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Record W2976166882 · doi:10.1056/nejmoa1908419

Ticagrelor with or without Aspirin in High-Risk Patients after PCI

2019· article· en· W2976166882 on OpenAlexafffund
Roxana Mehran, Usman Baber, Samin K. Sharma, David J. Cohen, Dominick J. Angiolillo, Carlo Briguori, Timothy Collier, George Dangas, Dariusz Dudek, Vladimír Džavík, Javier Escaned, Robert Gil, Paul A. Gurbel, Christian W. Hamm, Timothy D. Henry, Kurt Huber, Adnan Kastrati, Upendra Kaul, Ran Kornowski, Mitchell W. Krucoff, Vijay Kunadian, Steven O. Marx, Shamir R. Mehta, David J. Moliterno, E. Magnus Ohman, Keith G. Oldroyd, Gennaro Sardella, Samantha Sartori, Richard Shlofmitz, Philippe Gabríel Steg, Giora Weisz, Bernhard Witzenbichler, Yaling Han, Stuart Pocock, C. Michael Gibson

Bibliographic record

VenueNew England Journal of Medicine · 2019
Typearticle
Languageen
FieldMedicine
TopicAntiplatelet Therapy and Cardiovascular Diseases
Canadian institutionsHamilton Health SciencesUniversity Health Network
FundersJanssen PharmaceuticalsAbbott VascularSt. Jude MedicalMicroPortIdorsia PharmaceuticalsPharmaMarDaiichi Sankyo EuropeGilead SciencesServierEisaiBritish Heart FoundationSanofiAbiomedOsprey MedicalAmarin PharmaNovo NordiskMedicines CompanyAstraZenecaAmarin CorporationBoston Scientific CorporationMassachusetts Medical SocietyRegeneron PharmaceuticalsMedicureUS WorldMedsBristol-Myers SquibbEli Lilly and CompanyPfizerIcahn School of Medicine at Mount SinaiCSL BehringCardinal HealthAmgen
KeywordsTicagrelorConventional PCIPercutaneous coronary interventionAspirinP2Y12MedicineCardiologyInternal medicineClopidogrelMyocardial infarction

Abstract

fetched live from OpenAlex

BACKGROUND: inhibitor after a minimum period of dual antiplatelet therapy is an emerging approach to reduce the risk of bleeding after percutaneous coronary intervention (PCI). METHODS: In a double-blind trial, we examined the effect of ticagrelor alone as compared with ticagrelor plus aspirin with regard to clinically relevant bleeding among patients who were at high risk for bleeding or an ischemic event and had undergone PCI. After 3 months of treatment with ticagrelor plus aspirin, patients who had not had a major bleeding event or ischemic event continued to take ticagrelor and were randomly assigned to receive aspirin or placebo for 1 year. The primary end point was Bleeding Academic Research Consortium (BARC) type 2, 3, or 5 bleeding. We also evaluated the composite end point of death from any cause, nonfatal myocardial infarction, or nonfatal stroke, using a noninferiority hypothesis with an absolute margin of 1.6 percentage points. RESULTS: We enrolled 9006 patients, and 7119 underwent randomization after 3 months. Between randomization and 1 year, the incidence of the primary end point was 4.0% among patients randomly assigned to receive ticagrelor plus placebo and 7.1% among patients assigned to receive ticagrelor plus aspirin (hazard ratio, 0.56; 95% confidence interval [CI], 0.45 to 0.68; P<0.001). The difference in risk between the groups was similar for BARC type 3 or 5 bleeding (incidence, 1.0% among patients receiving ticagrelor plus placebo and 2.0% among patients receiving ticagrelor plus aspirin; hazard ratio, 0.49; 95% CI, 0.33 to 0.74). The incidence of death from any cause, nonfatal myocardial infarction, or nonfatal stroke was 3.9% in both groups (difference, -0.06 percentage points; 95% CI, -0.97 to 0.84; hazard ratio, 0.99; 95% CI, 0.78 to 1.25; P<0.001 for noninferiority). CONCLUSIONS: Among high-risk patients who underwent PCI and completed 3 months of dual antiplatelet therapy, ticagrelor monotherapy was associated with a lower incidence of clinically relevant bleeding than ticagrelor plus aspirin, with no higher risk of death, myocardial infarction, or stroke. (Funded by AstraZeneca; TWILIGHT ClinicalTrials.gov number, NCT02270242.).

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.006
GPT teacher head0.228
Teacher spread0.221 · 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 designRandomized trial
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

Citations1,000
Published2019
Admission routes2
Has abstractyes

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