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Record W1986029912 · doi:10.1542/peds.111.5.e601

Rapid Increase in Grip Force After Start of Pamidronate Therapy in Children and Adolescents With Severe Osteogenesis Imperfecta

2003· article· en· W1986029912 on OpenAlexaff
Kathleen Montpetit, Horacio Plotkin, Frank Rauch, Nathalie Bilodeau, Suzanne Cloutier, Mary Rabzel, Francis H. Glorieux

Bibliographic record

VenuePEDIATRICS · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnective tissue disorders research
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineOsteogenesis imperfectaIsometric exerciseGrip strengthHand strengthBody weightProspective cohort studyInternal medicineSurgeryAnatomy

Abstract

fetched live from OpenAlex

OBJECTIVE: To examine changes in grip force during pamidronate therapy in children and adolescents with severe osteogenesis imperfecta (OI). METHODS: Maximal isometric grip force of the nondominant hand was prospectively determined in 42 patients (age at the start of the study: 7.3-15.9 years; 18 girls) with severe forms of OI. Patients were treated with intravenous pamidronate infusions given in 4 monthly cycles, each cycle consisting of 3 infusions (1 mg pamidronate/kg body wt) on 3 successive days. RESULTS: At the start of pamidronate therapy, grip force was low compared with age-specific reference data (age z score mean +/- standard deviation: -2.7 +/- 2.1) but was normal for weight (weight z score: -0.1 +/- 1.8). Four months after the first pamidronate infusion cycle, grip force had increased significantly, whether related to age (age z score: -2.0 +/- 1.8) or to weight (weight z score: 0.6 +/- 1.5). At 2 years after the start of therapy, grip force z scores were not significantly different from the 4-month results. CONCLUSIONS: Maximal isometric grip force markedly increases after a single cycle of intravenous pamidronate in children with severe forms of OI, and this gain in grip force is maintained for at least 2 years.

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 score0.004
Threshold uncertainty score0.466

Codex and Gemma teacher scores by category

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 integrity0.0000.000
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 head0.005
GPT teacher head0.224
Teacher spread0.219 · 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

Citations76
Published2003
Admission routes1
Has abstractyes

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