Examination of the Anatomy of Lower Limb Length Discrepancy (LLLD) between Inuit and Urban Populations: Orthopaedic Considerations
Bibliographic record
Abstract
Previous studies have shown that LLLD affects 40–80% of the population, with a discrepancy of greater than 2 cm affecting 1 in 1000 individuals. LLLD affects the functional and structural integrity of locomotor gait with associated anatomical responses: osteoarthritis of the hip, loosening of hip prosthesis, standing balance and lower back pain. Our previous study (Russo et al., 2005), using an urban population, identified femora as the lower limb segment responsible for LLLD, with no tibial contribution to the bilateral asymmetry; it also demonstrated a right femoral dominance for both mixed and single sex populations. This current study examined two human populations, Inuit (I) n = 38 and urban (U) n = 46, with significantly contrasting life styles and distinctive ethnic/racial affinities. The U study considered cadaver specimens over a 3‐year period, the I study, specimens from the Point Hope Collection at the American Museum of Natural History. Femora and tibia lengths were measured for both the U and I groups. Results from the U study reaffirmed previous findings; femora were the only contributing source for a significant LLLD, again with right side dominance, p<0.025. In contrast, the I study showed both femora and tibia exhibiting contributions to a significant LLLD, p<0.044 and p< 0.003, respectively. Femoral plus tibial lengths, used as a surrogate measure for lower limb, also yielded a significant difference for the I group, p<0.0003. Given that the most common acquired LLLD in urban populations is from postoperative total hip arthroplasty, our comparative anatomical study suggests that high kinematic stress from life style hardship behaviors can produce LLLD.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".