Modular junction may be more problematic than bearing wear in metal-on-metal total hip arthroplasty
Bibliographic record
Abstract
INTRODUCTION: In total hip arthroplasty (THA), local adverse reaction to metal debris (ARMD) may be caused by abnormal metal ion release from a metal-on-metal (MoM) bearing, or by wear and corrosion of the implant's modular junction. The aim of this study was to compare ion levels and rate of ARMD between patients sharing the same MoM bearing but 1 group having monoblock stems versus another having modular stems. MATERIALS AND METHODS: Whole blood cobalt (Co) and chromium (Cr) ion concentrations, ARMD rate, revision rate, and function measured by UCLA and WOMAC scores were compared between groups. RESULTS: ARMD rate was significantly higher in the modular group (46%) compared with the monoblock group (16%, p = 0.031). Revision for ARMD was performed at 52.8 ± 8.1 months in the modular group versus 98.2 ± 15.5 months after primary THA in the monoblock group. ARMD originated from wear and corrosion of the junction between stem and femoral head adapter sleeve in all monoblock cases, and the junction between stem and modular neck in all the modular ones. Cr and Co ions levels were significantly higher in the modular stem group ( p < 0.001 for both). CONCLUSIONS: Although both groups had MoM bearings, corrosion at stem/neck or neck/head junctions combining dissimilar metal (Ti and Cr-Co) was seen as the source of excess metal ions release leading to ARMD. Poor performance of the modular junction may be more deleterious than wear of the bearing. To avoid such complications, THA femoral stem modular junctions should be eliminated (return to a full monoblock implant) or have improved junction design.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".