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Ejection Fraction Velocity Ratio as an Indicator of Aortic Stenosis Severity

2005· article· en· W2097117252 on OpenAlex
Abdullah Alghamdi, Libardo J. Meléndez, David Massel

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

VenueEchocardiography · 2005
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsCardiologyEjection fractionStenosisInternal medicineMedicineAortic valve stenosisAortic valveReceiver operating characteristicHeart failure

Abstract

fetched live from OpenAlex

BACKGROUND: Despite the widespread use of the continuity equation in the estimation of aortic valve area (AVA) in patients with aortic stenosis, it is subject to errors, time consuming, and can be technically demanding. As such, simpler methods of assessing aortic stenosis severity have been pursued. METHODS: The ejection fraction velocity ratio [EFVR = ejection fraction (%) / maximal aortic velocity (m/sec)] was compared to AVA determined with the continuity equation in 857 patients with aortic stenosis and varying degrees of LV systolic dysfunction. Severe aortic stenosis was defined as an AVA < 1.0 cm2. RESULTS: There was good to excellent correlation between our index and aortic valve area (P < 0.001 for each ejection fraction subgroup). Receiver operating characteristic analysis showed that the EFVR functioned well with areas under the curve between 0.893 and 0.938. CONCLUSION: The EFVR is a simple noninvasive method for screening patients for an AVA of 1.0 cm2. It could be used as a screening test or in lieu of the continuity equation particularly when there is problematic measurement of either the LVOT diameter or velocity.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.548

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.306
Teacher spread0.297 · 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