Caracterización de pacientes con gonartrosis de rodilla. Centro de Diagnóstico Integral "Concepción"
Bibliographic record
Abstract
Introduction: Gonarthrosis of the knee is a chronic inflammatory condition presents in patients over 40; obesity as risk factor is of increasing interest for health systems and according to World Health Statistics of the World Health Organization, Venezuela is the country of South America with the highest rates of this condition. Statistics of the National Institute of Nutrition of Venezuela show that Zulia rates are over the national average with 35% of obese. In the practice of Traumatology of La Canada Municipality we have observed a high incidence of patients with overweight and it stimulated us to do the present study. Objective: to characterize the patients with Gonarthrosis of knee those were attended in the CDC. Material and Methods: a descriptive transversal study was conducted in the CDC of La Canada de Urdaneta Municipality, Zulia Province, Venezuela from January 2012 to December 2014 with a sample of 360 patients out of a universe of 6740. Results: the lowest age was 35 years and the highest 93, mean 55.5 years. 86.6% were female and half of the patients had family history of osteoarthritis of the knee, while 93% were overweight. Chief complain of 60% of the patients was pain for one year or less. 49 % of the cases showed severe to moderate X ray signs as well as decrease of the muscular force of lower limbs in 71% of the patients. Conclusions : the risk factor most influenced was increased BMI in patients with Gonarthrosis. Keywords: gonarthrosis of the knee, risk factors, obesity, body mass index.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".