Article

Cardiac mortality of premature ventricular complexes in healthy people in Japan

Division of Community and Family Medicine, Jichi Medical University School of Medicine, Shimotsuke, Japan.
Journal of Cardiology (Impact Factor: 2.78). 02/2010; 56(1):23-6. DOI: 10.1016/j.jjcc.2010.01.005
Source: PubMed

ABSTRACT

Premature ventricular complexes (PVCs) are frequently encountered in healthy people. But the association between PVCs and cardiac events is not well established in Japan. We investigated the association of PVCs and cardiac deaths in people without cardiovascular disease in the Jichi Medical School (JMS) Cohort study.
We conducted a prospective cohort study in 12 districts in Japan as part of the JMS cohort study. Baseline data were obtained between April 1992 and July 1995. We excluded subjects who had myocardial infarction and stroke and those who had not received 12-lead electrocardiograms. Cox's proportional hazard model was used to calculate the hazard ratios (HRs) of cardiovascular mortality of subjects with PVCs, using subjects without PVCs as reference.
A total of 11,158 participants (4333 males and 6825 females) were analyzed. Participants were followed for an average of 11.9 years. PVCs were present in 1.4% of men and 1.1% of women. There were 92 cardiac deaths (47 males and 45 females) during the follow-up period. In crude cardiovascular mortality, HRs (95% confidence interval [CI]) were 5.29 (1.64-17.0) in males and 2.14 (0.29-15.5) in females. Age-adjusted HRs were 3.73 (1.16-12.0) and 0.98 (0.13-7.21), respectively. After further adjustment for body mass index, systolic blood pressure, total cholesterol level, high-density lipoprotein-cholesterol, and blood glucose, HRs were 3.98 (1.21-13.0) and 0.95 (0.13-7.11), respectively.
We conclude that PVCs are a predictive factor for cardiac death in men without structural heart disease.

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    • "Several studies have shown, e.g., [7], that PVCs have a potential to be used as a predictor of sudden cardiac death in men even without recognized heart disease. This particularly applies if frequent PVCs occur during physical exercise [2], [8], and especially during the phase of recovery [2], [9]. "
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    ABSTRACT: This work introduces a method for detection of premature ventricular contractions (PVCs) in photoplethysmogram (PPG). The method relies on 6 features, characterising PPG pulse power, and peak-to-peak intervals. A sliding window approach is applied to extract the features, which are later normalized with respect to an estimated heart rate. Artificial neural network with either linear and non-linear outputs was investigated as a feature classifier. PhysioNet databases, namely, the MIMIC II and the MIMIC, were used for training and testing, respectively. After annotating the PPGs with respect to synchronously recorded electrocardiogram, two main types of PVCs were distinguished: with and without the observable PPG pulse. The obtained sensitivity and specificity values for both considered PVC types were 92.4/99.9% and 93.2/99.9%, respectively. The achieved high classification results form a basis for a reliable PVC detection using a less obtrusive approach than the electrocardiography-based detection methods.
    No preview · Article · Oct 2015 · IEEE Transactions on Biomedical Circuits and Systems
    • "However, the severity of PVCs in people with a normal heart is controversial [10] [11]. Some studies point out that PVCs can lead to ischemic heart disease and sudden cardiac death in apparently healthy subjects [10] [11] [12]. In an elegant metaanalysis , Lee and collaborators [13] discuss the prognostic relevance of PVCs in apparently healthy adult subjects. "

    No preview · Article · Sep 2015 · Epilepsy & Behavior
    • "Several studies have shown, e.g., [7], that PVCs have a potential to be used as a predictor of sudden cardiac death in men even without recognized heart disease. This particularly applies if frequent PVCs occur during physical exercise [2], [8], and especially during the phase of recovery [2], [9]. "
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    ABSTRACT: The purpose of this study was the development and investigation of the automatic Premature Ventricular Contraction (PVC) detection and classification method using Photoplethysmographic (PPG) signals. The main issue of using PPG for arrhythmia detection are the artefacts which may be falsely detected as an arrhythmic pulses. The method is based on 6 PPG features, obtained in 12 s analysis frame. The features are peak-to-peak intervals and PPG power derived features. The fundamental frequency of the PPG was used for feature extraction and normalization. The Artificial Neural Network with back-propagation was used for the PPG pulse classification. The PPG signals from Physionet MIMIC II and MIMIC databases were used for algorithm training and testing. PPG were annotated by referring to synchronously registered ECG signals. The method was evaluated by calculating sensitivity and specificity which for the two main PVC types are 96,05 / 95,37 % and 99,85 / 99,80 %, respectively. The study results suggest that PPG can be used for the reliable PVC detection.
    No preview · Article · Dec 2014
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