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Prevalence, Predictors, and Outcomes of Primary Nonadherence After Acute Myocardial Infarction

2008· article· en· W1970485089 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCirculation · 2008
Typearticle
Languageen
FieldMedicine
TopicMedication Adherence and Compliance
Canadian institutionsUniversity Health NetworkInstitute for Clinical Evaluative SciencesWestern University
Fundersnot available
KeywordsMedicineMyocardial infarctionInternal medicinePrimary careEmergency medicineCardiologyIntensive care medicineFamily medicine

Abstract

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BACKGROUND: Secondary prevention after acute myocardial infarction (AMI) is achieved primarily through medications. However, patients must take their medications to benefit. Medication adherence research has focused primarily on continuation of medications rather than not filling the first prescription written (primary nonadherence). Our objectives were to characterize, to determine factors of, and to measure outcomes associated with primary nonadherence after AMI. METHODS AND RESULTS: We conducted a population-based cohort study using an AMI registry linked with administrative data in Ontario, Canada. The primary outcome was 1-year mortality. There were 4591 post-AMI patients >65 years of age included with 12 832 prescriptions written, of which 73% and 79% were filled within 7 and 120 days, respectively. By 120 days after discharge, more cardiac than noncardiac prescriptions were filled (82% versus 35%, respectively; P<0.0001). Only 74% of patients filled all their discharge prescriptions by 120 days after discharge after the exclusion of acetylsalicylic acid, which is also available over the counter in Ontario. Factors associated with filling all compared with filling no discharge prescriptions included younger age, low income, discharge medication counseling, in-hospital attending cardiologist, and fewer medications before AMI. The adjusted 1-year mortality rate was higher in patients who filled some versus all (odds ratio, 1.44; 95% confidence interval, 1.15 to 1.79; P=0.001) and none versus all (odds ratio, 1.80; 95% confidence interval, 1.35 to 2.42; P<0.0001) of their discharge medications. CONCLUSIONS: Patients fill most of their discharge prescriptions within 1 week after AMI. The 1-year mortality rate was higher for those patients who did not fill all of their discharge medications after AMI. Factors such as discharge medication counseling and postdischarge follow-up may help to increase the filling rate of medications after AMI.

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.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.358

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 head0.023
GPT teacher head0.262
Teacher spread0.239 · 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