Assessment of left ventricular systolic function using a single-channel ECG monitor with photoplethysmography based on machine learning models

Сагирова, Ж. Н.; Kuznetsova, Natalia; Suvorov, А. Yu.; Gognieva, Daria; Kulikov, V.M.; Чомахидзе, П. Ш.; Андреев, Д. А.; Kopylov, Philipp

doi:10.17116/kardio20231601146

Cited by 1 publication

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“…Statistical processing was carried out using the R programming language v4.2 and Python v.3.10 [^R] [10,11].…”

Section: Methodsmentioning

confidence: 99%

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Single Channel Electrocardiography Optimizes the Diagnostic Accuracy of Bicycle Ergometry

Marzoog,

Abdullaev,

Suvorov

et al. 2024

Preprint

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Background: Cardiovascular disease (CVD) such as ischemic heart disease impacts the people quality of life and has the highest mortality rate in the globe. This returns to the poor diagnostic and therapeutic strategies including the early prevention methods. Aims: To assess the changes in the single channel electrocardiography (SCECG) in rest and on exercise test in patients with vs without ischemic heart disease confirmed by stress computed tomography myocardial perfusion (CTP) imaging. Objectives: Ischemic heart disease patients frequently have preventable risk factors and causes that lead to the disease appearance. However, the lack of the proper diagnostic and prevention tools remains a global challenge in or era despite the current scientific advances. Material and methods: A cohort, prospective, single center observational study included 38 participants from Moscow. The participants aged ≥ 40 years and given a written consent to participate in the study. The participants subdivided into two groups according to the presence or absence of the myocardial perfusion defect on the CTP with vasodilatation stress-test. Both groups (group 1 with myocardial perfusion defect (n=19), group 2 without myocardial perfusion defect (n=19)) passed general primary consultation by cardiologist, anthropometric measurements, recording 3-minutes single channel electrocardiography (ECG) in rest before and just after exercise test, blood pressure and pulse rate using automatic tonometer, echocardiography, cardio-ankle vascular index, performing ergometry, immediately repeating the single channel ECG, then performing CTP. LASSO regression with nested cross-validation was used to find association between Cardio-Qvark parameters and the existence of the perfusion defect. Statistical processing was carried out using the R programming language v4.2 and Python v.3.10 [^R]. Results: The study results showed that the single channel ECG have significantly higher diagnostic accuracy in compare to bicycle ergometry. The specificity 63.2 % [95 % confidence interval (CI); 0.391 ; 0.833], sensitivity 73.7 % [95 % CI ; 0.533 ; 0.929], and accuracy of the diagnostic method using exhaled breath analysis, area under the curve (AUC) 68.4 % [95 % CI ; 0.527 ; 0.817]. Conclusion: Single channel ECG (Cardio-Qvark) has the potential to improve the diagnostic accuracy of the bicycle ergometry. Other: Further investigations required to uncover the hidden capabilities of Cardio-Qvark in the diagnosis of ischemic heart disease.

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“…Statistical processing was carried out using the R programming language v4.2 and Python v.3.10 [^R] [10,11].…”

Section: Methodsmentioning

confidence: 99%

“…Statistical processing was carried out using the R programming language v4.2 and Python v.3.10 [^R] [36, 37] . Statistically significant values considered at p<0.05.…”

Section: Data Collectionmentioning

confidence: 99%

Single Channel Electrocardiography Optimizes the Diagnostic Accuracy of Bicycle Ergometry

Marzoog,

Abdullaev,

Suvorov

et al. 2024

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

Assessment of left ventricular systolic function using a single-channel ECG monitor with photoplethysmography based on machine learning models

Cited by 1 publication

References 22 publications

Single Channel Electrocardiography Optimizes the Diagnostic Accuracy of Bicycle Ergometry

Single Channel Electrocardiography Optimizes the Diagnostic Accuracy of Bicycle Ergometry

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