https://ir.lib.ncu.edu.tw/handle/987654321/18625 Search the Channel s https://ir.lib.ncu.edu.tw/simple-search https://ir.lib.ncu.edu.tw/handle/987654321/50665 title: The Prognostic Value of Non-Linear Analysis of Heart Rate Variability in Patients with Congestive Heart Failure-A Pilot Study of Multiscale Entropy abstract: Aims: The influences of nonstationarity and nonlinearity on heart rate time series can be mathematically qualified or quantified by multiscale entropy (MSE). The aim of this study is to investigate the prognostic value of parameters derived from MSE in the patients with systolic heart failure. Methods and Results: Patients with systolic heart failure were enrolled in this study. One month after clinical condition being stable, 24-hour Holter electrocardiogram was recording. MSE as well as other standard parameters of heart rate variability (HRV) and detrended fluctuation analysis (DFA) were assessed. A total of 40 heart failure patients with a mea age of 56+/-16 years were enrolled and followed-up for 684+/-441 days. There were 25 patients receiving beta-blockers treatment. During follow-up period, 6 patients died or received urgent heart transplantation. The short-term exponent of DFA and the slope of MSE between scale 1 to 5 were significantly different between patients with or without b-blockers (p = 0.014 and p = 0.028). Only the area under the MSE curve for scale 6 to 20 (Area(6-20)) showed the strongest predictive power between survival (n = 34) and mortality (n = 6) groups among all the parameters. The value of Area(6-20) <= 21.2 served as a significant predictor of mortality or heart transplant (p = 0.0014). Conclusion: The area under the MSE curve for scale 6 to 20 is not relevant to beta-blockers and could further warrant independent risk stratification for the prognosis of CHF patients. <br> Tue, 27 Mar 2012 09:50:45 GMT https://ir.lib.ncu.edu.tw/handle/987654321/50664 title: Temporal Associations between Weather and Headache: Analysis by Empirical Mode Decomposition abstract: Background: Patients frequently report that weather changes trigger headache or worsen existing headache symptoms. Recently, the method of empirical mode decomposition (EMD) has been used to delineate temporal relationships in certain diseases, and we applied this technique to identify intrinsic weather components associated with headache incidence data derived from a large-scale epidemiological survey of headache in the Greater Taipei area. Methodology/Principal Findings: The study sample consisted of 52 randomly selected headache patients. The weather time-series parameters were detrended by the EMD method into a set of embedded oscillatory components, i.e. intrinsic mode functions (IMFs). Multiple linear regression models with forward stepwise methods were used to analyze the temporal associations between weather and headaches. We found no associations between the raw time series of weather variables and headache incidence. For decomposed intrinsic weather IMFs, temperature, sunshine duration, humidity, pressure, and maximal wind speed were associated with headache incidence during the cold period, whereas only maximal wind speed was associated during the warm period. In analyses examining all significant weather variables, IMFs derived from temperature and sunshine duration data accounted for up to 33.3% of the variance in headache incidence during the cold period. The association of headache incidence and weather IMFs in the cold period coincided with the cold fronts. Conclusions/Significance: Using EMD analysis, we found a significant association between headache and intrinsic weather components, which was not detected by direct comparisons of raw weather data. Contributing weather parameters may vary in different geographic regions and different seasons. <br> Tue, 27 Mar 2012 09:50:43 GMT https://ir.lib.ncu.edu.tw/handle/987654321/50663 title: Reduced physiologic complexity is associated with poor sleep in patients with major depression and primary insomnia abstract: Background: Depression is known to be associated with altered cardiovascular variability and increased cardiovascular comorbidity, yet it is unknown whether altered cardiac autonomic function in depression is associated with insomnia, a common symptom comorbid with depression. This study aimed to investigate the long-term diurnal profile of autonomic function as measured by heart rate variability (HRV) in both major depression and primary insomnia patients. Method: A total of 52 non-medicated patients with major depression, 47 non-medicated patients with primary insomnia, and 88 matched controls without insomnia were recruited. Each subject was assessed by means of sleep and mood questionnaires and underwent twenty-four-hour ambulatory electrocardiogram monitoring. Standard HRV analysis and a well-validated complexity measure, multiscale entropy, were applied to comprehensively assess the diurnal profiles of autonomic function and physiologic complexity in our study sample. Results: Compared with the controls, the patients with major depression and those with primary insomnia exhibited significant reductions in parasympathetic-related HRV indices, and this association was mainly driven by the presence of poor sleep. Both groups of patients also exhibited significant reductions in physiologic complexity during the sleep period as compared with the healthy controls. Alterations in HRV indices were correlated with perceived sleep questionnaire scores but not with depression scales. Conclusions: Our findings suggest a pivotal role of sleep disturbance in regulating cardiovascular variability in major depression and primary insomnia patients. These findings could highlight the importance of treating insomnia as an independent disease rather than a symptom. (C) 2010 Elsevier B.V. All rights reserved. <br> Tue, 27 Mar 2012 09:50:41 GMT https://ir.lib.ncu.edu.tw/handle/987654321/50662 title: Multiscale Entropy Analysis of Pulse Wave Velocity for Assessing Atherosclerosis in the Aged and Diabetic abstract: This study proposed a dynamic pulse wave velocity (PWV)-based biomedical parameter in assessing the degree of atherosclerosis for the aged and diabetic populations. Totally, 91 subjects were recruited from a single medical institution between July 2009 and October 2010. The subjects were divided into four groups: young healthy adults (Group 1, n = 22), healthy upper middle-aged adults (Group 2, n = 28), type 2 diabetics with satisfactory blood sugar control (Group 3, n = 21), and unsatisfactory blood sugar control (Group 4, n = 20). A self-developed six-channel electrocardiography (ECG)-PWV-based equipment was used to acquire 1000 successive recordings of PWV(foot) values within 30 min. The data, thus, obtained were analyzed with multiscale entropy (MSE). Large-scale MSE index (MEI(LS)) was chosen as the assessment parameter. Not only did MEI(LS) successfully differentiate between subjects in Groups 1 and 2, but it also showed a significant difference between Groups 3 and 4. Compared with the conventional parameter of PWV(foot) and MEI on R-R interval [i.e., MEI (RRI)] in evaluating the degree of atherosclerotic change, the dynamic parameter, MEI(LS) (PWV), could better reflect the impact of age and blood sugar control on the progression of atherosclerosis. <br> Tue, 27 Mar 2012 09:50:40 GMT