Long Term Bisphosphonate Use in Osteoporotic Patients; A Step Forward, Two Steps Back
Bibliographic record
Abstract
PURPOSE: Bisphosphonates are the main class of drugs widely used in prevention and treatment of osteoporosis. Along with the beneficial effects, recent studies point to the harms of long-term treatment with bisphosphonates. METHODS: The most relevant articles reporting serious adverse effects of bisphosphonates were selected and reviewed with the aim of assessing the risk-benefit of bisphosphonates. We searched PubMed, Web of Science, and Scopus using keywords bisphosphonates, risk of fracture, atrial fibrillation, osteonecrosis jaw, esophageal cancer, and adverse effects with no time limitation. We limited our s research to English articles. RESULTS: Our review shows that bisphosphonates reduce vertebral fractures in short term use while in long-term can cause osteonecrosis jaw, esophageal cancer, atrial fibrillation, and increase the risk of atypical fractures and probably adynamic bone disease. There is no consensus on the time limitation of bisphosphonate usage or its long term adverse effects. Thus, more studies on long-term side effects of bisphosphonates are highly recommended. In addition, new approaches for prevention and treatment of osteoporosis seem necessary. CONCLUSION: Prescribers should act cautionary and consider full assessment of risk-benefit and the duration of treatment.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".