TITLE: Calcitonin Nasal Spray for the Treatment of Fracture Pain: A Review of Clinical and Cost- Effectiveness
Bibliographic record
Abstract
Pain resulting from fractures, such as vertebral fractures and hip fractures may be treated with a wide variety of medications. These medications include acetaminophen (with or without codeine), non-steroidal anti-inflammatory drugs (NSAIDs), sedative hypnotics, and opioids. 1,2 However, these analgesics may pose risks due to adverse effects. NSAIDs have been associated with renal and gastrointestinal toxicities. 1,3 Opioids may cause constipation and psychological side-effects. 3 Patients and physicians may oppose the use of these medications as well. 3 The potential for drug abuse and interactions with standard analgesics is a serious risk. 1,3 In addition, standard analgesics may not be helpful for alleviating pain from vertebral compression fractures. 2 Calcitonin is a peptide hormone secreted by the body in response to hypercalcemia. 1,4 Calcitonin has been recognized as a treatment for numerous diseases, which include Paget’s disease, and osteoporosis. 4,5 Calcitonin may help in treating osteoporosis along with easing fracture pain. 1 Calcitonin is available in Canada as recombinant salmon calcitonin, which has a higher analgesic potency and longer duration of action than human calcitonin. 1,6 In this document, salmon calcitonin will be referred to as calcitonin. Nasal spray calcitonin has been
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".