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Record W2396616515

Combination Pharmacotherapy to Prevent Cardiovascular Disease: Present Status and Challenges

2013· article· en· W2396616515 on OpenAlexaff
Salim Yusuf, Amir Attaran, Jackie Bosch, Philip Joseph, Eva Lonn, Tara McCready, Andrew Mente, Robby Nieuwlaat, Prem Pais, Anthony Rodgers, JD Schwalm, Richard P. Smith, Koon Hoo Teo, Denis Xavier

Bibliographic record

VenueSSRN Electronic Journal · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicPharmaceutical Economics and Policy
Canadian institutionsUniversity of OttawaHamilton Health SciencesMcMaster UniversityPopulation Health Research Institute
Fundersnot available
KeywordsPillMedicineTolerabilityPolypillIntensive care medicineCombination therapyPharmacotherapyAspirinDiseaseStatinPharmacologyInternal medicineAdverse effect
DOInot available

Abstract

fetched live from OpenAlex

Combination pills containing aspirin,multiple blood pressure (BP) lowering drugs, and a statin have demonstrated safety, substantial risk factor reductions, and improved medication adherence in the prevention of cardiovascular disease (CVD). The individual medications in combination pills are already recommended for use together in secondary CVD prevention. Therefore, current information on their pharmacokinetics, impact on the risk factors, and tolerability should be sufficient to persuade regulators and clinicians to use fixed-dose combination pills in high-risk individuals, such as in secondary prevention. Long-term use of these medicines, in a poly pill or otherwise, is expected to reduce CVD risk by at least 50–60% in such groups. This risk reduction needs confirmation in prospective randomized trials for populations for whom concomitant use of the medications is not currently recommended (e.g.primary prevention). Given their additive benefits, the combined estimated relative risk reduction (RRR) in CVD from both lifestyle modification and a combination pill is expected to be 70–80%. The first of several barriers to the widespread use of combination therapy in CVD prevention is physician reluctance to use combination pills. This reluctance may originate from the belief that lifestyle modification should take precedence, and that medications should be introduced one drug at a time, instead of regarding combination pills and lifestyle modification as complementary and additive. Second, widespread availability of combination pills is also impeded by the reluctance of large pharmaceutical companies to invest in development of novel co-formulations of generic (or ‘mature’) drugs.A business model based on ‘mass approaches’ to drug production, packaging, marketing, and distribution could make the combination pill available at an affordable price, while at the same time providing a viable profit for the manufacturers.A third barrier is regulatory approval for novel multidrug combination pills, as there are few precedents for the approval of combination products with four or more components for CVD. Acceptance of combination therapy in other settings suggests that with concerted efforts by academics, international health agencies, research funding bodies, governments, regulators, and pharmaceutical manufacturers, combination pills for prevention of CVD in those with disease or at high risk (e.g. those with multiple risk factors) can be made available worldwide at affordable prices. It is anticipated that widespread use of combination pills with lifestyle modifications can lead to substantial risk reductions (as much as an 80% estimated RRR) in CVD.Heath care systems need to deploy these strategies widely, effectively, and efficiently. If implemented, these strategies could avoid several millions of fatal and non-fatal CVD events every year worldwide.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.383
Threshold uncertainty score0.628

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.038
GPT teacher head0.270
Teacher spread0.232 · 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 designTheoretical or conceptual
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

Citations21
Published2013
Admission routes1
Has abstractyes

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