THE OTTO AUFRANC AWARD: Bone Augmentation around and within Porous Implants by Local Bisphosphonate Elution
Bibliographic record
Abstract
The bisphosphonate zoledronic acid chemically and physically was bound to hydroxyapatite-coated porous tantalum implants. The zoledronic acid elution characteristics in saline were determined as a function of time and the in vivo effects of elution were quantified at 12 weeks in a canine ulnar implant model. Intramedullary implants surgically were implanted bilaterally into the ulnae of a control group of five dogs and a zoledronic acid-dosed (0.05 mg zoledronic acid) group of four dogs. Computerized image analysis of undecalcified histologic sections was used to quantify the amount of peri-implant bone within the intramedullary canal, the percentage of available pore space filled with new bone, and the number and size of the individual bone islands within the implant pores. The data were analyzed using a hierarchical analysis of variance with 95% confidence intervals. The peri-implant bone occupied a mean of 13.8% of the canal space in controls and 32.2% of the canal space in zoledronic acid-dosed dogs, a relative difference of 134% (2.34-fold) that was significant. The mean extent of bone ingrowth was 12.5% for the control implants and 19.8% for the zoledronic acid-dosed dogs, a relative difference of 58% that was statistically significant. Individual islands of new bone formation with the implant pores were similar in number in both implant groups but were 71% larger on average in the ZA-dosed group. We are the first authors to show that local elution of a bisphosphonate can cause substantial bone augmentation around and within porous orthopaedic implants. The concept represents a potential tool for restoration of bone stock and enhancement of implant fixation in primary and revision cementless joint arthroplasty surgeries in the face of compromised or deficient bone.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.073 | 0.030 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".