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Record W1998906488 · doi:10.1186/1546-0096-9-s1-p262

Identification of predictors of bone mineral density trajectories in pediatric Systemic Lupus Erythematosus patients

2011· article· en· W1998906488 on OpenAlexaff
SHL Lim, Susanne M. Benseler, Pascal N. Tyrrell, Martin Charron, E.K. Silverman

Bibliographic record

VenuePediatric Rheumatology · 2011
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsCanadian Nuclear Laboratories
Fundersnot available
KeywordsMedicineBone mineralCumulative doseBody mass indexCohortInternal medicineSystemic lupusStandard scorePediatricsOsteoporosisMathematics

Abstract

fetched live from OpenAlex

Results Females constituted 84% of the cohort with a median age at diagnosis of 13.1 years. The mean LS BMD zscores decreased with time. Initially, 9% of patients had a low BMD, this proportion increased to 19% by 3 years after diagnosis. Overall, the BMD category decreased in 35% of patients from 1 to 3rd DEXA study. LS BMD followed a general deteriorating trajectory of -0.25 z-score/year from diagnosis. Body mass index (BMI) z-score and cumulative steroid dose were the best predictors of BMD trajectories over time. Conclusions The LS BMD of pSLE patients decreased at a rate of 0.25 z-score/year. BMI z-score and cumulative doses of steroids modified the trajectories of LS BMD. These factors are potentially modifiable targets that can improve individual patient’s BMD trajectory.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
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 head0.016
GPT teacher head0.248
Teacher spread0.232 · 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
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
Published2011
Admission routes1
Has abstractyes

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