A case series studying the effect of low level laser therapy in osteoarthritis knee in elderly population of northeastern India
Bibliographic record
Abstract
Background: Osteoarthritis knee affects a large portion of the population and it is the leading cause of disability worldwide. The increase in life expectancy further added to the burden of the disease. Joint replacement surgery is in accessible to most people in this region. Our objective is to study the effectiveness of low level laser therapy in primary osteoarthritis knees in the north-eastern elderly population of India. Materials and methods: This is a prospective cohort study in 30 patients attending orthopaedic outpatient department with primary osteoarthritis knee. All selected patients including both male and female were managed with low level laser therapy (wavelength of 905 nm and a power that varies from 27 Wp to 100 Wp) for 4consecutive weeks. Scoring using WOMAC (Western Ontario and McMaster University Osteoarthritis Index) and VAS (Visual analog scale) were taken during first enrolment and then at 4 and 8 weeks of follow up. Results: There was a significant improvement in both WOMAC and VAS scores both at 4 weeks and 8 weeks of follow up. Improvement from baseline WOMAC mean score (enrolment 58.8, 79.36 at 4 weeks and 93.1 at 8 weeks (p
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".