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Record W3200574352 · doi:10.1016/j.jacc.2021.07.048

Intracranial Hemorrhage During Dual Antiplatelet Therapy

2021· review· en· W3200574352 on OpenAlexaff
Andrew C.T. Ha, Deepak L. Bhatt, James T. Rutka, S. Claiborne Johnston, C. David Mazer, Subodh Verma

Bibliographic record

VenueJournal of the American College of Cardiology · 2021
Typereview
Languageen
FieldMedicine
TopicAntiplatelet Therapy and Cardiovascular Diseases
Canadian institutionsHospital for Sick ChildrenSt. Michael's HospitalToronto General HospitalUniversity Health NetworkUniversity of Toronto
FundersNational Institutes of HealthAstraZeneca
KeywordsMedicineTicagrelorStroke (engine)DiseaseComplicationInternal medicineIntracerebral hemorrhageAmbulatoryCardiologyIntensive care medicineClopidogrelAspirinSubarachnoid hemorrhage

Abstract

fetched live from OpenAlex

Dual antiplatelet therapy (DAPT) with acetylsalicylic acid and a P2Y12 inhibitor is an established therapy for a broad spectrum of patients with cardiovascular disease. The ischemic benefit of DAPT is partially offset by its increased bleeding risk, with intracranial hemorrhage (ICH) being the most serious complication. Although uncommon (0.2%-0.3% annually), its cumulative burden can be substantial given the number of patients afflicted by cardiovascular disease worldwide. Patients with a history of stroke or transient ischemic attack harbor a particularly high risk for ICH when treated with DAPT. Prediction rules may assist clinicians when weighing the risk/benefit ratio of prescribing DAPT for patients with stroke/transient ischemic attack in the nonacute, ambulatory setting. Currently, there are no reversal agents that can rapidly and effectively reverse the effect of P2Y12 inhibitors in routine practice, although a reversal agent for ticagrelor is under clinical investigation.

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)0.002
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.021
GPT teacher head0.298
Teacher spread0.277 · 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

Citations60
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the American College of CardiologySame topicAntiplatelet Therapy and Cardiovascular DiseasesFrench-language works237,207