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Record W1984309459 · doi:10.1177/1479164109360593

Adherence to vascular protection drugs in diabetic patients in Quebec: a population-based analysis

2010· article· en· W1984309459 on OpenAlexaffabout
Shabnam Asghari, Josiane Courteau, Catherine Drouin, Jean‐Pierre Grégoire, André C. Carpentier, Mariane Pâquet, Alain Vanasse

Bibliographic record

VenueDiabetes and Vascular Disease Research · 2010
Typearticle
Languageen
FieldMedicine
TopicMedication Adherence and Compliance
Canadian institutionsUniversité de MontréalUniversité de SherbrookeUniversité Laval
Fundersnot available
KeywordsMedicineDiabetes mellitusInternal medicineCohortLogistic regressionPopulationMultivariate analysisEnvironmental healthEndocrinology

Abstract

fetched live from OpenAlex

The purpose of this study was to assess adherence to vascular protection drugs in diabetic patients using a cohort of diabetic patients aged >or=30 years, covered by the public drug insurance in the province of Quebec, excluding gestational diabetes and patients who were hopitalized or died during the 1-year follow-up. Drug adherence was measured using the medication possession ratio. Multivariate analyses, including logit and multinomial logit were used. Of the 170,381 diabetics (mean age: 62 +/- 14 years), 18% and 32% were regular users of ASA and ACEIs/ARBs, respectively. Regular use increased with age (p<0.0001) and comorbidities (p<0.0001). Rural inhabitants were more likely to use ACEIs/ARBs (OR: 1.29; 95% CI: 1.26-1.32) and to be regular users (OR: 1.36; 95% CI: 1.32-1.39). Similar results were found for ASA. In conclusion, despite the high cardiovascular risks associated with diabetes, less than one-third of diabetic adults took vascular-protection drugs regularly. This important issue needs proper attention.

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 score0.166
Threshold uncertainty score0.333

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.030
GPT teacher head0.335
Teacher spread0.305 · 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

Citations7
Published2010
Admission routes2
Has abstractyes

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