A Study to Find out Effect of Mechanical Knee Traction versus IFT on Pain and Functional Disability in Patients with Knee Osteoarthritis - An Interventional Study
Bibliographic record
Abstract
OA is degenerative joint disorder of articular cartilage leading to a decreased joint space width and range of motion. OA represent a major cause of impairment and disability among the elderly community. Objective of this study to find of comparative effect of mechanical knee traction versus IFT on pain and functional disability in patients with knee arthritis.30 patients with knee arthritis were allocated into 2 groups. Group A was given mechanical knee traction and conventional therapy. Group B was given IFT and conventional therapy. Visual analogue scale (VAS) was used to assess knee pain and western Ontario and McMaster universities osteoarthritis index used to measure physical function (WOMAC). Treatment was given for 7 days. Data was analysed by using SPSS software version 20. Within group there was significant improvement seen by Wilcoxon signed rank test and Between groups no significant difference using mannwhitney U test and VAS (Z=-0.832, p=-.403) and WOMAC (Z=-.727, p=-.467). result of this study says that mechanical knee traction and IFT both are equally effective in reducing pain and improving physical function in patients with knee osteoarthritis.
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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) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".