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Record W3112345872 · doi:10.1002/jcu.23063

First phase ejection fraction in aortic stenosis: A useful new measure of early left ventricular systolic dysfunction

2021· review· en· W3112345872 on OpenAlex
Sahrai Saeed, Haotian Gu, Ronak Rajani, Phil Chowienczyk, John B. Chambers

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Clinical Ultrasound · 2021
Typereview
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsSt. Thomas Hospital
FundersBritish Heart Foundation
KeywordsMedicineCardiologyInternal medicineEjection fractionSystoleStenosisAsymptomaticDiastoleFibrosisBlood pressureHeart failure

Abstract

fetched live from OpenAlex

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.591
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.007
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.091
GPT teacher head0.456
Teacher spread0.365 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it