Bibliographic record
Abstract
Mebazaa et al. review the use of agents with vasodilator properties for the treatment of acute HF.1 Better trials' design with early randomization, proper patients' selection, adequate endpoints, in addition to specific drugs' characteristics, will hopefully contribute to the identification of new drugs effective for the treatment of acute HF.1 Worsening HF is associated with higher risk for rehospitalizations and deaths in acute HF trials.2 Mentz et al. have confirmed its prognostic value and have found that this was not influenced by the time of occurrence and the intensity of treatment in 1,879 patients enrolled in the PROTECT trial.3 Uncertainties and dilemmas regarding HFpEF are reviewed by Ferrari et al.4 Echocardiographic predictors of clinical outcomes are analyzed in 538 HFpEF patients enrolled in the KaRen study with only E/e' as an independent predictor of deaths or HF hospitalizations after adjustment for baseline variables.5 Both abnormal QRS morphology and prolonged QRS duration were independent predictors of poorer outcomes in 2275 patients with HFrEF and mild symptoms enrolled in the EMPHASIS-HF trial.6 A simple risk stratification score after cardiac resynchronization therapy, based on age, gender, LVEF, NYHA class, atrial fibrillation, atrio-ventricular junction ablation, coronary heart disease, diabetes and ICD back-up has been developed in 3629 consecutive patients and validated in a cohort of 1524 other patients enrolled from 72 European centers.7 The advantages and limitations of this model are outlined in a comment by Normand and Dickstein.8 The hypothesis that the administration of the novel oral anticoagulant rivaroxaban may decrease events rate in patients with HFrEF is currently tested in the COMMANDER-HF trial, a randomised, double-blind, event-driven, multicentre study comparing oral rivaroxaban with placebo for reducing the risk of death, myocardial infarction or stroke in subjects with HFrEF, following an episode of HF decompensation:9 The rationale for this trial is outlined in an accompanying editorial.10 Lastly, the use of Wii gaming to improve exercise capacity and quality of life is discussed and will be formally tested in a new trial whose design is shown in our journal:11
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.345 | 0.290 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".