Extensor Mechanism Failure Associated With Total Knee Arthroplasty: Prevention and Management
Bibliographic record
Abstract
Extensor mechanism complications are the most commonly reported reasons for revision surgery after total knee arthroplasty and are a frequent source of postoperative morbidity. Patellofemoral instability is the most commonly reported extensor mechanism complication and has multiple etiologies, including prosthetic malalignment and soft-tissue imbabalce. Patellar fracture or rupture of either the quadriceps or patellar tendon can cause catastrophic disruption of the extensor mechanism. Although some stable fractures can be successfully managed nonsurgically, displaced fractures or tendon rupture often lead to poor results. Other complications include patellar clunk and soft-tissue adhesions, prosthetic wear or loosening, and osteonecrosis. Increased understanding of implant alignment, rotation, and soft-tissue balance, as well as improved design of the trochlear groove of femoral implants and patellar components, has resulted in a decline in extensor mechanism complications. Appropriate prosthetic selection and meticulous surgical technique remain the keys to avoiding unsatisfactory results and revision surgery.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".