An in vitro study comparing limited to full cementation of polyethylene glenoid components
Bibliographic record
Abstract
BACKGROUND: Glenoid component survival is critical to good long-term outcomes in total shoulder arthroplasty. Optimizing the fixation environment is paramount. The purpose of this study was to compare two glenoid cementing techniques for fixation in total shoulder arthroplasty. METHODS: Sixteen cadaveric specimens were randomized to receive peg-only cementation (CPEG) or full back-side cementation (CBACK). Physiological cyclic loading was performed and implant displacement was recorded using an optical tracking system. The cement mantle was examined with micro-computed tomography before and after cyclic loading. RESULTS: Significantly greater implant displacement away from the inferior portion of the glenoid was observed in the peg cementation group when compared to the fully cemented group during the physiological loading. The displacement was greatest at the beginning of the loading protocol and persisted at a diminished rate during the remainder of the loading protocol. Micro-CT scanning demonstrated that the cement mantle remained intact in both groups and that three specimens in the CBACK group demonstrated microfracturing in one area only. DISCUSSION: Displacement of the CPEG implants away from the inferior subchondral bone may represent a suboptimal condition for long-term implant survival. Cement around the back of the implant is suggested to improve initial stability of all polyethylene glenoid implants. CLINICAL RELEVANCE: Full cementation provides greater implant stability when compared to limited cementation techniques for insertion of glenoid implants. Loading characteristics are more favorable when cement is placed along the entire back of the implant contacting the subchondral bone.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".