrist and elbow joints. We stress the importance of monitoring knee extension range of motion at least every 6 months and adopting a proactive approach to maintain full knee extension for optimal lifelong mobility.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.223
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.010
GPT teacher head0.193
Teacher spread0.183 · 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 designObservational
Domainnot available
GenreOther

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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