Prevalence of Knee Osteoarthritis and Analysis of Pain, Rigidity, and Functional Incapacity
Bibliographic record
Abstract
Knee osteoarthritis is one of the most prevalent health problems in our society. It accounts for 10% of all primary care visits in general medicine and 30% of outpatient appointments. The objectives of this cross-sectional descriptive study of 100 patients suffering from gonarthritis were to assess pain, functional capacity, and joint damage in patients diagnosed with knee osteoarthritis, as well as the possible repercussions for subsequent surgical treatment. Sociodemographic, clinical, and radiological data were collected, and pain and functional capacity were evaluated by using the Western Ontario and McMaster Universities Osteoarthritis Index. The majority (71) of patients were women, mean age 71 years (SD=7.84), of low educational (66%) and financial (89%) status, with mean disease duration of 11.8 years. Of the total, 87% presented with comorbidity. Radiographs revealed a varus malalignment in 31% of patients and a valgus malalignment in 17%, with bone collapse in 39% of these. The factors that most affect surgery and subsequent rehabilitation are closely linked to social status, the general state of the patient, and the radiological severity of gonarthritis. Most of the patients were obese and suffered from comorbid conditions, and some presented with psychopathology. These factors may influence surgery, and thus improvements in primary care should be made as a way of offering a simpler and more effective treatment for gonarthritis.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".