Calcitonin Injection and Functional Status of Females With Knee Osteoarthritis
Bibliographic record
Abstract
Background: Osteoarthritis (OA) is one of the most common diseases of both bone and cartilage. Since calcitonin may have positive effect on both of them. Objectives: The current study aimed to evaluate the effect of weekly calcitonin injection on patients with knee osteoarthritis using Western Ontario and McMaster universities arthritis index (WOMAC) questionnaire. Methods: The current prospective cross sectional study, randomly recruited 28 eligible female participants aged 55 - 70 from outpatients referred to rehabilitation clinics. These patients were in stages II and III based on Kellgren-Lawrence grading scale. Patients were requested to fill out the multidimensional WOMAC questionnaire on the day of enrollment into the study (baseline examination) and five weeks after completion of their treatment with calcitonin. Paired T-test was used to assess mean differences of the questionnaire. Results: Compared to baseline, significant improvement in WOMAC score was observed after five weeks of treatment. Pain, joint stiffness, functional activity and total score of WOMAC showed improvement of 80.6%, 25.3%, 41.9% and 47.91% respectively, which were statistically significant (P value < 0.001). Pain, activity and stiffness improved respectively according to the mean differences and confidence interval. Conclusions: The study results showed that calcitonin can provide proper outcomes such as increased locomotor activity. Although WOMAC parameters increased in all age groups, it had great effect just on 55 - 60 years age group. Therefore, improvement of quality of life and proper rehabilitation, which are the main factors in osteoarthritis patients, were almost achieved in this study.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".