Olson method for locating and calculating the extent of transmural ischemic areas at risk of infarction

Olson, Charles W.; Wagner, Galen S.; Terkelsen, Christian Juhl; Stickney, Ronald E.; Lim, Tobin; Pahlm, Olle; Estes, E. Harvey

doi:10.1016/j.jelectrocard.2014.04.005

Cited by 7 publications

(11 citation statements)

References 14 publications

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“…We compared a model-based culprit assessment algorithm (Olson Automated Method [10]) with an expert-rule based culprit assessment method, operating on either visually assessed J-point amplitudes or on the computermeasured J-point amplitudes in the ECGs of 53 ACS patients recorded prior to PCI. In all patients a complete coronary occlusion was angiographically demonstrated.…”

Section: Discussionmentioning

confidence: 99%

“…The Olson method [10] is based on a model that divides the left ventricle (LV) into 12 segments, according to the display format of Selvester et al [15] (Fig. 2).…”

Section: Assessment Of the Culprit Location By The Model-based Methodsmentioning

confidence: 99%

“…The culprit artery assessments by the model-based Olson method [10], using computer-based ST-segment deviation measurements, and by the expert-rule based method, using either visual or computer-based ST-segment deviation measurements, were compared with the culprit lesions as found during coronary angiography. Misclassifications were categorized in one of the six possible categories: assessed LAD-true LCX, assessed LCX-true LAD, assessed LCX-true RCA, assessed RCA-true LCX, assessed RCA-true LAD and assessed LAD-true RCA misclassifications.…”

Section: Comparison Of the Model-based And Expert-rule Based Methodsmentioning

confidence: 99%

“…If so, this could help to optimize emergency reperfusion procedures. The purpose of our study is to compare, in a database with ECGs of patients with acute ischemia recorded prior to cardiac catheterization, a model-based automated method (Olson method) [10], using computer-based ST-segment deviation measurements, with an expert-rule based method, using either visual or computer-based ST-segment deviation measurements, for the identification of the culprit coronary artery.…”

Section: Introductionmentioning

confidence: 99%

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Comparison of model-based and expert-rule based electrocardiographic identification of the culprit artery in patients with acute coronary syndrome

Kamphuis¹,

Wagner²,

Pahlm³

et al. 2015

Journal of Electrocardiology

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Section: Discussionmentioning

confidence: 99%

“…The Olson method [10] is based on a model that divides the left ventricle (LV) into 12 segments, according to the display format of Selvester et al [15] (Fig. 2).…”

Section: Assessment Of the Culprit Location By The Model-based Methodsmentioning

confidence: 99%

Section: Comparison Of the Model-based And Expert-rule Based Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Comparison of model-based and expert-rule based electrocardiographic identification of the culprit artery in patients with acute coronary syndrome

Kamphuis¹,

Wagner²,

Pahlm³

et al. 2015

Journal of Electrocardiology

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“…5 Electrocardiographic Decision Support -Myocardial Ischaemia (EDS-MI), previously referred to as 'the Olson method', is a graphical decision support for detection and localization of acute transmural ischaemia. 6 EDS-MI has previously proved to accurately identify the culprit artery in patients with acute coronary occlusion. 7 A recent study indicated that EDS-MI has higher sensitivity than STEMI criteria.…”

Section: Introductionmentioning

confidence: 99%

Diagnostic Accuracy Of The Electrocardiographic Decision Support – Myocardial Ischaemia (EDS-MI) Algorithm In Detection Of Acute Coronary Occlusion

Lindow

Pahlm

Olson³

et al. 2018

European Heart Journal: Acute Cardiovascular Care

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Electrocardiographic Decision Support - Myocardial Ischaemia (EDS-MI) is a graphical decision support for detection and localization of acute transmural ischaemia. A recent study indicated that EDS-MI performs well for detection of acute transmural ischaemia. However, its performance has not been tested in patients with non-ischaemic ST-deviation. We aimed to optimize the diagnostic accuracy of EDS-MI in patients with verified acute coronary occlusion as well as patients with non-ischaemic ST deviation and compare its performance with STEMI criteria. We studied 135 patients with non-ischaemic ST deviation (perimyocarditis, left ventricular hypertrophy, takotsubo cardiomyopathy and early repolarization) and 117 patients with acute coronary occlusion. In 63 ischaemic patients, the extent and location of the ischaemic area (myocardium at risk) was assessed by both cardiovascular magnetic resonance imaging and EDS-MI. Sensitivity and specificity of ST elevation myocardial infarction criteria were 85% (95% confidence interval (CI) 77, 90) and 44% (95% CI 36, 53) respectively. Using EDS-MI, sensitivity and specificity increased to 92% (95% CI 85, 95) and 81% (95% CI 74, 87) respectively (p=0.035 and p<0.001). Agreement was strong (83%) between cardiovascular magnetic resonance imaging and EDS-MI in localization of ischaemia. Mean myocardium at risk was 32% (± 10) by cardiovascular magnetic resonance imaging and 33% (± 11) by EDS-MI when the estimated infarcted area according to Selvester QRS scoring was included in myocardium at risk estimation. In conclusion, EDS-MI increases diagnostic accuracy and may serve as an automatic decision support in the early management of patients with suspected acute coronary syndrome. The added clinical benefit in a non-selected clinical chest pain population needs to be assessed.

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QRS, ST and T changes of acute transmural myocardial ischemia: Overview editorial

Pahlm

Wagner

2014

Journal of Electrocardiology

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Olson method for locating and calculating the extent of transmural ischemic areas at risk of infarction

Cited by 7 publications

References 14 publications

Comparison of model-based and expert-rule based electrocardiographic identification of the culprit artery in patients with acute coronary syndrome

Comparison of model-based and expert-rule based electrocardiographic identification of the culprit artery in patients with acute coronary syndrome

Diagnostic Accuracy Of The Electrocardiographic Decision Support – Myocardial Ischaemia (EDS-MI) Algorithm In Detection Of Acute Coronary Occlusion

QRS, ST and T changes of acute transmural myocardial ischemia: Overview editorial

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