042 EPICARDIAL POTENTIALS DERIVED FROM THE BODY SURFACE POTENTIAL MAP USING INVERSE ELECTROCARDIOGRAPHY IMPROVE DIAGNOSIS OF ACUTE MYOCARDIAL INFARCTION: A PROSPECTIVE STUDY
Bibliographic record
Abstract
Background Epicardial potentials (EP) derived from body surface potentials using a thoracic volume conductor model (TVCM) improve acute myocardial infarction (AMI) diagnosis. In this study, we compared EP derived from the 80-lead body surface potential map (BSPM) using a TVCM developed from CT imaging with other electrocardiographic techniques in AMI diagnosis. Methods In this prospective study, consecutive patients presenting to both the ED and pre-hospital coronary care unit between August 2009 and August 2011 with acute ischaemic-type chest pain at rest were enrolled. At first medical contact a 12-lead electrocardiogram (ECG) and BSPM were recorded. Cardiac troponin-T (cTnT) was sampled 12 h after symptom onset. AMI was diagnosed when cTnT ≥0.1 µg/l. Patients were excluded from analysis if they had bundle branch block, permanent pacemaker, left ventricular hypertrophy by voltage criteria or concomitant digitalis therapy. A cardiologist assessed the 12-lead ECG for STEMI by Minnesota criteria and the BSPM. BSPM ST-elevation (STE) was ≥0.2 mV in anterior, ≥0.1 mV in lateral, inferior, right ventricular (RV) or high right anterior and ≥0.05 mV in posterior territories indicating AMI. To derive EP, the 80-lead BSPM data were interpolated (Laplacian method) to yield values at 352-nodes of a Dalhouse torso. Using an inverse solution based on the boundary element method employing Tikhonov regularisation, EP at 98 cardiac nodes positioned within a standard TVCM were estimated. EP ≥0.3 mV defined STE. A cardiologist blinded to both the 12-lead ECG and BSPM interpreted the EP map. Results Enrolled were 400 patients (age 62±13 years; 57% male): 80 patients had exclusion criteria. Of the remaining 320 patients, 180 (56%) had AMI. Of these 180 patients, 117 had STEMI by Minnesota criteria (sensitivity 65%, specificity 89%) and 146 had BSPM STE (sensitivity 81%, specificity 90%). EP STE occurred in 158 patients (sensitivity 88%, specificity 95%, p<0.001). Of those with non-STEMI by Minnesota criteria on 12-lead ECG and AMI (n=63), 29 (46%) patients had STE detected by BSPM with a further 12 (19%) patients having STE detected only using EP derived from the BSPM using a TVCM. Overall, 41 (65%) patients with both a non-diagnostic 12-lead ECG at presentation and AMI had STE detected only by BSPM or derived EP. In 32/41 (78%) patients, STE was detected in the posterior or RV territories. All 41 patients had AMI diagnosed by EP. Conclusions Among those with an initial non-diagnostic 12-lead ECG, EP derived from BSPM using a TVCM significantly improves AMI diagnosis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".