Evaluating Surgeon Estimation of Cup Position in Total Hip Arthroplasty: A Cadaver Study
Bibliographic record
Abstract
Abstract Inaccurate placement of components during total hip arthroplasty (THA) can lead to significant postoperative complications including revision surgery. Traditionally, surgeons grossly estimate component positioning intraoperatively using anatomical landmarks; however, evidence indicates that this surgeon assessment may not be reliable. The purpose of this study was to determine the accuracy of surgeon estimates of component position as compared with imaging (radiographs and computed tomography [CT] scan) and a new surgical navigation system. Three board-certified orthopaedic surgeons each performed four THA procedures on six cadavers (12 hips). Radiographs and CT scans were obtained postoperatively. The “gold standard” measurements of implanted cup anteversion and inclination were derived from three-dimensional renderings created from postoperative CTs. A reference value for cup position was created by aligning the anterior pelvic plane in each rendering coplanar with the CT table. Following each procedure, surgeons provided their estimate of acetabular cup component orientation. Surgeon estimates were compared with data gathered from postoperative radiographs, CT scans, and the navigation device. Surgeon estimates of anteversion and inclination were within 10 degrees of reference values in 64% (7/11) and 82% (9/11) of cases, respectively. Surgeon estimates of anteversion differed from reference values by a mean of 7.6 ± 5 degrees, whereas inclination differed from reference values by a mean of 6.1 ± 5.1 degrees (all means absolute). Radiographic measurements differed from reference values by 7.8 ± 4.3 degrees (p > 0.05) and 2.7 ± 2.3 degrees (p = 0.06) for anteversion and inclination, respectively, whereas CT values differed by 2.5 ± 1.6 degrees (p = 0.004) and 2.3 ± 2.1 degrees (p = 0.04). The navigation system differed from reference values by 4 ± 4 degrees (p = 0.08) and 4.2 ± 3.2 degrees (p = 0.31). Surgeons underestimated anteversion and inclination by 7.7 ± 4.8 degrees and 6.9 ± 4.8 degrees, respectively. Surgeon underestimation was observed in 8/11 (73%) cases, with anteversion underestimated by > 5 degrees in 5/8 (62%) cases and inclination underestimated by > 5 degrees in 4/8 (50%) cases. Our findings suggest that surgeons tend to underestimate both anteversion and inclination and that the accuracy of their estimates is similar to that of radiographs. CT scans and the navigation system were able to provide more accurate measurements of cup position.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".