MétaCan
Menu
Back to cohort
Record W2163232672 · doi:10.1002/clc.22032

Statin and Aspirin Therapy for the Prevention of Cardiovascular Events in Patients With Type 2 Diabetes Mellitus

2012· review· en· W2163232672 on OpenAlexfundaboutno aff
Jacob A. Udell, Benjamin M. Scirica, Eugene Braunwald, Itamar Raz, Philippe Gabríel Steg, Jaime A. Davidson, Boaz Hirshberg, Deepak L. Bhatt

Bibliographic record

VenueClinical Cardiology · 2012
Typereview
Languageen
FieldMedicine
TopicLipoproteins and Cardiovascular Health
Canadian institutionsnot available
FundersServierSanofiBayer HealthCareDuke Clinical Research InstituteNovo NordiskTeva Pharmaceutical IndustriesMedicines CompanyEisaiBoston VA Research InstituteGilead SciencesCanadian Institutes of Health ResearchAmerican Heart AssociationEli Lilly and CompanyBristol-Myers SquibbAstraZeneca
KeywordsMedicineBristol-MyersFamily medicineManagementInternal medicine

Abstract

fetched live from OpenAlex

Abstract Patients with type 2 diabetes mellitus are at 2 to 4 times increased risk of cardiovascular events compared with those without diabetes, both among patients with multiple risk factors only and those with established atherothrombosis. In this review, we provide recommendations for the use of statins and aspirin for the prevention of cardiovascular events in high‐risk patients with diabetes mellitus. Clin. Cardiol. 2012 doi: 10.1002/clc.22032 The SAVOR‐TIMI 53 trial is sponsored by AstraZeneca and Bristol‐Myers Squibb. Dr. Udell is a recipient of a Postdoctoral Research Fellowship from the Canadian Institutes for Health Research (CIHR) and Canadian Foundation for Women's Health. Dr. Scirica receives research grants from AstraZeneca, Bristol‐Myers Squibb, Merck, Johnson & Johnson, Bayer Healthcare, and Gilead Sciences and consultancy fees from Gilead Sciences, Lexicon, and Arena Pharmaceuticals. Dr. Braunwald receives research grants from AstraZeneca and Bristol‐Myers Squibb. Dr. Raz has received honoraria/expenses for advisory board participation from AstraZeneca, Bristol‐Myers Squibb, Novo Nordisk, Merck, Sharp & Dohme, and Eli Lilly; has served as a consultant for Andromea, AstraZeneca, Bristol‐Myers Squibb, Eli Lilly, Johnson & Johnson, HealOr, Insuline, Teva, and TransPharma; and has participated in speakers bureaus for AstraZeneca, Bristol‐Myers Squibb, Eli Lilly, Novo Nordisk, Johnson & Johnson, and Roche. Dr. Steg receives research grants from Servier. Dr. Davidson participated on advisory panels for AstraZeneca, Bristol‐Myers Squibb, Merck, Johnson & Johnson, Boehringer Ingelheim, Eli Lilly, Generex Biotechnology, Novo Nordisk A/S, Roche Diagnostics, and Takeda Pharmaceutical Company and participated in speaker's bureaus for Eli Lilly and Takeda Pharmaceutical Company. Dr. Hirshberg is an employee of and holds stock in AstraZeneca. Dr. Bhatt discloses the following relationships—Advisory Board: Medscape Cardiology; Board of Directors: Boston VA Research Institute, Society of Chest Pain Centers; Chair: American Heart Association Get With The Guidelines Science Subcommittee; Honoraria: American College of Cardiology (Editor, Clinical Trials, Cardiosource), Duke Clinical Research Institute (clinical trial steering committees), Slack Publications (Chief Medical Editor, Cardiology Today Intervention), WebMD (CME steering committees); Research Grants: Amarin, AstraZeneca, Bristol‐Myers Squibb, Eisai, Ethicon, Medtronic, Sanofi Aventis, The Medicines Company; Unfunded Research: FlowCo, PLx Pharma, Takeda. The design and conduct of the SAVOR‐TIMI 53 study are being done by the academic executive committee in collaboration with the sponsors.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.097
GPT teacher head0.389
Teacher spread0.292 · 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 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

Citations24
Published2012
Admission routes2
Has abstractyes

Explore more

Same venueClinical CardiologySame topicLipoproteins and Cardiovascular HealthFrench-language works237,207