Treatment of postmenopausal osteoporosis, patient perspectives – focus on once yearly zoledronic acid
Bibliographic record
Abstract
Treatment of postmenopausal osteoporosis, patient perspectives – focus on once yearly zoledronic acid Raj Carmona, Rick AdachiDivision of Rheumatology Department of Medicine, McMaster University, Hamilton, Ontario, CanadaAbstract: Oral bisphosphonates are of proven efficacy in preventing fractures in postmenopausal osteoporosis. However, poor adherence limits their real-world efficacy and clinical utility. Zoledronic acid (ZOL) is a potent bisphosphonate administered by annual intravenous infusion, effectively ensuring adherence to therapy over the following year. According to available data, 66% to 79% of patients have expressed a preference for ZOL over oral bisphosphonates. This is likely to lead to enhanced clinical outcomes, although long-term (repeat annual) adherence is currently unknown. ZOL is of proven efficacy, with hip fracture reduction of 41% and morphometric vertebral fracture reduction of 70% over 3 years in the HORIZON PFT trial. It has demonstrated a good side-effect profile with postinfusion flu-like symptoms being the most common. Additionally, it has been associated with decreased mortality in patients following surgery for hip fracture. There is no clear association between exposure and the rate of serious or nonserious atrial fibrillation. We review adherence to oral bisphosphonates, and the pharmacokinetics, efficacy, safety, and patient preference for ZOL.Keywords: zoledronic acid, bisphosphonate, osteoporosis, fractures
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".