Revision Total Knee Arthroplasty for the Management of Periprosthetic Fractures
Bibliographic record
Abstract
Periprosthetic fractures after total knee arthroplasty (TKA) can present reconstructive challenges. Not only is the procedure technically complex, but patients with these fractures may have multiple comorbidities, making them prone to postoperative complications. Early mobilization is particularly beneficial in patients with multiple comorbidities. Certain patient factors and fracture types may make revision TKA the ideal management option. Periprosthetic fractures around the knee implant occur most frequently in the distal femur, followed by the tibia and the patella. Risk factors typically are grouped into patient factors (eg, osteoporosis, obesity) and surgical factors (eg, anterior notching, implant malposition). Surgical options for periprosthetic fractures that involve the distal femur or proximal tibia include reconstruction of the bone stock with augments or metal cones or replacement with an endoprosthesis.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".