The Effect of Rehabilitation in Hip and Knee Proprioception in Older Adults Following Hip Fracture
Bibliographic record
Abstract
1010 Ongoing risk of falls and disability following hip fracture may involve proprioceptive deficits. PURPOSE: To determine the effect of post-surgical rehabilitation on proprioception in the hip and knee joints of patients with hip fracture on discharge from an inpatient hip fracture rehabilitation program. METHODS: Proprioception (Biometrics Ltd. electrogoniometer) was assessed within 48 h of admission and 48 h before discharge. The passive to active reproduction of joint angle technique was performed to determine absolute angular error (AAE) in non-weight-bearing positions at 15°, 30°, and 60° of hip flexion and knee extension in both the injured and non-injured sides. Data were collected on 30 hip fracture patients (3 men, 27 women; mean age 80 ± 7 y, range 66–94 y) who attended physiotherapy and occupational therapy sessions 5 times/week during a mean rehabilitation hospital length of stay of 25 ± 8 days. RESULTS: On admission, there was a significant difference in AAE between the injured and non-injured hips indicating that the hip fracture affected hip joint proprioception. There was a significant (p < .05) decrease in AAE from admission (5.3 ± 2.6°; 4.1 ± 3.1°) to discharge (3.0 ± 2.3°; 2.8 ± 3.1°) in hip flexion and knee extension, respectively, on the injured side. The magnitude of the AAE was significantly different (p < .05) at 15° compared to 30° and 60° angles in both hip flexion and knee extension at admission and discharge on the injured side. CONCLUSION: The rehabilitation program was focused on strengthening, balance, and gait retraining, all of which contribute to mobility and may indirectly improve proprioception. Hip and knee joint proprioception significantly improved in the injured side after the program.
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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 | 0.000 | 0.004 |
| 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) | 0.001 | 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".