2008 John Charnley Award: Metal Ion Levels After Metal-on-Metal Total Hip Arthroplasty: A Randomized Trial
Bibliographic record
Abstract
UNLABELLED: Metal-on-metal bearing total hip arthroplasty is performed more commonly than in the past. There may be manufacturing differences such as clearance, roughness, metallurgy, and head size that affect performance. In a prospective, randomized trial, we compared 2-year postoperative ion levels for a 28-mm metal-on-polyethylene bearing with 28-mm and 36-mm metal-on-metal bearings. We measured serum, erythrocyte, and urine ion levels. We observed no difference in the ion levels for the 28-mm and 36-mm metal-on-metal bearings. The ion levels in these patients were lower than reported for most other metal-on-metal bearings. Although both erythrocyte and serum cobalt increased, erythrocyte chromium and erythrocyte titanium did not increase despite a four- to sixfold serum chromium and a three- to fourfold serum titanium increase. This may represent a threshold level for serum chromium and serum titanium below which erythrocytes are not affected. LEVEL OF EVIDENCE: Level I, therapeutic study. See the Guidelines for Authors for a complete description of levels of evidence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.079 | 0.004 |
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".