In vitro biomechanical evaluation of fibular movement in below knee amputations
Bibliographic record
Abstract
Background In below knee amputations (BKA), the tibia and fibula may be subjected to intrinsic and extrinsic forces resulting in fibular rotation and abduction, impeding ambulation. We investigated the effect of biceps femoris muscle tension and interosseous membrane (IOM) integrity on fibular kinematics in two BKA lengths. We hypothesize the stabilizing role of the IOM will be decreased in shorter amputations, and therefore, fibular movement will occur more readily. Methods Two cadaveric specimens, disarticulated at the knee, were amputated at 5 and 10cm lengths. Tibiae were mounted in a material testing machine and biceps femoris tendons (BFT) were sutured to the actuator. A cyclical loading pattern applied displacement‐dependent tensile forces (initial displacement of 3mm for 100 cycles @1Hz with increments of 1mm) to the BFT. The three‐dimensional kinematics of the tibia with respect to the fibula were measured. To evaluate the role of the IOM, the aforementioned procedure was repeated on specimens with a sectioned IOM. Results The 10cm BKA required more force than the 5cm BKA in the 100 th cycle at each incremental displacement block, presumably due to decreased fibular movement. However, this difference is predicted to be negated when the IOM is sectioned. Conclusion Understanding the cause of fibular abduction in BKA will lead to recommendations for preventive surgical and rehabilitative measures. Grant Funding Source : Departmental
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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 | 0.000 |
| 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) | 0.002 | 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".