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Record W3011676222 · doi:10.14740/cr851

Stress Echocardiography: Concept and Criteria, Structure and Steps, Obstacles and Outcomes, Focused Update and Review

2020· review· en· W3011676222 on OpenAlexvenueno aff
Antoine Kossaify, Elie Bassil, Mikhael Kossaify

Bibliographic record

VenueCardiology Research · 2020
Typereview
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineStress EchocardiographyCoronary artery diseaseDobutamineCardiologyStenosisInternal medicineDiastoleCADHemodynamicsBlood pressure

Abstract

fetched live from OpenAlex

Stress echocardiography (SEC) is a technique established more than 35 years ago; however, it is still poorly implemented in many countries and institutions, and this reluctance may be related to many obstacles such as operator skills, lack of awareness or institutional policy. Stress echo was initially used for assessing coronary artery disease (CAD), with respect to myocardial viability, using wall motion response; however, current use of stress echo extends beyond CAD, such as valvular heart disease and diastolic stress test. Dobutamine is a commonly used agent when pharmaceutical approach is implemented. With regard to CAD, there are four stress responses: normal, ischemic, viable and necrotic. A low dose dobutamine protocol is recommended in patients with baseline wall motion abnormalities, and a very low dose dobutamine is used in low flow low gradient aortic stenosis in order to check the flow and contractility reserve. Of note, respecting protocols, indications and contraindications are important to avoid or minimize risks of complications during the procedure. This article presents a focused update and review regarding SEC, along with an overview of the different indications, structures and steps, and obstacles and outcomes; also the article aims to highlight more awareness and sensitization on this useful technique.

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 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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.950
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0050.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.002
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 head0.077
GPT teacher head0.430
Teacher spread0.353 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations12
Published2020
Admission routes1
Has abstractyes

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