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Record W2120263956 · doi:10.1111/apa.12314

Can ultrasound be used to estimate bone mineral density in children with growth problems?

2013· article· en· W2120263956 on OpenAlexaff
Karim Khan, Kyriakie Sarafoglou, Arif Somani, Brigitte I. Frohnert, Bradley S. Miller

Bibliographic record

VenueActa Paediatrica · 2013
Typearticle
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsMcMaster University
FundersNational Center for Research ResourcesU.S. Public Health Service
KeywordsMedicineBone mineralUltrasoundDual energyNuclear medicineDual-energy X-ray absorptiometryLumbar spineInternal medicineRadiologySurgeryOsteoporosis

Abstract

fetched live from OpenAlex

AIM: To assess predictability of bone mineral density (BMD) of the lumbar spine (LS) determined by dual-energy x-ray absorptiometry (DXA) using by ultrasound speed of sound of the right and left radii (SOS-R and SOS-L) in patients with growth problems. METHODS: Ultrasound and DXA were compared in patients with advanced, normal and delayed bone ages assessed by Greulich and Pyle (GP) and Tanner and Whitehouse (TW3) methods. RESULTS: There was a strong correlation (r), of raw scores, between SOS-R and SOS-L, r = 0.81, p = 0.000 and their respective Z-scores, r = 0.78, p = 0.000. Z-score correlations were poor between SOS-R or SOS-L and LS-BMD. Sensitivity, specificity, positive and negative predictive values of SOS-R and Z-scores for predicting normal (>-1 to <1) and low (<-1) LS-BMD were poor. For high (>1) LS-BMD, Z-scores were 22%, 93%, 29% and 90%, respectively, for SOS-R and for SOS-L, 25%, 89%, 20% and 91%. For very low (<-2) LS-BMD, SOS-R and SOS-L were the same, respectively, 29%, 91%, 40% and 86%. CONCLUSION: Ultrasound of the radius is a poor predictor of radiologically assessed BMD at the LS, especially with delayed bone age.

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 score0.017
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.015
GPT teacher head0.283
Teacher spread0.268 · 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

Citations12
Published2013
Admission routes1
Has abstractyes

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