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Results for “Cardiovascular Diseases/physiopathology”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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Physiological basis for human autonomic rhythms

Oscillations of arterial pressures, heart periods, and muscle sympathetic nerve activity have been studied intensively in recent years to explore otherwise obscure human neurophysiological mechanisms. The best-studied rhythms are those occurring at breathing frequencies. Published evidence indicates that respiratory fluctuations of muscle sympathetic nerve activity and electrocardiographic R-R intervals result primarily from the action of a central 'gate' that opens during expiration and closes during inspiration. Parallel respiratory fluctuations of arterial pressures and R-R intervals are thought to be secondary to arterial baroreflex physiology: changes in systolic pressure provoke changes in the R-R interval. However, growing evidence suggests that these parallel oscillations result from the influence of respiration on sympathetic and vagal-cardiac motoneurones rather than from baroreflex physiology. There is a rapidly growing literature on the use of mathematical models of low- and high-frequency (respiratory) R-R interval fluctuations in characterizing instantaneous 'sympathovagal balance'. The case for this approach is based primarily on measurements made with patients in upright tilt. However, the strong linear relation between such measures as the ratio of low- to high-frequency R-R interval oscillations and the angle of the tilt reflects exclusively the reductions of the vagal (high-frequency) component. As the sympathetic component does not change in tilt, the low- to high-frequency R-R interval ratio provides no proof that sympathetic activity increases. Moreover, the validity of extrapolating from measurements performed during upright tilt to measurements during supine rest has not been established. Nonetheless, it is clear that measures of heart rate variability provide important prognostic information in patients with cardiovascular diseases. It is not known whether reduced heart rate variability is merely a marker for the severity of disease or a measurement that identifies functional reflex abnormalities contributing to terminal dysrhythmias.

Review, Tutorial↗

Estimation of cardiac reserve by peak power: validation and initial application of a simplified index

OBJECTIVES: To validate a simplified estimate of peak power (SPP) against true (invasively measured) peak instantaneous power (TPP), to assess the feasibility of measuring SPP during exercise and to correlate this with functional capacity. DESIGN: Development of a simplified method of measurement and observational study. SETTING: Tertiary referral centre for cardiothoracic disease. SUBJECTS: For validation of SPP with TPP, seven normal dogs and four dogs with dilated cardiomyopathy were studied. To assess feasibility and clinical significance in humans, 40 subjects were studied (26 patients; 14 normal controls). METHODS: In the animal validation study, TPP was derived from ascending aortic pressure and flow probe, and from Doppler measurements of flow. SPP, calculated using the different flow measures, was compared with peak instantaneous power under different loading conditions. For the assessment in humans, SPP was measured at rest and during maximum exercise. Peak aortic flow was measured with transthoracic continuous wave Doppler, and systolic and diastolic blood pressures were derived from brachial sphygmomanometry. The difference between exercise and rest simplified peak power (Delta SPP) was compared with maximum oxygen uptake (VO(2)max), measured from expired gas analysis. RESULTS: SPP estimates using peak flow measures correlated well with true peak instantaneous power (r = 0.89 to 0.97), despite marked changes in systemic pressure and flow induced by manipulation of loading conditions. In the human study, VO(2)max correlated with Delta SPP (r = 0.78) better than Delta ejection fraction (r = 0.18) and Delta rate-pressure product (r = 0.59). CONCLUSIONS: The simple product of mean arterial pressure and peak aortic flow (simplified peak power, SPP) correlates with peak instantaneous power over a range of loading conditions in dogs. In humans, it can be estimated during exercise echocardiography, and correlates with maximum oxygen uptake better than ejection fraction or rate-pressure product.

Non-NASA Center↗

Increased gait unsteadiness in community-dwelling elderly fallers

OBJECTIVE: To test the hypothesis that quantitative measures of gait unsteadiness are increased in community-dwelling elderly fallers. STUDY DESIGN: Retrospective, case-control study. SETTING: General community. PARTICIPANTS: Thirty-five community-dwelling elderly subjects older than 70 years of age who were capable of ambulating independently for 6 minutes were categorized as fallers (age, 82.2 +/- 4.9 yrs [mean +/- SD]; n = 18) and nonfallers (age, 76.5 +/- 4.0 yrs; n = 17) based on history; 22 young (age, 24.6 +/- 1.9 yrs), healthy subjects also participated as a second reference group. MAIN OUTCOME MEASURES: Stride-to-stride variability (standard deviation and coefficient of variation) of stride time, stance time, swing time, and percent stance time measured during a 6-minute walk. RESULTS: All measures of gait variability were significantly greater in the elderly fallers compared with both the elderly nonfallers and the young subjects (p < .0002). In contrast, walking speed of the elderly fallers was similar to that of the nonfallers. There were little or no differences in the variability measures of the elderly nonfallers compared with the young subjects. CONCLUSIONS: Stride-to-stride temporal variations of gait are relatively unchanged in community-dwelling elderly nonfallers, but are significantly increased in elderly fallers. Quantitative measurement of gait unsteadiness may be useful in assessing fall risk in the elderly.

NASA Discipline Cardiopulmonary↗

Mathematical modelling of the human cardiovascular system in the presence of stenosis

This paper reports a theoretical study on the distribution of blood flow in the human cardiovascular system when one or more blood vessels are affected by stenosis. The analysis employs a mathematical model of the entire system based on the finite element method. The arterial-venous network is represented by a large number of interconnected segments in the model. Values for the model parameters are based upon the published data on the physiological and rheological properties of blood. Computational results show how blood flow through various parts of the cardiovascular system is affected by stenosis in different blood vessels. No significant changes in the flow parameters of the cardiovascular system were found to occur when the reduction in the lumen diameter of the stenosed vessels was less than 65%.

NASA Program Data Analysis↗

System identification of closed-loop cardiovascular control mechanisms: diabetic autonomic neuropathy

We applied cardiovascular system identification (CSI) to characterize closed-loop cardiovascular regulation in patients with diabetic autonomic neuropathy (DAN). The CSI method quantitatively analyzes beat-to-beat fluctuations in noninvasively measured heart rate, arterial blood pressure (ABP), and instantaneous lung volume (ILV) to characterize four physiological coupling mechanisms, two of which are autonomically mediated (the heart rate baroreflex and the coupling of respiration, measured in terms of ILV, to heart rate) and two of which are mechanically mediated (the coupling of ventricular contraction to the generation of the ABP wavelet and the coupling of respiration to ABP). We studied 37 control and 60 diabetic subjects who were classified as having minimal, moderate, or severe DAN on the basis of standard autonomic tests. The autonomically mediated couplings progressively decreased with increasing severity of DAN, whereas the mechanically mediated couplings were essentially unchanged. CSI identified differences between the minimal DAN and control groups, which were indistinguishable based on the standard autonomic tests. CSI may provide a powerful tool for assessing DAN.

Non-NASA Center↗

Statistical physics and physiology: monofractal and multifractal approaches

Even under healthy, basal conditions, physiologic systems show erratic fluctuations resembling those found in dynamical systems driven away from a single equilibrium state. Do such "nonequilibrium" fluctuations simply reflect the fact that physiologic systems are being constantly perturbed by external and intrinsic noise? Or, do these fluctuations actually, contain useful, "hidden" information about the underlying nonequilibrium control mechanisms? We report some recent attempts to understand the dynamics of complex physiologic fluctuations by adapting and extending concepts and methods developed very recently in statistical physics. Specifically, we focus on interbeat interval variability as an important quantity to help elucidate possibly non-homeostatic physiologic variability because (i) the heart rate is under direct neuroautonomic control, (ii) interbeat interval variability is readily measured by noninvasive means, and (iii) analysis of these heart rate dynamics may provide important practical diagnostic and prognostic information not obtainable with current approaches. The analytic tools we discuss may be used on a wider range of physiologic signals. We first review recent progress using two analysis methods--detrended fluctuation analysis and wavelets--sufficient for quantifying monofractual structures. We then describe recent work that quantifies multifractal features of interbeat interval series, and the discovery that the multifractal structure of healthy subjects is different than that of diseased subjects.

NASA Discipline Cardiopulmonary↗

Fractal mechanisms and heart rate dynamics. Long-range correlations and their breakdown with disease

Under healthy conditions, the normal cardiac (sinus) interbeat interval fluctuates in a complex manner. Quantitative analysis using techniques adapted from statistical physics reveals the presence of long-range power-law correlations extending over thousands of heartbeats. This scale-invariant (fractal) behavior suggests that the regulatory system generating these fluctuations is operating far from equilibrium. In contrast, it is found that for subjects at high risk of sudden death (e.g., congestive heart failure patients), these long-range correlations break down. Application of fractal scaling analysis and related techniques provides new approaches to assessing cardiac risk and forecasting sudden cardiac death, as well as motivating development of novel physiologic models of systems that appear to be heterodynamic rather than homeostatic.

NASA Discipline Cardiopulmonary↗