Reconstruction of Complete Knee Extensor Mechanism Loss with Gastrocnemius Flaps
Bibliographic record
Abstract
UNLABELLED: We assessed the outcome after reconstruction of traumatic, complete, infected, extensor mechanism loss attributable to high-velocity open knee injuries in eight consecutive patients (all males) who presented to us between February 2005 and September 2007 at an average followup of 24 months. All were treated with gastrocnemius flaps. The loss in extensor mechanism was the patellar tendon in five patients, patella and patellar tendon in two patients, and combined patella, quadriceps, and patellar tendon in one patient. The size of the defect ranged from 8 x 5 cm to 15 x 15 cm. The patients were evaluated for functional outcome of the knee, resolution of infection, range of flexion of the knee, and return to work. Four patients had an excellent outcome whereas the others had a good outcome using the Hospital for Special Surgery knee rating scale. All flaps healed primarily with resolution of infection. The average knee flexion was 110 degrees. All patients except two returned to their original occupation. Three patients had an extensor lag of 5 degrees. The gastrocnemius flap is a good option for open knee injuries with extensor mechanism loss, giving consistent results across a wide spectrum of presentation. LEVEL OF EVIDENCE: Level IV, case series. See the Guidelines for Authors for a complete description of levels of evidence.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".