1000 resultados para Cardiac defense


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Rise time and duration are two parametric characteristics of the eliciting stimulus frequently used to differentiate among psychophysiological reflexes. The present research varied the duration (study 1) and rise time (study 2) of an intense acoustic stimulus to dissociate cardiac defense and cardiac startle using the eyeblink response as the external criterion of startle. In each study, 100 participants were presented with five white noise stimuli of 105 dB under one of five duration (50, 100, 250, 500, and 1000 ms) or rise time (0, 24, 48, 96, and 240 ms) conditions. Cardiac defense was affected by stimulus duration, present only in the 500- and 1000-ms conditions, but not by stimulus rise time, present in all rise time conditions. Rise time affected blink startle, but did not selectively alter the short latency accelerative component of the heart rate response, thus questioning whether it reflects startle.

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Comparative studies of autonomic and somatic reflexes, such as cardiac defense and motor startle, are rare. However, examination of the pattern of covariation, independence, or interference among physiological reflexes may help to clarify their functional significance and elucidate their complex modulation by psychological factors. Here we report the results of a study that examined the pattern of interference of eye-blink startle on subsequent cardiac defense. Participants were 63 students (31 women) distributed into three groups according to the sensory modality of the eliciting stimulus during the startle trials: acoustic high intensity (105 dB), acoustic low intensity (65 dB), and visual modality. Startle trials consisted of 12 presentations of the eliciting stimulus with a duration of 50 ms, instantaneous risetime, and a variable inter-stimulus interval of 16 – 20 s.Defense trials began 20 s after the last startle trial and consisted, for all groups, of 3 presentations of the high intensity acoustic stimulus with a duration of 500 ms and an inter-stimulus interval of 215 s. Results showed a clear interference of the startle trials on the subsequent defense trials when both types of trials shared identical sensory modality (acoustic) independently of intensity: the expected pattern of cardiac defense in the first trial only appeared in the visual modality. Similar interference effects were observed in the skin conductance response. Subjective reactivity to the defense stimulus did not detect differences between conditions.

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BACKGROUND: Mechanical overload of the heart is associated with excessive deposition of extracellular matrix proteins and the development of cardiac fibrosis. This can result in reduced ventricular compliance, diastolic dysfunction, and heart failure. Extracellular matrix synthesis is regulated primarily by cardiac fibroblasts, more specifically, the active myofibroblast. The influence of mechanical stretch on human cardiac fibroblasts' response to pro-fibrotic stimuli, such as transforming growth factor beta (TGFβ), is unknown as is the impact of stretch on B-type natriuretic peptide (BNP) and natriuretic peptide receptor A (NPRA) expression. BNP, acting via NPRA, has been shown to play a role in modulation of cardiac fibrosis.

METHODS AND RESULTS: The effect of cyclical mechanical stretch on TGFβ induction of myofibroblast differentiation in primary human cardiac fibroblasts and whether differences in response to stretch were associated with changes in the natriuretic peptide system were investigated. Cyclical mechanical stretch attenuated the effectiveness of TGFβ in inducing myofibroblast differentiation. This finding was associated with a novel observation that mechanical stretch can increase BNP and NPRA expression in human cardiac fibroblasts, which could have important implications in modulating myocardial fibrosis. Exogenous BNP treatment further reduced the potency of TGFβ on mechanically stretched fibroblasts.

CONCLUSION: We postulate that stretch induced up-regulation of the natriuretic peptide system may contribute to the observed reduction in myofibroblast differentiation.

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Background The accurate measurement of Cardiac output (CO) is vital in guiding the treatment of critically ill patients. Invasive or minimally invasive measurement of CO is not without inherent risks to the patient. Skilled Intensive Care Unit (ICU) nursing staff are in an ideal position to assess changes in CO following therapeutic measures. The USCOM (Ultrasonic Cardiac Output Monitor) device is a non-invasive CO monitor whose clinical utility and ease of use requires testing. Objectives To compare cardiac output measurement using a non-invasive ultrasonic device (USCOM) operated by a non-echocardiograhically trained ICU Registered Nurse (RN), with the conventional pulmonary artery catheter (PAC) using both thermodilution and Fick methods. Design Prospective observational study. Setting and participants Between April 2006 and March 2007, we evaluated 30 spontaneously breathing patients requiring PAC for assessment of heart failure and/or pulmonary hypertension at a tertiary level cardiothoracic hospital. Methods SCOM CO was compared with thermodilution measurements via PAC and CO estimated using a modified Fick equation. This catheter was inserted by a medical officer, and all USCOM measurements by a senior ICU nurse. Mean values, bias and precision, and mean percentage difference between measures were determined to compare methods. The Intra-Class Correlation statistic was also used to assess agreement. The USCOM time to measure was recorded to assess the learning curve for USCOM use performed by an ICU RN and a line of best fit demonstrated to describe the operator learning curve. Results In 24 of 30 (80%) patients studied, CO measures were obtained. In 6 of 30 (20%) patients, an adequate USCOM signal was not achieved. The mean difference (±standard deviation) between USCOM and PAC, USCOM and Fick, and Fick and PAC CO were small, −0.34 ± 0.52 L/min, −0.33 ± 0.90 L/min and −0.25 ± 0.63 L/min respectively across a range of outputs from 2.6 L/min to 7.2 L/min. The percent limits of agreement (LOA) for all measures were −34.6% to 17.8% for USCOM and PAC, −49.8% to 34.1% for USCOM and Fick and −36.4% to 23.7% for PAC and Fick. Signal acquisition time reduced on average by 0.6 min per measure to less than 10 min at the end of the study. Conclusions In 80% of our cohort, USCOM, PAC and Fick measures of CO all showed clinically acceptable agreement and the learning curve for operation of the non-invasive USCOM device by an ICU RN was found to be satisfactorily short. Further work is required in patients receiving positive pressure ventilation.

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Objectives: The current study was conducted to determine levels of cardiac knowledge and cardiopulmonary resuscitation (CPR) training in older people in Queensland, Australia.---------- Methods: A telephone survey of 4490 Queensland adults examined respondents’ knowledge of coronary heart disease (CHD) risk factors, knowledge of heart attack symptoms, knowledge of the local emergency telephone number, as well as respondents’ rates and recency of training in CPR.---------- Results: Older participants, aged 60 years and over, were approximately one and a half times more likely than the 30–39 year-old reference group to have limited knowledge of heart disease risk factors (OR = 1.53), and low knowledge of heart attack symptoms (OR = 1.60). Knowledge of the local emergency telephone number also decreased with age. Older participants had significantly lower rates of training in CPR, with almost three quarters (71.7%) reporting that they had never been trained. Older people who had completed CPR training were significantly less likely to have done so recently.---------- Conclusions: Cardiac knowledge levels and CPR training rates in older Queensland persons were lower than those found in the younger population.

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BACKGROUND: Although we know much about the molecular makeup of the sinus node (SN) in small mammals, little is known about it in humans. The aims of the present study were to investigate the expression of ion channels in the human SN and to use the data to predict electrical activity. METHODS AND RESULTS: Quantitative polymerase chain reaction, in situ hybridization, and immunofluorescence were used to analyze 6 human tissue samples. Messenger RNA (mRNA) for 120 ion channels (and some related proteins) was measured in the SN, a novel paranodal area, and the right atrium (RA). The results showed, for example, that in the SN compared with the RA, there was a lower expression of Na(v)1.5, K(v)4.3, K(v)1.5, ERG, K(ir)2.1, K(ir)6.2, RyR2, SERCA2a, Cx40, and Cx43 mRNAs but a higher expression of Ca(v)1.3, Ca(v)3.1, HCN1, and HCN4 mRNAs. The expression pattern of many ion channels in the paranodal area was intermediate between that of the SN and RA; however, compared with the SN and RA, the paranodal area showed greater expression of K(v)4.2, K(ir)6.1, TASK1, SK2, and MiRP2. Expression of ion channel proteins was in agreement with expression of the corresponding mRNAs. The levels of mRNA in the SN, as a percentage of those in the RA, were used to estimate conductances of key ionic currents as a percentage of those in a mathematical model of human atrial action potential. The resulting SN model successfully produced pacemaking. CONCLUSIONS: Ion channels show a complex and heterogeneous pattern of expression in the SN, paranodal area, and RA in humans, and the expression pattern is appropriate to explain pacemaking.

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Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart, by the sympathetic and parasympathetic branches of the autonomic nervous system. Heart rate variability analysis is an important tool to observe the heart's ability to respond to normal regulatory impulses that affect its rhythm. A computer-based intelligent system for analysis of cardiac states is very useful in diagnostics and disease management. Like many bio-signals, HRV signals are nonlinear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of nonlinear systems and provides good noise immunity. In this work, we studied the HOS of the HRV signals of normal heartbeat and seven classes of arrhythmia. We present some general characteristics for each of these classes of HRV signals in the bispectrum and bicoherence plots. We also extracted features from the HOS and performed an analysis of variance (ANOVA) test. The results are very promising for cardiac arrhythmia classification with a number of features yielding a p-value < 0.02 in the ANOVA test.

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The study objective was to determine whether the ‘cardiac decompensation score’ could identify cardiac decompensation in a patient with existing cardiac compromise managed with intraaortic balloon counterpulsation (IABP). A one-group, posttest-only design was utilised to collect observations in 2003 from IABP recipients treated in the intensive care unit of a 450 bed Australian, government funded, public, cardiothoracic, tertiary referral hospital. Twenty-three consecutive IABP recipients were enrolled, four of whom died in ICU (17.4%). All non-survivors exhibited primarily rising scores over the observation period (p < 0.001) and had final scores of 25 or higher. In contrast, the maximum score obtained by a survivor at any time was 15. Regardless of survival, scores for the 23 participants were generally decreasing immediately following therapy escalation (p = 0.016). Further reflecting these changes in patient support, there was also a trend for scores to move from rising to falling at such treatment escalations (p = 0.024). This pilot study indicates the ‘cardiac decompensation score’ to accurately represent changes in heart function specific to an individual patient. Use of the score in conjunction with IABP may lead to earlier identification of changes occurring in a patient's cardiac function and thus facilitate improved IABP outcomes.

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The theory of nonlinear dyamic systems provides some new methods to handle complex systems. Chaos theory offers new concepts, algorithms and methods for processing, enhancing and analyzing the measured signals. In recent years, researchers are applying the concepts from this theory to bio-signal analysis. In this work, the complex dynamics of the bio-signals such as electrocardiogram (ECG) and electroencephalogram (EEG) are analyzed using the tools of nonlinear systems theory. In the modern industrialized countries every year several hundred thousands of people die due to sudden cardiac death. The Electrocardiogram (ECG) is an important biosignal representing the sum total of millions of cardiac cell depolarization potentials. It contains important insight into the state of health and nature of the disease afflicting the heart. Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. Heart rate variability analysis is an important tool to observe the heart's ability to respond to normal regulatory impulses that affect its rhythm. A computerbased intelligent system for analysis of cardiac states is very useful in diagnostics and disease management. Like many bio-signals, HRV signals are non-linear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of non-linear systems and provides good noise immunity. In this work, we studied the HOS of the HRV signals of normal heartbeat and four classes of arrhythmia. This thesis presents some general characteristics for each of these classes of HRV signals in the bispectrum and bicoherence plots. Several features were extracted from the HOS and subjected an Analysis of Variance (ANOVA) test. The results are very promising for cardiac arrhythmia classification with a number of features yielding a p-value < 0.02 in the ANOVA test. An automated intelligent system for the identification of cardiac health is very useful in healthcare technology. In this work, seven features were extracted from the heart rate signals using HOS and fed to a support vector machine (SVM) for classification. The performance evaluation protocol in this thesis uses 330 subjects consisting of five different kinds of cardiac disease conditions. The classifier achieved a sensitivity of 90% and a specificity of 89%. This system is ready to run on larger data sets. In EEG analysis, the search for hidden information for identification of seizures has a long history. Epilepsy is a pathological condition characterized by spontaneous and unforeseeable occurrence of seizures, during which the perception or behavior of patients is disturbed. An automatic early detection of the seizure onsets would help the patients and observers to take appropriate precautions. Various methods have been proposed to predict the onset of seizures based on EEG recordings. The use of nonlinear features motivated by the higher order spectra (HOS) has been reported to be a promising approach to differentiate between normal, background (pre-ictal) and epileptic EEG signals. In this work, these features are used to train both a Gaussian mixture model (GMM) classifier and a Support Vector Machine (SVM) classifier. Results show that the classifiers were able to achieve 93.11% and 92.67% classification accuracy, respectively, with selected HOS based features. About 2 hours of EEG recordings from 10 patients were used in this study. This thesis introduces unique bispectrum and bicoherence plots for various cardiac conditions and for normal, background and epileptic EEG signals. These plots reveal distinct patterns. The patterns are useful for visual interpretation by those without a deep understanding of spectral analysis such as medical practitioners. It includes original contributions in extracting features from HRV and EEG signals using HOS and entropy, in analyzing the statistical properties of such features on real data and in automated classification using these features with GMM and SVM classifiers.

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Background: Nurse-led telephone follow-up offers a relatively inexpensive method of delivering education and support for assisting recovery in the early discharge period; however, its efficacy is yet to be determined. Aim: To perform a critical integrative review of the research literature addressing the effectiveness of nurse-led telephone interventions for people with coronary heart disease (CHD). Methods: A literature search of five health care databases; Sciencedirect, Cumulative Index to Nursing and Allied Health Literature, Pubmed, Proquest and Medline to identify journal articles between 1980 and 2009. People with cardiac disease were considered for inclusion in this review. The search yielded 128 papers, of which 24 met the inclusion criteria. Results: A total of 8330 participants from 24 studies were included in the final review. Seven studies demonstrated statistically significant differences in all outcomes measured, used two group experimental research design and valid and reliable instruments. Some positive effects were detected in eight studies in regards to nurse-led telephone interventions for people with cardiac disease and no differences were detected in nine studies. Discussion: Studies with some positive effects generally had stronger research designs, large samples, used valid and reliable instruments and extensive nurse-led educative interventions. Conclusion: The results suggest that people with cardiac disease showed some benefits from nurse-led/delivered telephone interventions. More rigorous research into this area is needed.