Artificial Intelligence Detection of Occlusive Myocardial Infarction from Electrocardiograms Interpreted as “Normal” by Conventional Algorithms
Abstract
:1. Introduction
2. Methods
2.1. Study Design
- (1)
- The diagnosis of acute type 1 MI with rise and/or fall of troponin level; and
- (2)
- Angiographic culprit with intervention; and
- (3)
- One of the following:
- (A)
- TIMI-0-2 flow;
- (B)
- TIMI-3 flow or unknown flow with large acute infarct size, as determined by one of the following:
- (i)
- Very elevated troponin defined as follows:
- (a)
- Peak high-sensitivity troponin I level > 5000 ng/L;
- (b)
- Peak 4th generation troponin I > 10 ng/mL;
- (c)
- Peak high-sensitivity troponin T > 1000 ng/L;
- (d)
- Peak 4th generation troponin T > 1.0 ng/mL.
- (ii)
- New regional wall motion abnormality (WMA) on echocardiography if peak troponin levels were not available or were below the very high threshold.
2.2. Data Elements
2.3. Artificial Intelligence Algorithm
2.4. Primary Outcome
2.5. Statistical Analysis
3. Results
3.1. Participants
3.2. CCA Interpretations of the Initial ECG
3.3. AI Interpretations of the Initial ECG
3.4. Per-ECG Diagnostic Performance
3.5. AI Performance with CCA “Normal” ECGs
3.6. CCA vs. AI, Case by Case
- Cases in which both the CCA and the AI system diagnosed acute MI.
- Cases in which the CCA did not diagnose acute MI, but the AI system did.
- Cases in which neither the CCA nor the AI system diagnosed acute MI.
- Cases in which the CCA diagnosed MI, but the AI system did not.
Common ECG Features
4. Discussion
5. Limitations
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Otherwise Normal ECG Reads | Total | Abnormal ECG Reads | Total |
---|---|---|---|
Sinus Bradycardia | 7 | Nonspecific ST-T Wave Abnormality | 7 |
Sinus Tachycardia | 1 | Consider Subendocardial Injury | 3 |
Marked Sinus Arrhythmia | 1 | Moderate ST Depression | 2 |
Frequent PVCs | 1 | Right Bundle Branch Block | 2 |
Early Repolarization | 1 | Anterior MI of Indeterminate Age | 1 |
- | - | Possible Acute Pericarditis | 1 |
- | - | Possible Left Atrial Enlargement | 1 |
- | - | Prolonged QT | 1 |
Total “Otherwise Normal” | 11 | Total “Abnormal” | 18 |
Case Number | Interpretation Software | ECG 1 | ECG 2 | ECG 3 | ECG 4 |
---|---|---|---|---|---|
1 | Unknown CCA | Normal | Unknown | STEMI (Assumed) | |
QoH | OMI Mid | (+150 Min) | |||
3 | Unknown CCA | Normal | Unknown | STEMI (Assumed) | |
QoH | Not OMI High | OMI High | (+40 Min) | ||
11 | Zoll Algorithm | STEMI (Assumed) | |||
QoH | OMI High | ||||
14 | Marquette 12 SL | Normal | Normal | Abnormal | STEMI |
QoH | Not OMI High | OMI High | (+120 Min) | ||
21 | Unknown CCA | Normal | STEMI (Assumed) | ||
QoH | OMI High | (Unknown time) | |||
30 | Marquette 12 SL | STEMI | |||
QoH | OMI High | ||||
41 | Marquette 12 SL | Normal | STEMI | ||
QoH | OMI High | (+125 Min) | |||
42 | Marquette 12 SL | Normal | STEMI (Assumed) | ||
QoH | OMI High | (+45 Min) |
Case Number | Interpretation Software | ECG 1 | ECG 2 | ECG 3 |
---|---|---|---|---|
6 | Unknown CCA | Normal | ||
QoH | Not OMI Mid | |||
8 | Marquette 12 SL | Otherwise Normal | ||
QoH | Not OMI Mid | |||
16 | Marquette 12 SL | Normal | Otherwise Normal | Normal |
QoH | Not OMI High | Not OMI High | Not OMI High | |
31 | Unknown CCA | Normal | ||
QoH | Nor OMI Low |
Culprit Artery | Number of Cases |
---|---|
LAD | 18 |
Diagonal | 4 |
Circumflex | 2 |
Obtuse Marginal | 7 |
RCA | 12 |
PDA | 2 |
Ramus | 1 |
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Share and Cite
Karim, S.R.; Helseth, H.C.; Baker, P.O.; Keller, G.A.; Meyers, H.P.; Herman, R.; Smith, S.W. Artificial Intelligence Detection of Occlusive Myocardial Infarction from Electrocardiograms Interpreted as “Normal” by Conventional Algorithms. J. Pers. Med. 2025, 15, 130. https://doi.org/10.3390/jpm15040130
Karim SR, Helseth HC, Baker PO, Keller GA, Meyers HP, Herman R, Smith SW. Artificial Intelligence Detection of Occlusive Myocardial Infarction from Electrocardiograms Interpreted as “Normal” by Conventional Algorithms. Journal of Personalized Medicine. 2025; 15(4):130. https://doi.org/10.3390/jpm15040130
Chicago/Turabian StyleKarim, Shifa R., Hans C. Helseth, Peter O. Baker, Gabriel A. Keller, H. Pendell Meyers, Robert Herman, and Stephen W. Smith. 2025. "Artificial Intelligence Detection of Occlusive Myocardial Infarction from Electrocardiograms Interpreted as “Normal” by Conventional Algorithms" Journal of Personalized Medicine 15, no. 4: 130. https://doi.org/10.3390/jpm15040130
APA StyleKarim, S. R., Helseth, H. C., Baker, P. O., Keller, G. A., Meyers, H. P., Herman, R., & Smith, S. W. (2025). Artificial Intelligence Detection of Occlusive Myocardial Infarction from Electrocardiograms Interpreted as “Normal” by Conventional Algorithms. Journal of Personalized Medicine, 15(4), 130. https://doi.org/10.3390/jpm15040130