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Record W4226218064

The Impact of Age and Sex Concordance Between Patients and Physicians on Medication Adherence: A Population-Based Study

2022· article· en· W4226218064 on OpenAlexaffabout
Shenzhen Yao, Lisa M. Lix, Gary Teare, Charity Evans, David Blackburn

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2022
Typearticle
Languageen
FieldMedicine
TopicMedication Adherence and Compliance
Canadian institutionsAlberta Health ServicesUniversity of ManitobaUniversity of Saskatchewan
Fundersnot available
KeywordsConcordanceMedicineConfoundingLogistic regressionPopulationDemographyInternal medicineOdds ratioStatinRetrospective cohort studyCohortGeneralized estimating equationEnvironmental health
DOInot available

Abstract

fetched live from OpenAlex

Shenzhen Yao,1 Lisa Lix,2 Gary Teare,3 Charity Evans,1 David Blackburn1 1College of Pharmacy and Nutrition, University of Saskatchewan, Saskatoon, Saskatchewan, Canada; 2Department of Community Health Sciences of Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada; 3Program Program Knowledge, Evidence and Innovation, Provincial Population and Public Health, Alberta Health Services, Calgary, Alberta, CanadaCorrespondence: David BlackburnCollege of Pharmacy and Nutrition, University of Saskatchewan, 2A20.01 Health Sciences Building, 107 Wiggins Road, Saskatoon, Saskatchewan, S7N5E5, CanadaTel +1 306 966 2081Fax +1 306 966 6377Email d.blackburn@usask.caPurpose: Age or sex concordance (same sex or same age range) may also be associated with medication adherence but was not fully investigated. We aim to quantify the impact of age and sex concordance on optimal adherence to statin medications.Patients and Methods: A retrospective cohort study was conducted using population-based health administrative data from Saskatchewan, Canada. Participants were individuals newly initiated on statin medications between January 1, 2012, and December 31, 2017. The outcome was optimal adherence (proportion of days covered ≥ 80%) measured at one year after the first statin claim. The independent variables were sex and age concordance (age within five years) between patients and prescribers. The association between adherence outcome and sex/age concordance was analyzed by multivariable logistic regression models using generalized estimating equations controlled by a package of potential confounding factors.Results: Among 51,874 new statin users, 20.6% (n = 10,710) were age concordant with prescriber. The vast majority of age concordance occurred in patients younger than 66 years (88.6%, 9,486/10,710). Sex concordance was observed in 62.8% (n = 32,551) of patients and age-sex combined concordance in 13.2% (n = 6,856). Among patients younger than 66 years (n = 36,641/51,874, 70.6%), age concordance did not have a significant impact on optimal adherence [adjusted OR (aOR) = 1.02, 95% CI 0.97 to 1.07]. Weak association between sex concordance (aOR = 1.05, 95% CI 1.00 to 1.11), and age-sex combined concordance (aOR = 1.05, 95% CI 0.99 to 1.12) was observed.Conclusion: Age and sex concordance were not statistically significant predictors of optimal statin adherence. However, a weak association was detected for sex concordance. Future studies should examine this factor in different health care settings.Keywords: medication adherence, age concordance, sex concordance, statin, observational study, cohort

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)0.003
metaresearch head score (Gemma)0.007
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 score0.161
Threshold uncertainty score0.320

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.224
GPT teacher head0.558
Teacher spread0.334 · 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

Citations5
Published2022
Admission routes2
Has abstractyes

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