Early acetabular cup migration may be a source of error in the assessment of intra-operative placement accuracy
Bibliographic record
Abstract
Proper alignment of the acetabular cup is essential for long-term success total hip arthroplasty (THA) success. Computer navigation and robotic techniques have been of interest to improve cup alignment, with their accuracy often reported by comparing the intraoperative alignment to six-week postoperative alignment; however, early component migration is known to occur within the first six weeks. This study aimed to assess the potential error in cup position measurements caused by early acetabular cup migration within the first six weeks following THA. Acetabular cup inclination and anteversion angles were measured by two raters from radiographs taken intra-operatively and at six weeks post-operation. An RSA examination was performed on the day of surgery as well as 6-weeks post-operation. Thirty-three patients were included in our analysis. Mean inclination angles were 31.2° intra-operatively and 32.8° at six weeks post-operation (maximum difference = 11.1°). Mean anteversion angles were 23.5° and 29.3° intra-operatively and at six weeks post-operation (maximum difference = 15.3°). Mean anterior tilt, internal rotation, and valgus rotation between the day of surgery and six weeks post-operation were 1.33°, 0.98°, and 0.80°, respectively. This study demonstrated that early migration of acetabular cups may introduce an error in studies reporting computer navigation accuracy in acetabular cup placement based on post-operative imaging follow-ups.
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 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".