Outcome of Patients in Term of Range of Motion after Total Knee Arthroplasty with all Poly Implants
Bibliographic record
Abstract
Objective: To evaluate the outcome of patients in term of range of motion after total knee arthroplasty with all poly implants. Study Design: Retrospective study Place and Duration of Study: Department of Orthopaedics, Sahara Medical College, Narowal from 1st April 2021 to 31st March 2022. Methodology: Sixty various patients who came for total knee arthroplasty were selected on the basis of their conditions. Patients were divided into two inserts groups for understanding the better outcome results in terms of range of motion (ROM). Thirty patients having fixed bearing and other 30 patients having mobile bearing inserts will all poly implants. A standardized medial-parapatellar approach was taken for surgical procedure and resection of primary tibia was done. Pain function and evaluation was performed through knee society scoring (KSS) as well as VAS score and goniometer was used for analyzing range of motion which was defined as degree of flexion of knee subtracting from number of extension-defect. Results: There was no significant difference in either the gender or ages of both implants selected patients However the mobile bearing group patients has a better BMI value than the fixed bearing implant patients. In term of range of motion mobile bearing group patients had a higher ROM value than the fixed bearing operated patients in case of overall change in range of motion analysis. The Western Ontario and McMaster Universities Osteoarthritis (WOMAC) Index, score showed a significant change with an increased value observed in mobile bearing implant patients. Conclusion: Visual analogue pain score show significant difference in mobile and fixed bearing group. In terms of range of motion, mobile implants show better outcome in contrast to fixed bearing group. Keywords: Knee implants, Mobile, Fixed bearing, Outcomes, Osteolysis
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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 | 0.001 |
| 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) | 0.002 | 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".