Review of patient-reported outcomes in periprosthetic distal femur fractures after total knee arthroplasty: a plate or intramedullary nail?
Bibliographic record
Abstract
PURPOSE: This study reviewed the literature regarding the patient-reported treatment outcomes of using either open reduction and internal fixation (ORIF) with a plate and screw system or intramedullary nail (IMN) fixation for periprosthetic distal femur fractures around a total knee arthroplasty. METHODS: A total of 13 studies published in the last 20 years met the inclusion criteria. The studies included 347 patients who were allocated to ORIF (n = 249) and IMN (n = 98) groups according to the implants used. The primary outcome measures were the Knee Society Score or the Western Ontario and McMaster Universities osteoarthritis index. The secondary outcome measures included knee range of motion and the rates of complications, including non-union, malunion, infection, revision total knee arthroplasty, and reoperation. Statistical significance was set at P < 0.05. RESULTS: The mean Knee Society Scores of ORIF and IMN groups were 83 and 84, respectively; the mean postoperative range of motion of the knee were 99° and 100°, respectively (P < 0.05); the non-union rates were 9.4 and 3.8%, respectively (P > 0.05); the malunion rates were 1.8 and 7.5%, respectively (P < 0.05); surgical site infection rates were 2 and 1.3%, respectively (P > 0.05); the reoperation rates were 9.6 and 5.1%, respectively (P > 0.05); and revision rates of total knee arthroplasty were 2 and 1%, respectively (P > 0.05). CONCLUSION: Based on the patient-reported outcome assessments, both ORIF with a plate and screw system and IMN fixation are well-accepted techniques for periprosthetic distal femur fractures around a TKA, and they produce similar functional outcomes.
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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 | 0.007 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".