Frequency of Grade (III) Knee Osteoarthritis (OA) Among Women in Lahore Pakistan
Bibliographic record
Abstract
Objective: To determine Grade (III) Knee Osteoarthritis (OA) among Women in Lahore Pakistan.Study Design: Cross sectional study.Place and Duration of Study: Kannan physiotherapy and spine clinic.6 months(November 2020-April 2021).Methods:Sample size of this study was100. Inclusion Criteria is Females with Grade (III) knee osteoarthritis age from 55-70 years were included. And Exclusion criteria is females with the history of malignancy and the females who did not give us the consent were excluded. Convenient Sampling technique was used.The data was collected by using The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Data was analyzed by using SPSS version 21. Results: According to the results of this study the mean age of participants were 53.8+ 6.024. Out of 100 participants (11)11%marked that they feel no pain while walking. (13)13%marked slight pain(25)25%marked moderate pain(24)24%marked very pain(27)27%marked extreme pain while walking. Out of 100 participants (12)12%marked that they feel no pain while stair climbing.(13)13%marked slight pain(24)24%marked moderate pain(25)25%marked very pain(26)26%marked extreme pain while stair climbing. Conclusion:This research concluded that the frequency of knee pain among women was very high. Due to this knee pain many daily life activities including rising from the bed, lying in the bed, using toilet or bending on the floor. Many light and heavy domestic duties of women were also affected due to knee pain.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".