Radiographic Measures of Knee Alignment in Patients with varus Gonarthrosis
Bibliographic record
Abstract
BACKGROUND: Radiographic measures of lower limb malalignment are used to indicate abnormal loading of the knee and to plan corrective procedures. HYPOTHESES: Weightbearing status during hip-to-ankle radiographs will significantly affect malalignment measures; malalignment in single-limb standing will be most highly correlated to the external knee adduction moment during gait, a proposed dynamic measure of functional knee joint load. STUDY DESIGN: Controlled laboratory study. METHODS: Mechanical axis angle was measured in 40 patients with varus gonarthrosis from hip-to-ankle radiographs taken with patients in single-limb standing, double-limb standing, and supine positions. Kinematic and kinetic data were collected during walking and used to calculate the peak adduction moment about the knee. RESULTS: Repeated-measures analysis of variance and Scheffé post hoc tests indicated that mechanical axis angle measured on single-limb standing radiographs (-8.7 degrees +/- 4.0 degrees) was significantly greater than on double-limb standing radiographs (-7.1 degrees +/- 3.8 degrees), which was significantly greater than on supine radiographs (-5.5 degrees +/- 2.8 degrees). The peak knee adduction moment (2.8 +/- 0.8 percentage body weight x height) was only moderately correlated with mechanical axis angle on single-limb standing (r = -0.46), double-limb standing (r = -0.45), and supine (r = -0.43) radiographs. CONCLUSION: Patient position significantly affects frontal plane knee alignment. However, the peak knee adduction moment is only moderately correlated to mechanical axis angle, regardless of weightbearing status. CLINICAL RELEVANCE: These findings are inconsistent with the hypothesis that mechanical axis angle measured in single-limb standing is more representative of dynamic joint load and further highlight the differences between static and dynamic measures. Results also underscore the importance of reporting patient position during radiographs and keeping positions consistent when evaluating patients over time.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".