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Record W2113562075 · doi:10.1186/1745-6215-14-332

Routine versus selective cardiac magnetic resonance in non-ischemic heart failure – OUTSMART-HF: study protocol for a randomized controlled trial (IMAGE-HF (heart failure) project 1-B)

2013· article· en· W2113562075 on OpenAlexafffundabout
D. Ian Paterson, George A. Wells, Justin A. Ezekowitz, James A. White, Matthias G. Friedrich, Lisa Mielniczuk, Eileen O’Meara, Benjamin J.W. Chow, Rob deKemp, Ran Klein, Carole Dennie, Alexander Dick, Doug Coyle, Girish Dwivedi, Miroslaw Rajda, Graham A. Wright, Mika Laine, Helena Hänninen, Éric Larose, Kim A. Connelly, Howard Leong‐Poi, Andrew G. Howarth, Ross A. Davies, Lloyd Duchesne, Seppo Ylä‐Herttuala, Antti Saraste, Paul Farand, Linda Garrard, Jean‐Claude Tardif, Malcolm Arnold, Juhani Knuuti, Rob Beanlands, Kwan L. Chan

Bibliographic record

VenueTrials · 2013
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsUniversité de SherbrookeUniversity of CalgarySt. Michael's HospitalSunnybrook Health Science CentreDalhousie UniversityLondon Health Sciences CentreOttawa HospitalMontreal Heart InstituteUniversité du QuébecUniversity of OttawaUniversité de MontréalUniversity of Alberta
FundersCanadian Institutes of Health ResearchAlberta InnovatesAlberta Cancer Foundation
KeywordsMedicineHeart failureEtiologyCardiac magnetic resonance imagingCardiologyEjection fractionInternal medicineMagnetic resonance imagingMedical diagnosisIschemic cardiomyopathyCardiomyopathyClinical trialIntensive care medicineRadiology

Abstract

fetched live from OpenAlex

BACKGROUND: Imaging has become a routine part of heart failure (HF) investigation. Echocardiography is a first-line test in HF given its availability and it provides valuable diagnostic and prognostic information. Cardiac magnetic resonance (CMR) is an emerging clinical tool in the management of patients with non-ischemic heart failure. Current ACC/AHA/CCS/ESC guidelines advocate its role in the detection of a variety of cardiomyopathies but there is a paucity of high quality evidence to support these recommendations.The primary objective of this study is to compare the diagnostic yield of routine cardiac magnetic resonance versus standard care (that is, echocardiography with only selective use of CMR) in patients with non-ischemic heart failure. The primary hypothesisis that the routine use of CMR will lead to a more specific diagnostic characterization of the underlying etiology of non-ischemic heart failure. This will lead to a reduction in the non-specific diagnoses of idiopathic dilated cardiomyopathy and HF with preserved ejection fraction. DESIGN: Tertiary care sites in Canada and Finland, with dedicated HF and CMR programs, will randomize consecutive patients with new or deteriorating HF to routine CMR or selective CMR. All patients will undergo a standard clinical echocardiogram and the interpreter will assign the most likely HF etiology. Those undergoing CMR will also have a standard examination and will be assigned a HF etiology based upon the findings. The treating physician's impression about non-ischemic HF etiology will be collected following all baseline testing (including echo ± CMR). Patients will be followed annually for 4 years to ascertain clinical outcomes, quality of life and cost. The expected outcome is that the routine CMR arm will have a significantly higher rate of infiltrative, inflammatory, hypertrophic, ischemic and 'other' cardiomyopathy than the selective CMR group. DISCUSSION: This study will be the first multicenter randomized, controlled trial evaluating the role of CMR in non-ischemic HF. Non-ischemic HF patients will be randomized to routine CMR in order to determine whether there are any gains over management strategies employing selective CMR utilization. The insight gained from this study should improve appropriate CMR use in HF. TRIAL REGISTRATION: NCT01281384.

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)0.011
metaresearch head score (Gemma)0.043
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.162
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.043
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0080.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.035
GPT teacher head0.377
Teacher spread0.342 · 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 designRandomized trial
Domainnot available
GenreProtocol

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

Citations6
Published2013
Admission routes3
Has abstractyes

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