July 2018 at a Glance: Practical Guidance in Acute Heart Failure, Pathophysiology and Clinical Trials of Medical Therapy
Bibliographic record
Abstract
Acute heart failureA statement from the Acute Heart Failure Committee of the Heart Failure Association of the European Society of Cardiology (ESC) provides practical recommendations about clinical, laboratory and instrumental monitoring of patients hospitalized for acute heart failure (HF).The indications, timing of assessment and prognostic value of clinical symptoms and signs, laboratory markers and echocardiographic parameters are discussed.1 Pathophysiology Left ventricular ejection time and development of heart failureBiering-Sørensen et al. 2 assessed the role of left ventricular ejection time (LVET) for the development of HF in a middle-aged African-Americans cohort of the Atherosclerosis Risk in Communities study (Jackson cohort, n = 1980) who underwent echocardiography between 1993 and 1995.During a median follow-up of 17.6 years, 384 subjects (19%) developed HF, 158 (8%) had a myocardial infarction, and 587 (30%) died.A lower LVET was associated with increased risk of all events and remained an independent predictor of incident HF (hazard ratio 1.07, 95% confidence interval 1.02-1.14;P = 0.010 per 10 ms decrease) after adjustment for age, sex, hypertension, diabetes, body mass index, heart rate, systolic and diastolic blood pressure, fractional shortening and left atrial diameter.
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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 | 0.036 | 0.137 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.021 | 0.017 |
| Insufficient payload (model declined to judge) | 0.109 | 0.097 |
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".