P4413The prognostic importance of myocardial fibrosis detected by late-gadolinium enhancement cardiovascular magnetic resonance (LGE-CMR) in new-presentation dilated cardiomyopathy (DCM)
Bibliographic record
Abstract
Background: Presence of myocardial fibrosis in DCM has been reported to be associated with increased adverse clinical outcomes. However, the presence of myocardial fibrosis at presentation in DCM, and its subsequent role in perpetuating long term left ventricular (LV) dysfunction, heart failure (HF) and ventricular arrhythmia (VA) remains unclear. Past studies did not characterise DCM patients early in their disease course, and may not have accounted for patients with significant improvement in LV function. Objectives: To determine whether the extent of myocardial fibrosis quantified by LGE-CMR at presentation, independently predicts long term major adverse cardiovascular events (MACE) in patients with newly-diagnosed DCM. Methods: Consecutive patients with a new diagnosis of DCM made within the preceding two weeks were recruited. Patients underwent LGE-CMR, echocardiography, 6-minute-walk testing, cardiopulmonary exercise testing, and blood sampling for measurement of serum NT-pro-BNP concentration at baseline. Replacement myocardial fibrosis by LGE-CMR was quantified by experienced observers blinded to patient outcome. MACE was defined as a composite end-point including cardiac death, HF rehospitalisation and the occurrence of sustained VA defined as sustained VT or VF.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".