MétaCan
Menu
Back to cohort
Record W2074889935 · doi:10.2147/ppa.s3494

Treatment of postmenopausal osteoporosis, patient perspectives – focus on once yearly zoledronic acid

2009· article· en· W2074889935 on OpenAlexaffabout
Raj Carmona

Bibliographic record

VenuePatient Preference and Adherence · 2009
Typearticle
Languageen
FieldMedicine
TopicBone health and treatments
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineZoledronic acidOsteoporosisFracture reductionBisphosphonateInternal medicineClinical trialSurgery

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.932
Threshold uncertainty score0.853

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.043
GPT teacher head0.301
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2009
Admission routes2
Has abstractyes

Explore more

Same venuePatient Preference and AdherenceSame topicBone health and treatmentsFrench-language works237,207