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Record W4387610418 · doi:10.46747/cfp.6910701

Lipid-lowering therapies for cardiovascular disease prevention and management in primary care

2023· review· en· W4387610418 on OpenAlexaffvenue
Nicolas Dugré, Adrienne J. Lindblad, Danielle Perry, G. Michael Allan, Émélie Braschi, Jamie Falk, Liesbeth Froentjes, Scott Garrison, Jessica Kirkwood, Christina Korownyk, James McCormack, Samantha S. Moe, Allison Paige, Jen Potter, Betsy Thomas, Joey Ton, Jennifer Young, Justin Weresch, Michael R. Kolber

Bibliographic record

VenueCanadian Family Physician · 2023
Typereview
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsMcMaster UniversityDoug Bragg Enterprises (Canada)University of ManitobaÉlisabeth Bruyère HospitalUniversity of British ColumbiaCollege of Family Physicians of CanadaUniversity of AlbertaCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal
Fundersnot available
KeywordsMedicineEzetimibeSystematic reviewInternal medicineAdverse effectRelative riskMaceInterquartile rangeStatinCochrane LibraryRandomized controlled trialMeta-analysisIntensive care medicineMEDLINEConfidence intervalMyocardial infarctionPercutaneous coronary intervention

Abstract

fetched live from OpenAlex

OBJECTIVE: To assess the benefits and harms of lipid-lowering therapies used to prevent or manage cardiovascular disease including bile acid sequestrants (BAS), ezetimibe, fibrates, niacin, omega-3 supplements, proprotein convertase subtilisin-kexin type 9 (PCSK9) inhibitors, and statins. DATA SOURCES: MEDLINE, the Cochrane Database of Systematic Reviews, and a grey literature search. STUDY SELECTION: Systematic reviews of randomized controlled trials published between January 2017 and March 2022 looking at statins, ezetimibe, PCSK9 inhibitors, fibrates, BAS, niacin, and omega-3 supplements for preventing cardiovascular outcomes were selected. Outcomes of interest included major adverse cardiovascular events (MACE), cardiovascular mortality, all-cause mortality, and adverse events. SYNTHESIS: A total of 76 systematic reviews were included. Four randomized controlled trials were also included for BAS because no efficacy systematic review was identified. Statins significantly reduced MACE (6 systematic reviews; median risk ratio [RR]=0.74; interquartile range [IQR]=0.71 to 0.76), cardiovascular mortality (7 systematic reviews; median RR=0.85, IQR=0.83 to 0.86), and all-cause mortality (8 systematic reviews; median RR=0.91, IQR=0.88 to 0.92). Major adverse cardiovascular events were also significantly reduced by ezetimibe (3 systematic reviews; median RR=0.93, IQR=0.93 to 0.94), PCSK9 inhibitors (14 systematic reviews; median RR=0.84, IQR=0.83 to 0.87), and fibrates (2 systematic reviews; mean RR=0.86), but these interventions had no effect on cardiovascular or all-cause mortality. Fibrates had no effect on any cardiovascular outcomes when added to a statin. Omega-3 combination supplements had no effect on MACE or all-cause mortality but significantly reduced cardiovascular mortality (5 systematic reviews; median RR=0.93, IQR=0.93 to 0.94). Eicosapentaenoic acid ethyl ester alone significantly reduced MACE (1 systematic review, RR=0.78) and cardiovascular mortality (2 systematic reviews; RRs of 0.82 and 0.82). In primary cardiovascular prevention, only statins showed consistent benefits on MACE (6 systematic reviews; median RR=0.75, IQR=0.73 to 0.78), cardiovascularall-cause mortality (7 systematic reviews, median RR=0.83, IQR=0.81 to 0.90), and all-cause mortality (8 systematic reviews; median RR=0.91, IQR=0.87 to 0.91). CONCLUSION: Statins have the most consistent evidence for the prevention of cardiovascular complications with a relative risk reduction of about 25% for MACE and 10% to 15% for mortality. The addition of ezetimibe, a PCSK9 inhibitor, or eicosapentaenoic acid ethyl ester to a statin provides additional MACE risk reduction but has no effect on all-cause mortality.

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)0.014
metaresearch head score (Gemma)0.048
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.048
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.005
Bibliometrics0.0060.004
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.041
GPT teacher head0.290
Teacher spread0.248 · 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 designSystematic review
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

Citations18
Published2023
Admission routes2
Has abstractyes

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