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Record W2409005826

Simple, quantitative body surface potential map parameters in the diagnosis of remote Q wave and non-Q wave myocardial infarction.

2004· article· en· W2409005826 on OpenAlexaff
Mihály Medvegy, P. Savard, Arnold Pintér, G Tremblay, James Nasmith, Donald Palisaitis, Gábor Zoltán Duray, István Préda, Réginald Nadeau

Bibliographic record

VenuePubMed · 2004
Typearticle
Languageen
FieldMedicine
TopicCardiac electrophysiology and arrhythmias
Canadian institutionsUniversité de MontréalHôpital du Sacré-Cœur de Montréal
Fundersnot available
KeywordsMedicineMyocardial infarctionInfarctionCardiologyInternal medicineReceiver operating characteristicQT intervalBody surfaceScintigraphyNuclear medicineGeometryMathematics
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: Body surface potential mapping has been shown to be a useful tool in the diagnosis and localization of remote non-Q wave and Q wave myocardial infarction, but human expertise is required to interpret the maps. OBJECTIVE: To identify quantitative body surface potential mapping parameters that could enable a computer-based diagnosis. METHODS: Body surface isopotential maps (63 unipolar leads) were recorded in 86 patients with remote Q wave and 71 patients with remote non-Q wave myocardial infarction. Twenty-four healthy adults served as control subjects. Myocardial infarctions were classified using standard electrocardiogram leads in the acute and chronic phases, and were validated by coronary angiography, ventriculography and thallium scintigraphy. RESULTS: Two simple quantitative parameters with high diagnostic power were identified: the time interval between the peak minimum and the peak maximum potentials (time-shift), and the ratio of these potentials (maximum to minimum ratio [max/min]). Both parameters showed significant differences between infarction patients and normal control subjects, and optimum cut-off values were determined using receiver operating characteristic curves (anterior infarction: time-shift of -4 ms or less, max/min of 0.6 or less; posterior infarction: time-shift of 8 ms or greater, max/min of 1.25 or greater). The sensitivities of the two parameters were 100% and 97%, and the specificities were 99% and 100%, respectively, in the anterior Q wave infarction group, compared with sensitivities of 88% and 100%, and specificities of 94% and 95%, respectively, in the posterior Q wave infarction group. In the anterior non-Q wave infarction group, sensitivity was 35% for both parameters, specificity was 100% for both parameters, and only infarctions associated with a low ejection fraction were detected, indicating that infarction size may influence the power of the tests. CONCLUSIONS: Time-shift and max/min are two new, simple, powerful parameters for infarction diagnosis and may also be suitable for automated, computer-based processing.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.020
GPT teacher head0.248
Teacher spread0.228 · 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 source (direct Gemma or distilled Codex), 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

Citations7
Published2004
Admission routes1
Has abstractyes

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