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Record W2906096545 · doi:10.1093/eurheartj/ehy808

Resting heart rate and cardiovascular outcomes in diabetic and non-diabetic individuals at high cardiovascular risk analysis from the ONTARGET/TRANSCEND trials

2018· article· en· W2906096545 on OpenAlexaff
Michael Böhm, Helmut Schumacher, Koon Teo, Eva Lonn, Felix Mahfoud, Christian Ukena, Johannes F.E. Mann, Giuseppe Mancia, Josep Redón, Roland E. Schmieder, Karen Sliwa, Nikolaus Marx, Michael A. Weber, Bryan Williams, Salim Yusuf

Bibliographic record

VenueEuropean Heart Journal · 2018
Typearticle
Languageen
FieldMedicine
TopicHeart rate and cardiovascular health
Canadian institutionsMcMaster UniversityPopulation Health Research Institute
FundersMedical Research CouncilDeutsche Forschungsgemeinschaft
KeywordsMedicineDiabetes mellitusInternal medicineCardiologyMyocardial infarctionRamiprilStroke (engine)Heart failureTelmisartanHazard ratioType 2 diabetesProportional hazards modelBlood pressureConfidence intervalEndocrinology

Abstract

fetched live from OpenAlex

AIMS: Resting heart rate (RHR) has been shown to be associated with cardiovascular outcomes in various conditions. It is unknown whether different levels of RHR and different associations with cardiovascular outcomes occur in patients with or without diabetes, because the impact of autonomic neuropathy on vascular vulnerability might be stronger in diabetes. METHODS AND RESULTS: We examined 30 937 patients aged 55 years or older with a history of or at high risk for cardiovascular disease and after myocardial infarction, stroke, or with proven peripheral vascular disease from the ONTARGET and TRANSCEND trials investigating ramipril, telmisartan, and their combination followed for a median of 56 months. We analysed the association of mean achieved RHR on-treatment with the primary composite outcome of cardiovascular death, myocardial infarction, stroke, hospitalization for heart failure, the components of the composite primary outcome, and all-cause death as continuous and categorical variables. Data were analysed by Cox regression analysis, ANOVA, and χ2 test. These trials were registered with ClinicalTrials.gov.number NCT00153101. Patients were recruited from 733 centres in 40 countries between 1 December 2001 and 31 July 2008 (ONTARGET) and 1 November 2001 until 30 May 2004 (TRANSCEND). In total, 19 450 patients without diabetes and 11 487 patients with diabetes were stratified by mean RHR. Patients with diabetes compared to no diabetes had higher RHRs (71.8 ± 9.0 vs. 67.9 ± 8.8, P < 0.0001). In the categories of <60 bpm, 60 ≤ 65 bpm, 65 ≤ 70 bpm, 70 ≤ 75 bpm, 75 ≤ 80 bpm and ≥80 bpm, non-diabetic patients had an increased hazard of the primary outcome with mean RHR of 75 ≤ 80 bpm (adjusted hazard ratio [HR] 1.17 (1.01-1.36)) compared to RHR 60 ≤ 65 bpm. For patients with in-trial RHR ≥80 bpm the hazard ratios were highest (diabetes: 1.96 (1.64-2.34), no diabetes: 1.73 (1.49-2.00), For cardiovascular death hazards were also clearly increased at RHR ≥80 bpm (diabetes [1.99, (1.53-2.58)], no diabetes [1.73 (1.38-2.16)]. Similar results were obtained for hospitalization for heart failure and all-cause death while the effect of RHR on myocardial infarction and stroke was less pronounced. Results were robust after adjusting for various risk indicators including beta-blocker use and atrial fibrillation. No significant association to harm was observed at lower RHR. CONCLUSION: Mean RHR above 75-80 b.p.m. was associated with increased risk for cardiovascular outcomes except for stroke. Since in diabetes, high RHR is associated with higher absolute event numbers and patients have higher RHRs, this association might be of particular clinical importance in diabetes. These data suggest that RHR lowering in patients with RHRs above 75-80 b.p.m. needs to be studied in prospective trials to determine if it will reduce outcomes in diabetic and non-diabetic patients at high cardiovascular risk. CLINICAL TRIAL REGISTRATION: http://clinicaltrials.gov.Unique identifier: NCT00153101.

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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)0.033
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0330.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.043
GPT teacher head0.294
Teacher spread0.251 · 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 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

Citations55
Published2018
Admission routes1
Has abstractyes

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