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Record W2464586391 · doi:10.1161/jaha.116.003407

Lipoprotein‐Associated Phospholipase A <sub>2</sub> Activity Is a Marker of Risk But Not a Useful Target for Treatment in Patients With Stable Coronary Heart Disease

2016· article· en· W2464586391 on OpenAlexaff
Lars Wallentin, Claes Held, Paul W. Armstrong, Christopher P. Cannon, Richard Y. Davies, Christopher B. Granger, Emil Hagström, Robert A. Harrington, Judith S. Hochman, Wolfgang Köenig, Sue Krug‐Gourley, Emile R. Mohler, Agneta Siegbahn, Elizabeth Tarka, Philippe Gabríel Steg, Ralph Stewart, Robert Weiss, Ollie Östlund, Harvey D. White, Andrzej Budaj, Diego Ardissino, Álvaro Avezum, Philip E. Aylward, Alfonso Bryce, Hong Chen, Ming‐Fong Chen, Ramón Corbalán, Anthony J. Dalby, Nicolas Danchin, Robbert J. de Winter, Stefan Denchev, Rafael Díaz, Moses Elisaf, Marcus Flather, Assen Goudev, Liliana Grinfeld, Steen Husted, Hyo‐Soo Kim, Aleš Linhart, Eva Lonn, José López‐Sendón, Athanasios Manolis, José Carlos Nicolau, Prem Pais, Alexander Parkhomenko, Terje R. Pedersen, Daniel Pella, Marco Antonio Ramos-Corrales, Mikhail Ruda, Mátyás Sereg, Saulat Siddique, Peter Sinnaeve, Piyamitr Sritara, Henk P. Swart, Rody G. Sy, Tamio Teramoto, Hung‐Fat Tse, W. Douglas Weaver, Margus Viigimaa, Dragoş Vinereanu, Junren Zhu

Bibliographic record

VenueJournal of the American Heart Association · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Kinase Regulation and GTPase Signaling
Canadian institutionsCanadian VIGOUR CentreUniversity of Alberta
FundersAgence Nationale de la Recherche
KeywordsMedicineInterquartile rangeLipoprotein-associated phospholipase A2Hazard ratioInternal medicineMyocardial infarctionProportional hazards modelCardiologyHeart failureSurrogate endpointClinical endpointLipoproteinConfidence intervalClinical trialCholesterol

Abstract

fetched live from OpenAlex

BACKGROUND: We evaluated lipoprotein-associated phospholipase A2 (Lp-PLA2) activity in patients with stable coronary heart disease before and during treatment with darapladib, a selective Lp-PLA2 inhibitor, in relation to outcomes and the effects of darapladib in the STABILITY trial. METHODS AND RESULTS: Plasma Lp-PLA2 activity was determined at baseline (n=14 500); at 1 month (n=13 709); serially (n=100) at 3, 6, and 18 months; and at the end of treatment. Adjusted Cox regression models evaluated associations between Lp-PLA2 activity levels and outcomes. At baseline, the median Lp-PLA2 level was 172.4 μmol/min per liter (interquartile range 143.1-204.2 μmol/min per liter). Comparing the highest and lowest Lp-PLA2 quartile groups, the hazard ratios were 1.50 (95% CI 1.23-1.82) for the primary composite end point (cardiovascular death, myocardial infarction, or stroke), 1.95 (95% CI 1.29-2.93) for hospitalization for heart failure, 1.42 (1.07-1.89) for cardiovascular death, and 1.37 (1.03-1.81) for myocardial infarction after adjustment for baseline characteristics, standard laboratory variables, and other prognostic biomarkers. Treatment with darapladib led to a ≈65% persistent reduction in median Lp-PLA2 activity. There were no associations between on-treatment Lp-PLA2 activity or changes of Lp-PLA2 activity and outcomes, and there were no significant interactions between baseline and on-treatment Lp-PLA2 activity or changes in Lp-PLA2 activity levels and the effects of darapladib on outcomes. CONCLUSIONS: Although high Lp-PLA2 activity was associated with increased risk of cardiovascular events, pharmacological lowering of Lp-PLA2 activity by ≈65% did not significantly reduce cardiovascular events in patients with stable coronary heart disease, regardless of the baseline level or the magnitude of change of Lp-PLA2 activity. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov. Unique identifier: NCT00799903.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.107
Threshold uncertainty score0.336

Codex and Gemma teacher scores by category

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

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 head0.220
Teacher spread0.213 · 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.

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

Citations65
Published2016
Admission routes1
Has abstractyes

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