The Hip Center Rule Can be Used to Decide if Measured Pelvic Incidence is Accurate
Bibliographic record
Abstract
STUDY DESIGN: Simulation study. OBJECTIVE: Pelvic incidence (PI) should be considered during surgical planning. The ideal patient position with both hip centers perfectly aligned for a lateral radiograph is rarely obtained. It has been suggested that a radiograph with axial and coronal rotation up to 20° is acceptable to obtain a measured PI within 6 degrees of the actual PI. We seek to: (1) evaluate the effect of variations in PI and patient malpositioning on measured vs true PI, and (2) determine whether the presence of one hip center within the bony acetabular rim of the contralateral hip can serve as a simple clinical decision rule on the accuracy of measured PI. METHODS: Published anthropometric three-dimensional pelvic landmark coordinates were used in this study. Radiographic projections were generated using linear algebra for combinations of axial and coronal rotation from -20° to +20°. True and measured PIs were compared. RESULTS: Rotation to 20° cannot be uniformly accepted as decision rule. Pelvises with higher PIs are more sensitive to malpositioning with greater PI deviation with smaller amounts of rotation. Diagnostic performance of the hip center rule demonstrated a sensitivity of 25.58% and a specificity of 100.00%. CONCLUSIONS: Rather than assessing the quality of radiographs for PI measurement by magnitude of malpositioning, we recommend clinicians use the "hip center rule." As long as at least one hip center is contained within the bony acetabular rim of the contralateral hip, there is high confidence that measured PI will be within 6° of true PI.
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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 | 0.013 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".