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Record W2023299185 · doi:10.1002/mrm.1115

Examining a canine model of stunned myocardium with Gd‐DTPA‐enhanced MRI

2001· article· en· W2023299185 on OpenAlexafffund
Rebecca E. Thornhill, Frank S. Prato, Raoul S. Pereira, Gerald Wisenberg, Jane Sykes

Bibliographic record

VenueMagnetic Resonance in Medicine · 2001
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsSt Joseph's Health CentreWestern UniversityLawson Health Research Institute
FundersSiemens CanadaMedical Research Council Canada
KeywordsIn vivoNuclear medicineMyocardial stunningStunningMedicineFissipediaOcclusionInfarctionCardiologyMyocardial infarctionInternal medicineChemistryIschemiaBiology

Abstract

fetched live from OpenAlex

It has previously been shown that the distribution volume of Gd-DTPA (lambda) in infarcted, canine myocardium is higher than that of normal tissue. The purpose of this study was to determine whether stunned myocardium exhibits increased lambda. Stunning was produced in beagles by means of 30 min LAD occlusion followed by 3 weeks (n = 4) reperfusion. Gd-DTPA was infused at each imaging session and lambda determined in vivo using a saturation recovery turboFLASH sequence; cine imaging was used to assess ventricular wall thickening (%WT). (201)Tl uptake was used as an independent assessment of viability. %WT data confirmed that the brief insult caused prolonged, yet reversible, regional contractile dysfunction in each animal. %WT was not significantly different from baseline values by 3 weeks post-reflow. Normal (201)Tl uptake confirmed the absence of infarction. The lambda of stunned tissue (lambda = 0.381 +/- 0.030 ml/g) was not elevated above that of normal tissue (lambda = 0.398 +/- 0.027 ml/g, P = NS), at any time point studied, in vivo. These data suggest that an increase in lambda is a specific indicator of irreversible damage.

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)0.001
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 score0.139
Threshold uncertainty score0.863

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.026
GPT teacher head0.272
Teacher spread0.246 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations22
Published2001
Admission routes2
Has abstractyes

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