June 2019 at a Glance: From Genetics to Haemodynamics, Biomarkers and Imaging for the Prediction of Outcomes
Bibliographic record
Abstract
Mutations in arrhythmogenic right ventricular cardiomyopathy/dysplasiaGenetic status affects the clinical course of patients with arrhythmogenic right ventricular cardiomyopathy/dysplasia.Hermida et al. 1 compared the outcomes of desmoglein-2 (DSG2) mutation carriers to those with plakophilin-2 (PKP2) mutation.There were no differences between DSG2 and PKP2 mutation carriers concerning gender, proband status, age at diagnosis, T-wave inversion, or right ventricular dysfunction at baseline.DSG2 patients displayed more frequent epsilon wave and more left ventricular (LV) dysfunction at diagnosis.During a median follow-up of 5.6 years, DSG2 and PKP2 mutation carriers had a similar risk of sustained ventricular arrhythmia, but DSG2 mutation carriers were at higher risk of transplantation/heart failure (HF)-related death.Thus, DSG2 mutation is associated with a high risk of end-stage HF, compared to PKP2 mutation, and careful haemodynamic monitoring is needed in these patients.1 Haemodynamics Adult Fontan patientsThe Fontan operation is associated with significant long-term morbidity and mortality.Miranda et al. 2 divided 84 adult Fontan patients into four different haemodynamic profiles based on Fontan pressures and cardiac index.The normal cardiac index/high Fontan pressure haemodynamic profile was an independent predictor of mortality. Biomarkers Natriuretic peptidesA position statement by the Heart Failure Association (HFA) gives a thorough update of the role of natriuretic peptides, brain natriuretic peptide (BNP), N-terminal proBNP (NT-proBNP) and mid-regional pro-atrial natriuretic peptide, in the diagnosis . . . . . . . . . . . . . . . . . . . . . . . . .
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.039 | 0.024 |
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".