Results of Press-fit Stems in Revision Knee Arthroplasties
Bibliographic record
Abstract
The ideal method of stem fixation in revision knee arthroplasty is controversial with advantages and disadvantages for cemented and press-fit designs. Studies have suggested cemented revision knee stems may provide better long-term survival. The aim of this study was to report our experience with press-fit uncemented stems and metaphyseal cement fixation in a selected series of patients undergoing revision total knee arthroplasty. One hundred twenty-seven patients (135 knees) who underwent revision total knee arthroplasty using a press-fit technique (press-fit diaphyseal fixation and cemented metaphyseal fixation) were reviewed. Minimum followup was 2 years (mean, 5 years; range, 2-12 years). A Kaplan-Meier survivorship analysis using an end point of revision surgery or radiographic loosening was used to determine probability of survival at 5 and 10 years. Of the 127 patients (135 knees), 31 patients (36 knees) died and two patients (two knees) were lost to followup. Six patients (six knees) had revisions at a mean of 3.5 years (range, 1-8 years). Kaplan-Meier survivorship analysis revealed a probability of survival free of revision for aseptic loosening of 98% at 12 years. Survivorship of press-fit stems for revision knee arthroplasty is comparable to reported survivorship of cemented stem revision knee arthroplasty. Radiographic analysis has shown continued satisfactory appearances regardless of constraint, stem size, and augmentations.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".