First phase ejection fraction in aortic stenosis: A useful new measure of early left ventricular systolic dysfunction
Bibliographic record
Abstract
In aortic stenosis (AS), a left ventricular (LV) ejection fraction (EF) <50% or symptoms are class I indications for aortic valve intervention. However, an EF <50% may be too conservative since subendocardial fibrosis may already have developed. An earlier marker of LV systolic dysfunction is therefore needed and first phase EF (EF1) is a promising new candidate. It is the EF measured over early systole to the point of maximum transaortic blood flow. It may be low in the presence of preserved total LV EF since the heart may compensate by recruiting myosin motors in later systole. The EF1 is inversely related to the grade of AS and directly related to markers of subendocardial fibrosis like late gadolinium enhancement on cardiac magnetic resonance scanning. A reduced EF1 (<25%) predicts adverse clinical events better that total EF and global longitudinal strain. We suggest that it is worth exploring as an indication for surgery in patients with asymptomatic severe AS.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".