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Record W4306850817 · doi:10.1016/j.ijcard.2022.10.132

External applicability of the Effect of ticagrelor on Health Outcomes in diabEtes Mellitus patients Intervention Study (THEMIS) trial: An analysis of patients with diabetes and coronary artery disease in the REduction of Atherothrombosis for Continued Health (REACH) registry

2022· article· en· W4306850817 on OpenAlexafffund
Jérémie Abtan, Deepak L. Bhatt, Yedid Elbez, Grégory Ducrocq, Shinya Goto, Sidney C. Smith, E. Magnus Ohman, Kim A. Eagle, Kim Fox, Robert A. Harrington, Lawrence A. Leiter, Shamir R. Mehta, Tabassome Simon, Ivo Petrov, Peter Sinnaeve, Prem Pais, Eli I. Lev, Héctor Bueno, Peter Wilson, Philippe Gabríel Steg

Bibliographic record

VenueInternational Journal of Cardiology · 2022
Typearticle
Languageen
FieldMedicine
TopicAntiplatelet Therapy and Cardiovascular Diseases
Canadian institutionsHamilton Health SciencesMcMaster UniversityPopulation Health Research InstituteSt. Michael's Hospital
FundersEsperion TherapeuticsInstitut ServierJapan Society for the Promotion of ScienceHLS TherapeuticsIdorsia PharmaceuticalsAssistance publique-Hôpitaux de ParisNakatani Foundation for Advancement of Measuring Technologies in Biomedical EngineeringDuke Clinical Research InstituteEisaiMinistry of Education, Culture, Sports, Science and TechnologyPfizerModernaRegado BiosciencesMedicines CompanyAstraZenecaAmarin CorporationIronwood Pharmaceuticals, IncorporatedNational Institutes of HealthRegeneron PharmaceuticalsFédération Française de CardiologieJapan Agency for Medical Research and DevelopmentBrigham and Women's HospitalBoston VA Research InstituteBoston Scientific CorporationEli Lilly and CompanyCleveland ClinicBristol-Myers SquibbCSL BehringBelvoir Media GroupNovo NordiskMyoKardiaDaiichi Sankyo EuropeServierGilead SciencesAmgenSt. Jude MedicalKowa CompanySanofiAmerican Heart Association
KeywordsMedicineCoronary artery diseaseDiabetes mellitusInternal medicinePopulationMyocardial infarctionConventional PCIPercutaneous coronary interventionCardiologyAspirinStroke (engine)TicagrelorEndocrinology

Abstract

fetched live from OpenAlex

AIMS: THEMIS is a double-blind, randomized trial of 19,220 patients with diabetes mellitus and stable coronary artery disease (CAD) comparing ticagrelor to placebo, in addition to aspirin. The present study aimed to describe the proportion of patients eligible and reasons for ineligibility for THEMIS within a population of patients with diabetes and CAD included in the Reduction of Atherothrombosis for Continued Health (REACH) registry. METHODS AND RESULTS: The THEMIS eligibility criteria were applied to REACH patients. THEMIS included patients ≥50 years with type 2 diabetes and stable CAD as determined by either a history of previous percutaneous coronary intervention, coronary artery bypass grafting, or documentation of angiographic stenosis of ≥50% of at least one coronary artery. Patients with prior myocardial infarction or stroke were excluded. In REACH, 10,156 patients had stable CAD and diabetes. Of these, 6515 (64.1%) patients had at least one exclusion criteria. From the remaining population, 784 patients did not meet inclusion criteria (7.7%) mainly due to absence of aspirin treatment (7.2%), yielding a 'THEMIS-eligible population' of 2857 patients (28.1% of patients with diabetes and stable CAD). The main reasons for exclusion were a history of myocardial infarction (53.1%), use of oral anticoagulation (14.5%), or history of stroke (12.9%). Among the 4208 patients with diabetes and a previous PCI, 1196 patients (28.4%) were eligible for inclusion in the THEMIS-PCI substudy. CONCLUSIONS: In a population of patients with diabetes and stable coronary artery disease, a sizeable proportion appear to be 'THEMIS eligible.' CLINICAL TRIAL REGISTRATION: http://www. CLINICALTRIALS: gov identifier: NCT01991795.

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)0.005
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.299
Teacher spread0.289 · 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 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

Citations2
Published2022
Admission routes2
Has abstractyes

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