Accuracy of the modified Hardinge approach in acetabular positioning
Bibliographic record
Abstract
BACKGROUND: The surgical approach chosen for total hip arthroplasty (THA) may affect the positioning of the acetabular component. The purpose of this study was to examine the accuracy in orienting the acetabular component using the modified Hardinge approach. METHODS: We used our institutional arthroplasty database to identify patients with primary, press-fit, hemispherical acetabular components of a metal-on-polyethylene THA performed between 2003 and 2011. Patients with radiographs obtained 1-3 years after the index procedure were included for measurement of anteversion and inclination angles. Acceptable values of anteversion and abduction angles were defined as 15° ± 10° and 40° ± 10°, respectively. RESULTS: We identified 1241 patients from the database, and the modified Hardinge approach was used in 1010 of the patients included in our analysis. The acetabular component was anteverted in the acceptable zone in 54.1% of patients. The abduction angle was within the defined range in 79.2% of patients. Combined anteversion and abduction angles within the defined zone were present in 43.6% of patients. CONCLUSION: Consistent with studies examining accuracy from other approaches, our study reveals that the modified Hardinge approach was only moderately accurate in positioning the acetabular component in the acceptable zone.
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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 | 0.018 |
| 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 | 0.001 |
| Open science | 0.001 | 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".