Clinical effect of intramuscular calcitonin compared with oral celecoxib in the treatment of knee bone marrow lesions: a retrospective study
Bibliographic record
Abstract
BACKGROUND: Bone marrow lesions (BMLs) are a common finding in patients with osteoarthritis (OA), which are predictors of progression and pain related to cartilage damage in OA. The objective of the present research was to compare the short-term clinical effect of intramuscular calcitonin and oral celecoxib in treating knee BMLs. PATIENTS AND METHODS: Between January 2016 and December 2018, the medical records of patients with knee BMLs treated by intramuscular calcitonin or oral celecoxib were reviewed. Visual analog scale (VAS) and the Western Ontario and McMaster University Osteoarthritis Index (WOMAC) were used to assess knee pain and function, respectively. BMLs were assessed by MRI scans and were scored by the modified Whole-Organ MRI Score (WORMS). The safety of these two medications was also evaluated. RESULTS: A total of 123 eligible patients who received calcitonin treatment (n = 66) or celecoxib treatment (n = 57) were included. All patients were followed up clinically and radiographically for 3 months. The VAS and WOMAC scores were lower statistically in calcitonin group than celecoxib group at 4-week and 3-month follow-up. For BMLs, the WORMS scores in the calcitonin group were significantly lower than the celecoxib group. Besides, statistically higher MRI improvement rates were found in the calcitonin group compared with the celecoxib group at 4-week follow-up (21.21% vs. 7.01%; P = 0.039) and 3-month follow-up (37.88% vs. 15.79%; P = 0.006). CONCLUSION: Intramuscular calcitonin 50 IU once daily demonstrated a better short-term effect for knee BML patients compared with oral celecoxib 200 mg twice per day.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".