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Record W1955943376 · doi:10.1002/jbmr.2271

Risk of Osteoporotic Fractures With Angiotensin II Receptor Blockers Versus Angiotensin-Converting Enzyme Inhibitors in Hypertensive Community-Dwelling Elderly

2014· article· en· W1955943376 on OpenAlexafffundabout
Debra A. Butt, Muhammad Mamdani, Tara Gomes, Lisa M. Lix, Hong Lu, Karen Tu

Bibliographic record

VenueJournal of Bone and Mineral Research · 2014
Typearticle
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsToronto Western HospitalUniversity of ManitobaInstitute for Clinical Evaluative SciencesSt. Michael's HospitalThe Scarborough HospitalMuscular Dystrophy CanadaUniversity of Toronto
FundersCanadian Institutes of Health ResearchDepartment of Family and Community Medicine, University of TorontoUniversity of TorontoOntario Ministry of Health and Long-Term CareInstitute for Clinical Evaluative Sciences
KeywordsMedicineHazard ratioInternal medicineACE inhibitorPropensity score matchingAngiotensin-converting enzymeOsteoporosisPopulationSurgeryConfidence interval

Abstract

fetched live from OpenAlex

Angiotensin-converting enzyme (ACE) inhibitors and angiotensin II receptor blockers (ARBs) are used to treat hypertension; however, in vivo and clinical studies suggest that ARBs and ACE inhibitors may exert different effects on bone. The association between long-term use of ARBs and ACE inhibitors and fracture requiring medical attention is limited. We conducted a population-based, retrospective cohort study with propensity score matching using administrative databases in Ontario, Canada, to examine the risk of osteoporosis-related fractures in hypertensive elderly treated with ARBs versus ACE inhibitors. We identified a cohort of newly treated hypertensive patients aged 66 years and older who initiated an ACE inhibitor from May 1, 2004, to March 31, 2012, and matched them to ARB users on propensity score, sex, and age at drug initiation. The primary outcome was hip fracture, and secondary outcomes were non-hip major osteoporotic fractures (other femoral, clinical vertebral, forearm, wrist, humerus) and other osteoporotic fractures (pelvis, clavicle, patella, shoulder, upper arm, tibia, fibula, ankle, scapula, ribs, sternum, trunk). We calculated hazard ratios (HRs) using Cox proportional hazards model with robust standard errors. Of the 87,635 patients who initiated treatment, 28,819 (32.9%) started ARBs and 58,816 (67.1%) started ACE inhibitors. Among new ARB users, 27,815 (96.5%) were successfully matched to ACE inhibitor users. Without dose adjustment, no significant association was observed for ARBs relative to ACE inhibitor users for hip fractures (HR = 0.88; 95% confidence interval [CI] 0.70-1.11), with a decreased risk of other major osteoporotic fractures (HR = 0.81; CI 0.70-0.93) and no significant association for other osteoporotic fractures (HR = 0.88; CI 0.74-1.05). When adjusted for dosage, there was no significant difference between the effects of ARBs and ACE inhibitors on hip (HR = 0.99; CI 0.78-1.25), other major osteoporotic (HR = 0.87; CI 0.75-1.01), and other osteoporotic fractures (HR = 0.90; CI 0.74-1.08).

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.153

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.039
GPT teacher head0.339
Teacher spread0.299 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations24
Published2014
Admission routes3
Has abstractyes

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