[Effect of posterior cruciate ligament retaining or not on knee-joint proprioception].
Bibliographic record
Abstract
OBJECTIVE: To analyze the effect of the posterior cruciate ligament (PCL) retaining or not on knee-joint proprioception by comparing the proprioceptive difference between PCL retaining and no PCL retaining in total knee arthroplasty (TKA). METHODS: Between June 2009 and June 2010, 38 osteoarthritis patients meeting the inclusion criteria were divided into PCL retaining group (group A, n=19) and PCL-substituting group (group B, n=19) according to the random number table. There was no significant difference in gender, age, disease duration, the range of motion of the knee between 2 groups (P > 0.05). The effectiveness and the knee-joint proprioception were separately assessed by the Western Ontario and McMaster University Osteoarthritis Index (WOMAC) score and the passive angle reproduction test (30, 60, and 90 degrees of knee flexion) preoperatively and 12 months postoperatively. RESULTS: All incisons healed by first intention, without complications of infection, fracture, and deep vein thrombosis of lower limb. The patients were followed up 12-17 months (mean, 14.1 months). The knee function after operation was obviously improved when compared with preoperative one; significant differences were observed in the WOMAC scores and the results of passive angle reproduction test between at preoperation and at 12 months after operation (P < 0.05), but no significant difference was found between group A and group B (P > 0.05). CONCLUSION: Whether PCL retaining or not in TKA both can improve knee-joint proprioception, and no obvious difference between them.
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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 | 0.001 |
| 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) | 0.003 | 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".