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Record W2075578416 · doi:10.1001/archinte.161.2.183

Use of the Statins in Patients After Acute Myocardial Infarction

2001· article· en· W2075578416 on OpenAlexaffabout
Cynthia A. Jackevicius, George Anderson, Lawrence A. Leiter, Jack V. Tu

Bibliographic record

VenueArchives of Internal Medicine · 2001
Typearticle
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsToronto General HospitalUniversity Health Network
Fundersnot available
KeywordsPravastatinMedicineSimvastatinStatinMyocardial infarctionInternal medicineCardiologyCholesterol

Abstract

fetched live from OpenAlex

OBJECTIVE: To compare the use of lipid-lowering agents in 42 628 elderly patients (aged > or =65 years) after acute myocardial infarction, before and after the publication of the Scandinavian Simvastatin Survival Study (4S), using the Ontario Myocardial Infarction Database. METHODS: Multivariate regression models were created to estimate changes in the rate of statin use over time in monthly cohorts of elderly patients after acute myocardial infarction in Ontario from April 1, 1992, to March 31, 1997. Changes in the rate of statin use over time were estimated using patient and prescriber characteristics. RESULTS: We found a 3.6-fold significant increase in the monthly rate of statin use after the publication of 4S compared with before the publication of 4S (P<.001); specifically, the rate of increase in simvastatin and pravastatin sodium use was higher after the publication of 4S (P<.001 for each). Before the publication of 4S, the rate of increase in statin use in younger patients (aged 65-74 years) was 2.7 times higher than in older patients (aged > or =75 years) (P =.02), while after the publication of 4S, the rate of increase in statin use was only 1.8-fold higher in the younger group (P<.001). After the publication of 4S, there was a 1.6-fold higher rate of increase in statin use in male compared with female patients (P =.006). Also after the publication of 4S, specialists (cardiologists and internists) had a 2-fold higher rate of increased use of the statins than did generalists (P<.001). CONCLUSION: It is possible to shift practice if the evidence of benefit is strong, the intervention is easy to implement, and the intervention is marketed aggressively.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.289

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 head0.011
GPT teacher head0.256
Teacher spread0.245 · 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 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

Citations64
Published2001
Admission routes2
Has abstractyes

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