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Record W3181350235 · doi:10.1210/clinem/dgab494

Osteoporotic Fractures and Vertebral Body Reshaping in Children With Glucocorticoid-Treated Rheumatic Disorders

2021· article· en· W3181350235 on OpenAlexafffundabout
Leanne M. Ward, Jinhui Ma, Marie‐Eve Robinson, Maya Scharke, Josephine Ho, Kristin Houghton, Adam M. Huber, Rosie Scuccimarri, Julie Barsalou, Johannes Roth, Nazih Shenouda, Mary Ann Matzinger, Brian C. Lentle, Jacob L. Jaremko, Khaldoun Koujok, Karen Watanabe Duffy, Robert Stein, Anne Marie Sbrocchi, Celia Rodd, Päivi Miettunen, Claire LeBlanc, Maggie Larché, Roman Juřenčák, Elizabeth Cummings, Robert Couch, David A. Cabral, Stephanie A. Atkinson, Nathalie Alos, Elizabeth Sykes, Victor N. Konji, Frank Rauch, Kerry Siminoski, Bianca Lang

Bibliographic record

VenueThe Journal of Clinical Endocrinology & Metabolism · 2021
Typearticle
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsUniversity of ManitobaWestern UniversityUniversity of AlbertaUniversité de MontréalDalhousie UniversityMcGill UniversityChildren's Hospital of Eastern OntarioUniversity of CalgaryUniversity of British ColumbiaMcMaster UniversityUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsMedicineOsteoporosisContext (archaeology)Incidence (geometry)Bone mineralPediatricsBody mass indexCohortInternal medicineProspective cohort studyPopulation

Abstract

fetched live from OpenAlex

CONTEXT: Osteoporotic fractures are an important cause of morbidity in children with glucocorticoid-treated rheumatic disorders. OBJECTIVE: This work aims to evaluate the incidence and predictors of osteoporotic fractures and potential for recovery over six years following glucocorticoid (GC) initiation in children with rheumatic disorders. METHODS: Children with GC-treated rheumatic disorders were evaluated through a prospective inception cohort study led by the Canadian STeroid-induced Osteoporosis in the Pediatric Population (STOPP) Consortium. Clinical outcomes included lumbar spine bone mineral density (LS BMD), vertebral fractures (VF), non-VF, and vertebral body reshaping. RESULTS: A total of 136 children with GC-treated rheumatic disorders were enrolled (mean age 9.9 years, SD 4.4). The 6-year cumulative fracture incidence was 16.3% for VF, and 10.1% for non-VF. GC exposure was highest in the first 6 months, and 24 of 38 VF (63%) occurred in the first 2 years. Following VF, 16 of 19 children (84%) had complete vertebral body reshaping. Increases in disease activity and body mass index z scores in the first year and declines in LS BMD z scores in the first 6 months predicted incident VF over the 6 years, while higher average daily GC doses predicted both incident VF and non-VF. LS BMD z scores were lowest at 6 months (mean -0.9, SD 1.2) and remained low by 6 years even when adjusted for height z scores (-0.6, SD 0.9). CONCLUSION: VF occurred early and were more common than non-VF in children with GC-treated rheumatic disorders. Eighty-four percent of children with VF underwent complete vertebral body reshaping, whereas vertebral deformity persisted in the remainder of children. On average, LS BMD z scores remained low at 6 years, consistent with incomplete recovery.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.049
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.379
Teacher spread0.353 · 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 source (direct Gemma or distilled Codex), 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

Citations19
Published2021
Admission routes3
Has abstractyes

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