Clinical Outcome Endpoints in Heart Failure Trials: A European Society of Cardiology Heart Failure Association Consensus Document
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Full frame distilled prediction
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.
- Candidate categories
- Meta-epidemiology (narrow), Insufficient payload (model declined to judge)
- Consensus categories
- none
- Domain
- Candidate signal: noneConsensus signal: none
- Study design
- Candidate signal: Not applicableConsensus signal: Not applicable
- Genre
- Candidate signal: EmpiricalConsensus signal: Empirical
- Teacher disagreement score
- 0.436
- Threshold uncertainty score
- 1.000
- Validation status
machine_predicted_unvalidated·codex-gemma-dda1882f352a
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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.
- Teacher spread
- 0.288 · how far apart the two teachers sit on this one work
- Validation status
score_only:v0-immature-baseline· verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it
Abstract
Endpoint selection is a critically important step in clinical trial design. It poses major challenges for investigators, regulators, and study sponsors, and it also has important clinical and practical implications for physicians and patients. Clinical outcomes of interest in heart failure trials include all-cause mortality, cause-specific mortality, relevant non-fatal morbidity (e.g., all-cause and cause-specific hospitalization), composites capturing both morbidity and mortality, safety, symptoms, functional capacity, and patient-reported outcomes. Each of these endpoints has strengths and weaknesses that create controversies regarding which is most appropriate in terms of clinical importance, sensitivity, reliability, and consistency. Not surprisingly, a lack of consensus exists within the scientific community regarding the optimal endpoint(s) for both acute and chronic heart failure trials. In an effort to address these issues, the Heart Failure Association of the European Society of Cardiology (HFA-ESC) convened a group of expert heart failure clinical investigators, biostatisticians, regulators, and pharmaceutical industry scientists (Nice, France, 12-13 February 2012) to evaluate the challenges of defining heart failure endpoints in clinical trials and to develop a consensus framework. This report summarizes the group's recommendations for achieving common views on heart failure endpoints in clinical trials.
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.
The record
- Venue
- European Journal of Heart Failure
- Topic
- Heart Failure Treatment and Management
- Field
- Medicine
- Canadian institutions
- University of Alberta
- Funders
- National Institute for Health and Care Research
- Keywords
- MedicineHeart failureClinical trialClinical endpointIntensive care medicineEndpoint DeterminationMEDLINEConsistency (knowledge bases)Internal medicine
- Has abstract in OpenAlex
- yes