A Study on efficacy of different Therapeutic Modalities to Alleviate Pain due to Knee Osteoarthritis
Bibliographic record
Abstract
Introduction: Physiotherapy is one of the recommended non pharmacological management options in patients with osteoarthritis.Ultrasound & Pulsed electromagnetic energy(PEME) & Exercises are widely used in to treat pain due to osteoarthritis. Aims& Objectives: The purpose of the study was an effort to find out the role of different modalities (Therapeutic ultrasound, PEME , Exercises) to control the pain in osteoarthritis of knee. Study design & Methodology: The study was experimental, pre & post design. 60 female osteoarthritis patients including those suffering from bilateral osteoarthritis between age group 40- 65 years from the Department of Physiotherapy and Department of Orthopedics, PGIMER, Chandigarh were chosen for the study & randomly distributed in 3 groups. Electrotherapy modalities were administered for Group A (PEME) and Group B (Ultrasound) three times weekly for 6 weeks. The exercises & hot water fomentation were carried daily for all the three groups (Group A, Group B & Group C). The severity of knee pain was evaluated by Visual Analog Scale (VAS) in a weight bearing position (walking or standing) in parallel bars. Western Ontario McMaster universities (WOMAC) index of osteoarthritis was used to assess pain, stiffness, and physical function. SPSSVersion17 was used for statistical analysis. Conclusion: It is concluded that all the therapies administered (pulsed electromagnetic energy, therapeutic ultrasound, exercises) help to reduce pain in knee osteoarthritis but none of the modality proved more effective than others.
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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) | 0.004 | 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".