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Record W2518972738 · doi:10.1159/000447930

Effect of Denosumab on Peripheral Compartmental Bone Density, Microarchitecture and Estimated Bone Strength in <b><i>De Novo</i></b> Kidney Transplant Recipients

2016· article· en· W2518972738 on OpenAlexaff
Marco Bonani, Ursina Meyer, Diana Frey, Nicole Graf, Heike A. Bischoff‐Ferrari, Rudolf P. Wüthrich

Bibliographic record

VenueKidney & Blood Pressure Research · 2016
Typearticle
Languageen
FieldMedicine
TopicParathyroid Disorders and Treatments
Canadian institutionsInstitute of Aging
Fundersnot available
KeywordsBone mineralMedicineQuantitative computed tomographyUrologyTibiaDenosumabCortical boneInternal medicineOsteoporosisNuclear medicineSurgeryAnatomy

Abstract

fetched live from OpenAlex

BACKGROUND/AIMS: In a randomized controlled clinical trial in kidney transplant recipients (NCT01377467) we have recently shown that RANKL inhibition with denosumab significantly improved areal bone mineral density (aBMD) when given during the first year after transplantation. The effect of denosumab on skeletal microstructure and bone strength in kidney transplant recipients is not known. METHODS: The purpose of the present bone microarchitecture ancillary study was to investigate high-resolution peripheral quantitative computed tomography (HRpQCT) data from the distal tibia and distal radius in 24 study patients that had been randomized to receive either two injections of denosumab 60 mg at baseline and after 6 months (n=10) or no treatment (n=14). RESULTS: Consistent with the full trial findings, denosumab reduced biomarkers of bone turnover, and significantly increased aBMD at the lumbar spine (median difference of 4.7%; 95% confidence interval [CI] 2.6 - 7.8; p<0.001). Bone quality as assessed by total and cortical volumetric bone mineral density (Tot. vBMD, Ct.vBMD) and cortical thickness (Ct.Th) increased significantly at the tibia, while changes at the radius were less pronounced. The trabecular volumetric BMD (Tb.vBMD), thickness (Tb. Th), separation (Tb.Sp) and number (Tb.N) and the cortical porosity (Ct.Po) at the tibia and the radius did not significantly change in both treatment groups. Micro-finite element analysis (µFEA) showed that bone stiffness increased significantly at the tibia (median difference 5.6%; 95% CI 1.8% - 9.2%; p=0.002) but not at the radius (median difference 2.9%, 95% CI -3.7% - 9.1%; p=0.369). Likewise, failure load increased significantly at the tibia (median difference 5.1%; 95% CI 2.1% - 8.1%; p=0.002) but not at the radius (median difference 2.4%, 95% CI -3.2% - 8.5%; p=0.336). CONCLUSIONS: These findings demonstrate that denosumab improves bone density and bone quality in first-year kidney transplant recipients at risk to develop osteoporosis.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.311
Teacher spread0.294 · 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

Citations24
Published2016
Admission routes1
Has abstractyes

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