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Record W2316805009 · doi:10.1097/tme.0b013e31823df79a

Body Surface Mapping Improves Diagnosis of Acute Myocardial Infarction in the Emergency Department

2012· review· en· W2316805009 on OpenAlexaff
Michael J. Franks, Lauren Lawson

Bibliographic record

VenueAdvanced Emergency Nursing Journal · 2012
Typereview
Languageen
FieldMedicine
TopicECG Monitoring and Analysis
Canadian institutionsLawson Foundation
Fundersnot available
KeywordsMedicineTorsoEmergency departmentVentricleMyocardial infarctionBody surfaceCardiologyLead (geology)Internal medicineElectrocardiographyHeart failureMedical emergency

Abstract

fetched live from OpenAlex

Traditionally, the diagnosis of acute myocardial infarction (AMI) in emergency departments is done through an assessment of history and presenting symptoms, 12-lead electrocardiogram (ECG), and cardiac biomarkers. The 12-lead ECG is not highly sensitive for detecting ECG changes, and some infarctions may be missed. Failure to identify patients in the early stages of AMI can result in failure to provide beneficial therapies. New technology, the 80-lead ECG, uses body surface mapping to provide a more comprehensive view of cardiac electrical activity. Body surface mapping has greater sensitivity in detecting AMI in the inferoposterior portions of the left ventricle and the right ventricle. Portable hardware and user-friendly software coupled with an easily applied disposable torso vest containing the electrodes produce a 12-lead ECG, 80-lead ECG, and color contour torso or flat map showing ECG changes. Recent studies support the use of 80-lead body surface mapping for detecting AMI in the emergency department.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.988
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
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 head0.042
GPT teacher head0.376
Teacher spread0.334 · 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 designOther design
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

Citations3
Published2012
Admission routes1
Has abstractyes

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