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Comparing dual antiplatelet therapy strategies post-acute coronary syndrome: network meta-analysis

2022· article· en· W4306320583 on OpenAlexaff
Ricky D. Turgeon, Chaokun Hong, Erica H. Z. Wang, Graham C. Wong, Ursula Ellis

Bibliographic record

VenueEuropean Heart Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicAntiplatelet Therapy and Cardiovascular Diseases
Canadian institutionsSt. Paul's HospitalUniversity of British Columbia
Fundersnot available
KeywordsMedicineMaceAcute coronary syndromeClopidogrelInternal medicineTicagrelorOdds ratioMeta-analysisPercutaneous coronary interventionMyocardial infarctionCardiology

Abstract

fetched live from OpenAlex

Abstract Background Various approaches to dual antiplatelet therapy (DAPT) management exist to balance thrombotic and bleeding risks following acute coronary syndrome (ACS). Purpose The aim of this study was to compare and rank different DAPT management strategies in patients with ACS with or without percutaneous coronary interventions. Methods We conducted a systematic review with network meta-analysis of randomized controlled trials comparing DAPT strategies in patients with ACS using MEDLINE, Embase, and CENTRAL (2007-July 2021). The primary outcome was major adverse cardiovascular events (MACE). Secondary outcomes included all-cause death and major bleeding. We performed Bayesian network meta-analyses to compare all interventions simultaneously using the Markov-chain Monte Carlo method, conducted under the assumption of transitivity. We generated odds ratios (ORs) with 95% credible intervals (CrI) from the medians and 2.5th and 97.5th percentiles of the posterior distributions using a hierarchical Bayesian framework, using a random-effects model with informative priors for between-study heterogeneity based on pharmacological interventions with semi-objective outcomes (MACE or bleeding) or death. To rank interventions for each outcome, we calculated the mean surface under the cumulative ranking (SUCRA) curve. Results From 5941 articles, we included 24 trials (89,620 patients). Both clopidogrel- and ticagrelor-based DAPT increased MACE compared with pharmacogenomics-guided P2Y12 inhibitor selection (odds ratio [OR] 1.37, 95% credible interval [CrI] 1.08–1.74 and 1.35, 1.05–1.79, respectively) and empiric P2Y12 inhibitor de-escalation (OR 1.53, 95%CrI 1.00–2.30 and 1.51, 1.00–2.27, respectively). Compared with short-duration DAPT, standard DAPT duration with all P2Y12 inhibitors (clopidogrel, prasugrel, ticagrelor) and pharmacogenomics-guided P2Y12 inhibitor selection increased major bleeding. Ticagrelor-based DAPT increased major bleeding compared with platelet function testing-guided DAPT (OR 1.60, 95%CrI 1.00–2.55). Empiric P2Y12 inhibitor de-escalation ranked best for MACE (SUCRA 0.89), whereas short-duration DAPT ranked best for death (SUCRA 0.89) and major bleeding (SUCRA 0.93). Conclusions In patients with ACS, empiric P2Y12 inhibitor de-escalation was most efficacious whereas short-duration DAPT was the safest compared to other DAPT strategies. Funding Acknowledgement Type of funding sources: None.

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)0.028
metaresearch head score (Gemma)0.053
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.028
Threshold uncertainty score0.146

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0280.053
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0150.039
Bibliometrics0.0070.006
Science and technology studies0.0000.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.098
GPT teacher head0.306
Teacher spread0.208 · 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 designMeta-analysis
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".

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Citations1
Published2022
Admission routes1
Has abstractyes

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