The Relationship of Cup Inclination and Anteversion in the Coronal Plane with Ante-Inclination in the Sagittal Plane
Bibliographic record
Abstract
Background: This study aimed to establish an equation for calculating cup ante-inclination (AI) from radiographic cup inclination and anteversion, to validate this equation in a total hip arthroplasty (THA) cohort, and to test whether achieving previously described radiographic cup inclination and anteversion targets would also satisfy sagittal cup AI targets. Methods: A mathematical equation linking cup AI, radiographic inclination (RI), and anteversion (RA) was determined: tan(AI) = tan(RA)/cos(RI). Supine and standing anteroposterior and lateral radiographs of 440 consecutive THAs were assessed to measure cup RI and RA and spinopelvic parameters, including cup AI, using a validated software tool. Whether orientation within previously defined RI and RA targets was associated with achieving the AI target and satisfying the sagittal component orientation (combined sagittal index, 205° to 245°) was tested. Results: The cups in the THA cohort had a measured mean inclination (and standard deviation) of 43° ± 7°, anteversion of 26° ± 9°, and AI of 34° ± 10°. The calculated cup AI was 34° ± 12°. A strong correlation existed between measured and calculated AI (r = 0.75; p < 0.001), with a mean error of 0° ± 8°. The inclination and anteversion targets were both satisfied in 194 (44.1%) to 330 (75.0%) of the cases, depending on the safe zone targets that were used, and 311 cases (70.7%) satisfied the AI target. Only 125 (28.4%) to 233 (53.0%) of the cases satisfied the AI target as well as the inclination and anteversion targets. Satisfying inclination and anteversion targets was not associated with increased chances of satisfying the AI target. Conclusions: Achieving optimal cup inclination and anteversion does not ensure optimal orientation in the sagittal plane. The equation and nomograms provided can be used to determine and visualize how the 2 planes used for evaluating the cup orientation and the pertinent angles relate, potentially aiding in preoperative planning.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".