The effect of surface inclination and limb on knee loading measures in transtibial prosthesis users
Bibliographic record
Abstract
BACKGROUND: Osteoarthritis (OA) is a degenerative disease caused by the wearing of joint cartilage and bone. Literature has established that a prosthesis user's intact limb is at greater risk of developing OA. This study analyzed the effect of commonly encountered surface inclinations on knee joint loading measures in able-bodied and transtibial prosthesis users. METHODS: 12 transtibial prosthesis users and 12 able-bodied participants walked across level ground, up slope, down slope, and cross slope (further divided into top and bottom slope depending on the location of the limb being analyzed). First and second peak external knee adduction moment (KAM), external knee adduction moment rate, and external knee adduction moment impulse were extracted from the stance phase of gait. Mixed ANOVA statistics with Bonferonni post hoc analyses were performed. RESULTS: Significant limb differences were only found for KAM rate and first peak KAM. When compared to all other surfaces up slope had the significantly lowest KAM rate and was not significantly lower for all other tested variables. Down slope had significantly greater KAM rate than all surfaces except bottom slope. KAM second peak and KAM impulse analysis resulted in no significant differences. CONCLUSIONS: Individuals at risk for developing, or currently dealing with, knee OA could avoid walking for extended periods on down slope. Walking up moderate slopes may be considered as a complementary activity to level walking for rehabilitation and delaying OA progression. The lack of significant limb differences suggests that second peak KAM and KAM impulse may not be appropriate load-related indicators of OA initiation among prosthesis users without OA. KAM rate was the most sensitive joint loading variable and therefore should be investigated further as an appropriate variable for identifying OA risk in individuals with transtibial amputations.
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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 | 0.000 |
| 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".