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Record W2038005906 · doi:10.1097/mol.0b013e32833305a3

Polypill: the evidence and the promise

2009· review· en· W2038005906 on OpenAlexaff
Eva Lonn, Salim Yusuf

Bibliographic record

VenueCurrent Opinion in Lipidology · 2009
Typereview
Languageen
FieldMedicine
TopicMedication Adherence and Compliance
Canadian institutionsHamilton Health SciencesPopulation Health Research InstituteMcMaster University
FundersWellcome Trust
KeywordsPolypillMedicinePharmacologyIntensive care medicineTraditional medicineInternal medicineAspirin

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: In spite of great scientific advances, cardiovascular disease is the commonest cause of death worldwide and current cardiovascular prevention strategies fail to achieve the full potential of risk modification. A large amount of evidence supports the use of pharmacological treatments both in primary and secondary prevention and it was hypothesized that a fixed-dose combination of such drugs, a 'polypill', may greatly simplify and improve current prevention strategies. RECENT FINDINGS: Several polypill formulations have been developed and a recent trial demonstrated the short-term feasibility, safety and efficacy (in reducing risk factor levels) of a polypill in individuals at moderate risk. Many challenges remain and studies are underway, which will address questions related to formulation of polypill(s), the long-term safety and tolerability, the efficacy in reducing risk factor levels and cardiovascular events, physician, patient and societal acceptability, adherence, regulatory requirements, cost and impact on lifestyle habits. SUMMARY: Theoretical models suggest that a polypill containing low-dose aspirin, three blood pressure-lowering drugs at half dose and a potent statin, administered to a large proportion of the population at risk for cardiovascular events, could reduce ischemic heart disease and strokes by over 80%. The feasibility of this approach has recently been shown in a clinical trial and ongoing studies will define whether the postulated benefits of the polypill will be observed.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.910
Threshold uncertainty score0.449

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.370
GPT teacher head0.499
Teacher spread0.129 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations21
Published2009
Admission routes1
Has abstractyes

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