Key result
A predictive logistic regression model incorporating five clinical parameters demonstrated 84.5% diagnostic accuracy in assessing the risk of true ventricular arrhythmias in patients with ICDs.
Why the study?
Estimating the potential risk of life-threatening ventricular arrhythmias is needed to guide individual ICD programming options to reduce unnecessary electrotherapy and enable accurate drug therapy monitoring.
Observational (n=83)
No
Effect estimate: OR 33.3
p-value: p=<0.001
A predictive model based on 5 clinical parameters can estimate the risk of life-threatening ventricular arrhythmias in primary prevention ICD patients, potentially guiding individualized programming to reduce unnecessary shocks.
May support ICD risk stratification; leaves open prospective validation before guiding programming.
Clinical data analysis of 83 patients with implantable cardioverter-defibrillators (ICDs) for sudden cardiac death (SCD) primary prevention has been done. We revealed 5 parameters associated with the detection of life-threatening ventricular arrhythmias. These parameters formed the basis for constructing a logistic regression model. The model makes it possible to obtain the probability of occurrence of a specific event depending on the severity of the predictive parameters and the degree of its influence (risk of true ventricular arrhythmias detection). Estimating the potential risk of the life-threatening arrhythmias, individual programming options are required in implantable cardioverter-defibrillators (ICDs) to reduce the amount of unnecessary electrotherapy, as well as more accurate monitoring of the patient's drug therapy.
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Лебедева et al. (2018) conducted an observational in Primary prevention of sudden cardiac death with implantable cardioverter-defibrillators (ICDs) (n=83). Predictive logistic regression model for ICD programming vs. Conventional ICD programming was evaluated on Detection of true ventricular tachycardia/fibrillation (OR 33.3, p=<0.001). A predictive logistic regression model incorporating five clinical parameters demonstrated 84.5% diagnostic accuracy in assessing the risk of true ventricular arrhythmias in patients with ICDs.
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