MétaCan
Menu
Back to cohort
Record W3215724665 · doi:10.7860/jcdr/2021/50365.15207

Can the 12-Lead Electrocardiogram Predict Myocardial Viability?

2021· article· en· W3215724665 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJOURNAL OF CLINICAL AND DIAGNOSTIC RESEARCH · 2021
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicinePrecordial examinationCardiologyInternal medicineCoronary artery diseaseElectrocardiographyNuclear medicine

Abstract

fetched live from OpenAlex

Introduction: In patients with coronary artery disease and left ventricular dysfunction, the assessment of myocardial viability, prior to revascularisation has been shown to be of significant benefit. Most methods to assess myocardial viability such as Positron Emission Tomography (PET) and Cardiac MRI (CMR) are not readily available in resource constrained settings. The present study sought to determine if an easily available and inexpensive tool, such as the 12-lead surface Electrocardiogram (ECG) can be used as a screening tool to assess for myocardial viability. It is hypothesised that the R wave height as a marker of electrical activity would correlate with viability. Aim: To determine if the surface ECG can be used to predict myocardial viability. Materials and Methods: This retrospective study was conducted at the Christian Medical College and Hospital, Vellore, Tamil Nadu, India. Among all patients who had undergone CMR viability assessment as part of their routine care between February 2008 and October 2017, and analysis and preliminary write up was done between November 2017 and Decemeber 2018, 119 patients with previous anterior wall myocardial infarctions were identified. The 12-Lead ECGs of these patients were assessed for the height of R wave in lead V3 and sum of R wave heights in all precordial leads. Myocardial viability was assessed based on the extent of Late Gadolinium Enhancement (LGE) on CMR. Measures of diagnostic accuracy including sensitivity, specificity, predictive values and likelihood ratios were calculated. Results: It was found that a R wave height of less than 3 mm in lead V3 was 90.3% sensitive for the detection of non viable myocardium. Similarly, when the sum of the R wave heights in all precordial leads was less than 28.5 mm, it was 93.2% sensitive for the detection of non viable myocardium. Conclusion: In patients with previous anterior wall myocardial infarctions when the R wave height was less than 3 mm in lead V3, it was 90.3 % sensitive to identify those with non viable Left Anterior Descending artery (LAD) territory. The 12-Lead ECG is therefore a sensitive, inexpensive and easily available screening test to assess for LAD territory non viability.

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.

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)0.010
metaresearch head score (Gemma)0.162
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.153
Threshold uncertainty score0.963

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.162
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.096
GPT teacher head0.451
Teacher spread0.355 · 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