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Record W2887902830 · doi:10.14740/cr754w

Myocardial Stunning After Electrocution With Complete Reversibility Within 24 Hours: Role of Repeat Transthoracic Echocardiograms in Potential Cardiac Transplant Donors

2018· article· en· W2887902830 on OpenAlexvenueno aff
Hassan Tahir, Sarina Sachdev, Landai Nguyen, Nikky Bardia, Bassam Omar, Michael V. Cohen

Bibliographic record

VenueCardiology Research · 2018
Typearticle
Languageen
FieldMedicine
TopicCardiac Structural Anomalies and Repair
Canadian institutionsnot available
Fundersnot available
KeywordsStunningMedicineMyocardial stunningCardiologyInternal medicineElectrocutionEconomic shortageHeart failureTransthoracic echocardiogramHeart transplantationVentricular assist deviceTransplantationHeart transplantsIschemiaEmergency medicine

Abstract

fetched live from OpenAlex

Despite the development of ventricular assist devices, cardiac transplantation remains an important procedure for patients with advanced heart failure. The number of transplants done annually has remained stable because of lack of of donors. Left ventricular systolic dysfunction remains one of the most important reasons for seeking a donor heart. Myocardial stunning is an important cause of reversible systolic dysfunction. Electrical injury is a recognized cause of myocardial stunning with variable duration ranging from days to weeks. Repeating the transthoracic echocardiogram to look for reversibility of left ventricular dysfunction can be a cost-effective method to improve the selection of heart donors. This can significantly help to decrease critical organ shortage. We present a case of myocardial stunning after electrocution which was completely reversible within a few hours, thus meeting cardiac transplant donor criteria.

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)0.002
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 score0.064
Threshold uncertainty score0.892

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.002
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 head0.024
GPT teacher head0.309
Teacher spread0.285 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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