Key result
A novel 5-lead ECG algorithm identified the culprit artery in inferior STEMI with a sensitivity of 72.3%, specificity of 80.9%, and an AUC of 0.766, outperforming four previously published algorithms.
Why the study?
Identifying the culprit artery can aid management of inferior STEMI, but previously published algorithms to identify the infarct-related artery are suboptimal.
Does a novel 5-lead ECG algorithm improve the identification of the culprit artery in patients with inferior STEMI compared to previously published algorithms?
Cohort (n=342)
Does a novel 5-lead ECG algorithm improve the identification of the culprit artery in patients with inferior STEMI compared to previously published algorithms?
Answers are grounded in this paper and cite their sources.
May improve culprit localization in inferior STEMI; extends prior algorithms with RCT validation.
BACKGROUND: Identification of the culprit artery can be helpful in the management of inferior infarction with ST-segment elevation myocardial infarction. Some studies suggest that previously published algorithms intended to help identify the infarct-related artery are suboptimal. Our aim is to develop a better method to localise the culprit artery on the basis of the 12-lead ECG. PATIENTS AND METHODS: We analysed the ECG and coronary angiograms of two different cohorts of patients with inferior ST-segment elevation myocardial infarction. Patients from the first cohort were labelled the derivative cohort (group A), whereas patients in the second cohort were labelled the validation cohort (group B). ST-segment elevation was measured in each lead, and a multiple logistic regression analysis was carried out to determine the best equation to predict the culprit artery. A derived algorithm was then applied to the validation cohort. Next, our algorithm was applied to the total cohort of both groups and compared with four different previously published algorithms. We analysed differences in sensitivity, specificity and area under the curve (AUC). RESULTS: We included 252 patients in the derivative group and 90 in the validation group. The multiple models analysis concluded that the best model should include five leads. This model was validated by internal bootstrapping with 1000 repetitions in group A and externally in group B. The resultant algorithm was as follows: (ST-elevation in III + aVF + V3) - (ST-elevation in II + V6) less than 0.75 mm means that the culprit artery is the left circumflex artery (Cx). If the result is at least 0.75, the culprit artery is the right coronary artery. The total group of both cohorts comprised 342 patients, aged 61.2 ± 12.4 years, of whom 19.6% were female and 80.4% were male. The Cx was the culprit artery in 67 (19.6%) patients. Our algorithm had a sensitivity of 72.3, a specificity of 80.9 and an AUC of 0.766. The AUC value was better compared with the other algorithms. CONCLUSION: The best algorithm to localise the culprit artery includes ST-elevation in leads II and V6 related to Cx, and ST-elevation in leads III, aVF and V3 related to right coronary artery. Our algorithm has been validated internally and externally, and works better than other previously published algorithms.
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Ruiz-Mateos et al. (2019) conducted a cohort in Inferior ST-segment elevation myocardial infarction (n=342). Derived 5-lead ECG algorithm vs. Four previously published algorithms was evaluated on Identification of the culprit artery (AUC 0.766). A novel 5-lead ECG algorithm identified the culprit artery in inferior STEMI with a sensitivity of 72.3%, specificity of 80.9%, and an AUC of 0.766, outperforming four previously published algorithms.
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