A novel total knee arthroplasty infection model in rabbits
Bibliographic record
Abstract
Infection of biomaterial implants is an expensive and devastating complication of orthopaedic surgery historically ranging from less than 1% in primary total knee arthroplasty (TKA) to 10% in revision TKA. An in vivo animal model was developed to test the efficacy of innovative therapies for the prevention of biomaterial centered infections caused by methicillin-resistant Staphylococcus aureus bacteria (MRSA). Twenty-two New Zealand White rabbits were used in this study. After proper anesthesia, a stainless-steel screw with a high molecular weight polyethylene (UHMWPE) washer was cemented in a defect created in the intra-articular, non-articulating portion of the lateral femoral condyle of each knee. After closure of the joint capsule, each knee was inoculated with 0, 10(2), 10(3), or 10(4) colony forming units (CFU) of MRSA. Animals were sacrificed after 7 days at which time joint aspirate, tissues and biomaterial samples were examined for evidence of infection. A total of 42 knees were used for analysis. When saline was injected into the knee, 0/10 of the knees demonstrated evidence of biomaterial centered infection (with the contralateral knee receiving 10(4)CFU MRSA). Four of 10 knees developed a biomaterial centered infection when 10(2)CFU MRSA was introduced. Seven out of 10 knees developed a biomaterial centered infection when either 10(3) or 10(4)CFU MRSA was injected. No evidence of septicemia (positive blood cultures) was found in any animal. This rabbit knee model utilizes commonly employed inexpensive orthopaedic implant materials in an in vivo milieu and provides an effective method for the evaluation of treatments for biomaterial centered infections.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".