The effects of proprioceptive or strength training on the neuromuscular function of the ACL reconstructed knee: a randomized clinical trial
Bibliographic record
Abstract
OBJECTIVES: The purpose of this study was to determine the effects of a proprioceptive training program (PT) vs. a strength training (ST) program on neuromuscular function after anterior cruciate ligament (ACL) reconstruction. The second purpose was to establish the determinants of functional ability for the operated limb. METHODS: Ten participants with unilateral ACL reconstructions were randomly assigned to one of the following 12-week training protocols: (1) isotonic ST, and (2) PT. The outcome measures were: (1) peak torque time of the hamstring muscles (PeakTT), (2) average concentric and eccentric torques of the quadriceps and hamstring muscles, (3) one-legged single hop for distance (SLHD), (4) one-legged time hop (TH), and (5) subjective scores. RESULTS: : There was a significant group by time interaction effect for PeakTT (P = 0.017). The PT group demonstrated greater percent change in isokinetic torques than the ST group at the end of the 12 weeks (P < or = 0.05). Participants in both groups demonstrated similar significant gains in functional ability and subjective scores (P < or = 0.014). Quadriceps strength is a determinant of functional ability for the operated limb (R2 = 0.72). CONCLUSIONS: : Both training protocols influenced PeakTT. The beneficial effects of ST on PeakTT appear to be load-dependent, while sufficient practice may be crucial in maintaining PeakTT improvements induced by PT. Proprioceptive training alone can induce isokinetic strength gains. Restoring and increasing quadriceps strength is essential to maximize functional ability of the operated knee joint.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".