STUDY OF THE CLINICO-RADIOLOGICAL OUTCOME OF PCL RETAINING TOTAL KNEE ARTHROPLASTY IN SEVERE VARUS DEFORMITY: A PROSPECTIVE OBSERVATIONAL STUDY.
Bibliographic record
Abstract
Introduction: The role of the posterior cruciate ligament (PCL) in total knee arthroplasty (TKA) has been widely discussed in the orthopedic literature. It has been suggested that PCLretaining can produce femoral rollback, which increases the range of exion and prevents posterior translation. This in effect, reduces loosening and excessive polyethylene wear by decreasing the shear stresses at the xation surfaces. With consideration proper selection of patients, adequate attention to surgical technique and asepsis, proper Intra-operative soft tissue balancing, correct alignment of prosthesis and postoperative rehabilitation of patients, cruciate retaining total knee replacement has yielded excellent results Aim: The aim of this prospective study is to evaluate the clinic-radiological outcome of PCL retaining total knee arthroplasty in severe varus deformity Materials and Methods: This is a prospective study in which patients were randomly selected, and PCL retaining surgery was done for those knees with severe varus deformity and assessed the functional outcome using functional knee scores and oxford knee score and WOMAC (Western Ontario and McMaster Universities Osteoarthritis Index) questionnaires during the period between July 2016 to June 2018. Conclusion: PCL-retaining total knee arthroplasty appears to provide better range of motion and stair-climbing ability similar to anatomical knee.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".