Does cyclical loading affect the elution of antibiotics from articulating cement knee spacers?
Bibliographic record
Abstract
Two-stage revision surgery for infected total knee replacement offers the highest rate of success for the elimination of infection. The use of articulating antibiotic-laden cement spacers during the first stage to eradicate infection also allows protection of the soft tissues against excessive scarring and stiffness. We have investigated the effect of cyclical loading of cement spacers on the elution of antibiotics. Femoral and tibial spacers containing vancomycin at a constant concentration and tobramycin of varying concentrations were studied in vitro. The specimens were immersed and loaded cyclically to 250 N, with a flexion excursion of 45°, for 35 000 cycles. The buffered solution was sampled at set intervals and the antibiotic concentration was established so that the elution could be calculated. Unloaded samples were used as a control group for statistical comparison. The elution of tobramycin increased proportionately with its concentration in cement and was significantly higher at all sampling times from five minutes to 1680 minutes in loaded components compared with the control group (p = 0.021 and p = 0.003, respectively). A similar trend was observed with elution of vancomycin, but this failed to reach statistical significance at five, 1320 and 1560 minutes (p = 0.0508, p = 0.067 and p = 0.347, respectively). However, cyclically loaded and control components showed an increased elution of vancomycin with increasing tobramycin concentration in the specimens, despite all components having the same vancomycin concentration. The concentration of tobramycin influences both tobramycin and vancomycin elution from bone cement. Cyclical loading of the cement spacers enhanced the elution of vancomycin and tobramycin.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".