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Record W4367669151 · doi:10.11124/jbies-22-00375

Exercise stress cardiac magnetic resonance imaging in the assessment of induced cardiovascular responses in cardiac patients: a scoping review protocol

2023· review· en· W4367669151 on OpenAlexaff
Egidie Uwase, Maxime Caru, Ariane Lévesque, Philippe Dodin, Daniel Curnier, Delphine Périé

Bibliographic record

VenueJBI Evidence Synthesis · 2023
Typereview
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-JustinePolytechnique Montréal
Fundersnot available
KeywordsMedicineCardiac magnetic resonanceSystematic reviewProtocol (science)Cardiac magnetic resonance imagingMEDLINEMeta-analysisMedical physicsMagnetic resonance imagingIntensive care medicineInternal medicinePathologyAlternative medicineRadiology

Abstract

fetched live from OpenAlex

OBJECTIVE: This scoping review will describe cardiac magnetic resonance imaging testing protocols used in combination with exercise (Ex-CMR) to assess cardiovascular responses. The review will document the advantages and limitations of these protocols in cardiac patients. INTRODUCTION: Ex-CMR characterizes the heart, differentiating between normal and pathological cardiac remodeling with considerable accuracy. However, there is no review detailing existing Ex-CMR protocols. This is particularly important since not all Ex-CMR protocols seem to induce enough stress to effectively characterize cardiac remodeling, hence the need for a review to report on the current evidence. INCLUSION CRITERIA: This review will consider studies that use Ex-CMR testing protocols to assess cardiovascular responses, revealing cardiac remodeling in patients whose age at the time of the study was ≥ 18 years. METHODS: The review will be conducted in accordance with the JBI methodology for scoping reviews and reported in line with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). The following databases will be searched: PubMed, Embase, ISI Web of Science, OpenGrey, Grey Matters, and OAlster. Articles in English and French will be included and there will be no limitation set for the date of publication. Data will be extracted from papers included in the scoping review by 2 independent reviewers and will be classified in summary tables. REVIEW REGISTRATION: Open Science Framework https://osf.io/hvn75/?view_only=f6cf8fc2112e498d89c39639dbce70d1 .

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)0.008
metaresearch head score (Gemma)0.019
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.697
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.003
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.043
GPT teacher head0.403
Teacher spread0.360 · 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 designSystematic review
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

Citations2
Published2023
Admission routes1
Has abstractyes

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