Minimum ten-year follow-up of a randomized trial comparing acetabular component fixation of two porous in-growth surfaces using radiosteriometric analysis
Bibliographic record
Abstract
Aims To compare the in vivo long-term fixation achieved by two acetabular components with different porous ingrowth surfaces using radiostereometric analysis (RSA). Methods This was a minimum ten-year follow-up of a prospective randomized trial of 62 hips with two different porous ingrowth acetabular components. RSA exams had previously been acquired through two years of follow-up. Patients returned for RSA examination at a minimum of ten years. In addition, radiological appearance of these acetabular components was analyzed, and patient-reported outcome measures (PROMs) obtained. Results In all, 15 hips were available at ten years. There was no statistically significant difference in PROMS between the two groups; PROMs were improved at ten years compared to preoperative scores. Conventional radiological assessment revealed well-fixed components. There was minimal movement for both porous surfaces in translation (X, Y, Z, 3D translation in mm (median and interquartile range (IQR)), StikTite (Smith and Nephew, Memphis, Tennessee, USA): 0.03 (1.08), 0.12 (0.7), 0.003 (2.3), 0.37 (0.30), and Roughcoat (Smith and Nephew): -0.6 (0.59),–0.1 (0.49), 0.1 (1.12), 0.48 (0.38)), and rotation (X, Y, Z rotation in degrees (median and IQR), (Stiktite: -0.4 (3), 0.28 (2), -0.2 (1), and Roughcoat: - 0.4 (1),–0.1 (1), 0.2 (2)). There was no statistically significant difference between the two cohorts (p-value for X, Y, Z, 3D translation - 0.54, 0.46, 0.87, 0.55 and for X, Y, Z rotation - 0.41, 0.23, 0.23 respectively) at ten years. There was significant correlation between two years and ten years 3D translation for all components ( r = 0.81(p =< 0.001)). Conclusion Both porous ingrowth surfaces demonstrated excellent fixation on plain radiographs and with RSA at ten years. Short-term RSA data are good predictors for long-term migration data.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".