Bibliographic record
Abstract
BACKGROUND: Although several epidemiological studies demonstrate the association between resting heart rate (HR) and cardiovascular morbidity and mortality, an elevated HR remains a neglected cardiovascular risk factor. SOURCES OF DATA: This review summarizes the results of published studies on the relationship between elevated HR and cardiovascular risk. AREAS OF AGREEMENT: The role of HR in myocardial ischaemia in coronary patients is well known. Experimental data and clinical observations support the importance of HR in the pathophysiology of atherosclerosis and plaque rupture. A large body of evidence points to high resting HR as a risk factor for mortality in various populations, including coronary patients. AREAS OF CONTROVERSY: HR reduction is suggested to be a mechanism explaining the prognostic benefit of beta-blockers after myocardial infarction or in heart failure patients. However, it was unclear whether HR reduction per se directly affects cardiovascular prognosis. Treatment with ivabradine, a pure HR-reducing agent, provides an opportunity to assess the effects of selectively lowering HR without altering other aspects of cardiac function. GROWING POINTS: The results of the recent Morbidity-Mortality Evaluation of the I(f) Inhibitor Ivabradine in Patients with Coronary Disease and Left Ventricular Dysfunction study underline the importance of HR reduction in the management of stable coronary artery disease. The prospective analysis of data from the placebo arm demonstrated that elevated resting HR (>or=70 bpm) is a strong independent predictor of clinical outcomes. Consistent with these data, ivabradine significantly improved coronary outcomes in patients with a HR of 70 bpm or more. AREAS TIMELY FOR DEVELOPMENT: These data support the importance of HR in the management of stable coronary artery disease to assess prognosis and to guide optimal therapy.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".