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Record W1973853198 · doi:10.1302/0301-620x.87b3.14665

Zoledronic acid causes enhancement of bone growth into porous implants

2005· article· en· W1973853198 on OpenAlexaff
J Bobyn, S. Adam Hacking, Jan J. Krygier, Edward J. Harvey, David G. Little, Michael Tänzer

Bibliographic record

VenueJournal of Bone and Joint Surgery - British Volume · 2005
Typearticle
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsMontreal General HospitalMcGill University
FundersNovartis Pharma
KeywordsZoledronic acidBisphosphonateImplantFixation (population genetics)DentistryBiomedical engineeringBiocompatibilityMedicineDiphosphonatesSalineUrologyMaterials scienceOsteoporosisSurgeryInternal medicineBone resorption

Abstract

fetched live from OpenAlex

The effect of zoledronic acid on bone ingrowth was examined in an animal model in which porous tantalum implants were placed bilaterally within the ulnae of seven dogs. Zoledronic acid in saline was administered via a single post-operative intravenous injection at a dose of 0.1 mg/kg. The ulnae were harvested six weeks after surgery. Undecalcified transverse histological sections of the implant-bone interfaces were imaged with backscattered scanning electron microscopy and the percentage of available pore space that was filled with new bone was calculated. The mean extent of bone ingrowth was 6.6% for the control implants and 12.2% for the zoledronic acid-treated implants, an absolute difference of 5.6% (95% confidence interval, 1.2 to 10.1) and a relative difference of 85% which was statistically significant. Individual islands of new bone formation within the implant pores were similar in number in both groups but were 69% larger in the zoledronic acid-treated group. The bisphosphonate zoledronic acid should be further investigated for use in accelerating or enhancing the biological fixation of implants to bone.

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)0.000
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 score0.579
Threshold uncertainty score0.834

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.013
GPT teacher head0.230
Teacher spread0.217 · 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

Citations82
Published2005
Admission routes1
Has abstractyes

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