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Blood pressure and clinical outcomes in patients with diabetes and stable coronary artery disease in THEMIS

2022· article· en· W4306251243 on OpenAlexaff
Manan Pareek, Deepak L. Bhatt, Léon Zheng, J J Lee, L. A. Leiter, Tabassome Simon, SD Mehta, Robert A. Harrington, K. Fox, Anders Himmelmänn, Emmanuelle Vidal‐Petiot, Philippe Gabríel Steg

Bibliographic record

VenueEuropean Heart Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicHeart rate and cardiovascular health
Canadian institutionsMcMaster UniversitySt. Michael's Hospital
Fundersnot available
KeywordsMedicineTicagrelorInternal medicineCardiologyBlood pressureMyocardial infarctionCoronary artery diseaseStroke (engine)AspirinPopulationDiabetes mellitusTIMIProportional hazards modelPulse pressureAcute coronary syndromePercutaneous coronary interventionEndocrinology

Abstract

fetched live from OpenAlex

Abstract Background Various BP characteristics, e.g., systolic blood pressure (SBP), diastolic blood pressure (DBP), and pulse pressure (PP), as well as heart rate (HR) may affect the risk of both cardiovascular events and bleeding events. However, the exact way in which these characteristics and outcomes are associated among patients with diabetes and stable coronary artery disease (CAD) remains debated. Moreover, it is unknown whether the risks and benefits of intensified antiplatelet therapy in this patient population are affected by their baseline BP and HR. Purpose To assess the relationship between BP components (including HR) and cardiovascular and bleeding events, and to determine if the effects of ticagrelor vs. placebo varied across the BP and HR spectrum, in patients with diabetes and stable CAD. Methods THEMIS was a randomized, controlled trial in which 19,220 individuals ≥50 years of age with stable CAD and type 2 diabetes were randomized to receive either ticagrelor plus aspirin or placebo plus aspirin. Patients with a prior myocardial infarction or stroke, or already on dual antiplatelet therapy, were excluded. The primary efficacy outcome was a composite of cardiovascular death, myocardial infarction, or stroke. The primary safety outcome was TIMI major bleeding. We examined prognostic implications of BP components using 1) restricted cubic splines for the overall trends with outcomes; 2) Cox proportional-hazards regression models with predefined BP component intervals adjusted for demographic, clinical, and laboratory variables; and 3) Cox regression models for the effects of ticagrelor vs. placebo on outcomes across the spectrum of BP component values (test for interaction). THEMIS is registered at ClinicalTrials.gov (NCT01991795). Results Mean values of baseline BP components were similar between the two study groups. Median follow-up duration was 39.9 months (range 0–57), with 1554 primary efficacy events and 306 primary safety events occurring over the course of the study. All BP components (including HR) displayed various, independent relationships with the tested outcomes. For example, in adjusted spline models, SBP displayed non-linear relationships with the primary outcome, all-cause death, any bleeding, serious adverse events, and intracranial bleeding, and linear relationships with the remaining outcomes. Figure 1 shows the associations of each BP component with the primary efficacy outcome. BP components did not substantially modify the risks and benefits of ticagrelor vs. placebo for the tested outcomes. Conclusions BP components were independently associated with efficacy and safety outcomes in patients with stable CAD and type 2 diabetes. However, no important modification of BP components on the effect of ticagrelor vs. placebo was detected. Funding Acknowledgement Type of funding sources: Private company. Main funding source(s): AstraZeneca

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.274
Teacher spread0.254 · 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 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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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