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Record W2073266518 · doi:10.1155/2012/126369

Everolimus-Eluting versus Paclitaxel-Eluting Stents in Percutaneous Coronary Intervention: Meta-Analysis of Randomized Trials

2012· article· en· W2073266518 on OpenAlexaff
Ashraf Alazzoni, Ayman Al-Saleh, Sanjit S. Jolly

Bibliographic record

VenueThrombosis · 2012
Typearticle
Languageen
FieldMedicine
TopicCoronary Interventions and Diagnostics
Canadian institutionsMcMaster UniversityHamilton Health Sciences
Fundersnot available
KeywordsMedicinePercutaneous coronary interventionEverolimusStentPaclitaxelAlgorithmRandomized controlled trialInternal medicineComputer scienceMyocardial infarctionChemotherapy

Abstract

fetched live from OpenAlex

Background. Individual randomized trials have suggested that everolimus-eluting stents may have improved clinical outcomes compared to paclitaxel-eluting stents, but individual trials are underpowered to examine outcomes such as mortality and very late stent thrombosis. Methods. Medline, Cochrane, and conference proceedings were searched for randomized trials comparing everolimus versus paclitaxel-eluting stents for percutaneous coronary intervention. Results. 6792 patients were included from 4 randomized controlled trials. Stent thrombosis was reduced with everolimus stents versus paclitaxel stents (0.7% versus 2.3%; OR: 0.32; CI: 0.20-0.51; P < 0.00001). The reductions in stent thrombosis were observed in (i) early stent thrombosis (within 30 days) (0.2% versus 0.9%; OR: 0.24; P = 0.0005), (ii) late (day 31-365) (0.2% versus 0.6%; OR: 0.32; P = 0.01), and (iii) very late stent thrombosis (>365 days) (0.2% versus 0.8%; OR: 0.34; P = 0.009). The rates of cardiovascular mortality were 1.2% in everolimus group and 1.6% in paclitaxel group (OR: 0.85; P = 0.43). Patients receiving everolimus-eluting stents had significantly lower myocardial infarction events and target vessel revascularization as compared to paclitaxel-eluting stents. Interpretation. Everolimus compared to paclitaxel-eluting stents reduced the incidence of early, late, and very late stent thrombosis as well as target vessel revascularization.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.007
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.000

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 head0.253
GPT teacher head0.418
Teacher spread0.166 · 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 teacher head, not a consensus.

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".

Quick stats

Citations27
Published2012
Admission routes1
Has abstractyes

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