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Record W1995192760 · doi:10.1359/jbmr.2003.18.4.610

Bone Mass, Size, and Density in Children and Adolescents With Osteogenesis Imperfecta: Effect of Intravenous Pamidronate Therapy

2003· article· en· W1995192760 on OpenAlexaff
Frank Rauch, Horacio Plotkin, Leonid Zeitlin, Francis H. Glorieux

Bibliographic record

VenueJournal of Bone and Mineral Research · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicConnective tissue disorders research
Canadian institutionsMcGill UniversityMontreal Children's Hospital
Fundersnot available
KeywordsOsteogenesis imperfectaMedicineBone mineralDensitometryBone densityBone massPeak bone massBone mineral contentOsteoporosisInternal medicineAnatomy

Abstract

fetched live from OpenAlex

Cyclical intravenous therapy with pamidronate improves the clinical course in children and adolescents with osteogenesis imperfecta (OI). In this study, we evaluated the effect of this therapy on lumbar spine bone mass (bone mineral content [BMC]), size (bone volume [BV]), and density (volumetric bone mineral density [vBMD]). Results from 56 patients (age, 0.2-15.9 years; 25 girls) on long-term pamidronate treatment were compared with those of 167 patients who had not received pamidronate before densitometry. In all patients who received pamidronate, BMC, BV, and vBMD increased above levels expected for untreated patients (p < 0.001 in each case). After 4 years of treatment, BMC, BV, and vBMD were 154%, 44%, and 65% higher, respectively, in treated than in untreated patients who were matched for age and OI type. A multiple regression model showed that baseline BMC was negatively associated with the increase in BMC. In conclusion, the bone mass increase in pediatric OI patients receiving pamidronate is caused by increases in both bone size and density. Patients with larger deficits in bone mass at baseline have a more marked bone mass gain during therapy.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.364
Threshold uncertainty score0.341

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.009
GPT teacher head0.288
Teacher spread0.279 · 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

Citations194
Published2003
Admission routes1
Has abstractyes

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