Comparison of Lifts Versus Tape Measure in Determining Leg Length Discrepancy
Bibliographic record
Abstract
OBJECTIVE: To evaluate the validity (accuracy) and reliability of 2 commonly used clinical methods, 1 indirect (lifts) and 1 direct (tape measure), for assessment of leg length discrepancy (LLD) in comparison to radiograph. METHODS: Twenty subjects suspected of having LLD participated in this study. Two clinical methods, 1 direct using a tape measure and 1 indirect using lifts, were standardized and carried out by 4 examiners. Difference in height of the femoral heads on standing pelvic radiograph was measured and served as the gold standard. RESULTS: The intraclass correlation coefficient assessing interobserver reliability was 0.737 for lifts and 0.477 for tape measure. The remainder of the analysis is based on the average of the measurements by the 4 examiners. Pearson correlation coefficients were 0.93 for the lifts and 0.75 for the tape measure method. Paired sample t tests showed difference in means of 2 mm (p = 0.051) for lifts and -5 mm (p = 0.007) for tape measure compared with radiograph. Sensitivity and specificity were 55% and 89% for lifts and 45% and 56% for tape measure, respectively, using > 5 mm as the definition for LLD. The wrong leg was identified as being shorter in 1 out of 20 subjects using lifts versus 7 out of 20 using tape measure. CONCLUSION: The indirect standing method of LLD measurement using lifts had superior validity, interobserver reliability, and specificity in comparison with radiograph over the direct supine method using tape measure. Both clinical methods underestimated LLD compared with radiograph.
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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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".