CARDIOPULMONARY TIME SERIES ANALYSIS--DRUG AND AGING EFFECTS

心肺时间序列分析——药物和衰老的影响

• 批准号: 6204317
• 负责人: JANICE B SCHWARTZ
• 金额: $ 2.21万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-08-01 至 2000-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6204317
• 关键词: aging; animal old age; atropine; autonomic nervous system; baroreceptors; beta adrenergic agent; blood pressure; dogs; dosage; electronic pacemaker; electrophysiology; heart pharmacology; heart rate; hemodynamics; human old age (65+); human subject; juvenile animal; mathematical model; nitroglycerin; pharmacokinetics; phenylephrine; propranolol; pulmonary respiration; vasodilators; young adult human (21-34)

We propose that bioelectrical time series such as electrocardiograms (ECG), blood pressure recordings, and respiratory recordings, contain information regarding the state of a human, and, the effect of a drug on the state of a patient that univariate analytic techniques and simple mean effect measures are inadequate to characterize. We have shown that Fast Fourier Transformation (FFT)-based methods to analyze beat-to-beat variability of heart rate (ECG data) during administration of verapamil to man demonstrated effects (decreased variability in frequencies associated with respiratory or vagally-mediated parasympathetic modulation) which were not detected in average heart rate responses or other time domain analyses of heart rate responses. In addition, we and others have shown that frequency domain analysis of ECG data can identify activation of baroreflex responses - potentially allowing identification and quantitation of indirect drug effects via reflex response activation which may markedly influence net drug effect in vivo. We have also used these analytic techniques to show that aging alters basal heart rate variability and frequency content of heart rate responses to postural maneuvers. In these initial/pilot studies, it became apparent that method of respiration (as well as rate) alters the frequency content of heart rate data, and needs to be considered in evaluating heart rate data, and, that optimal methods for interpretation of frequency domain data were not yet developed. We have also demonstrated age-related changes in pharmacodynamics as well as pharmacokinetics. In particular, baroreflex responses appear to be altered (diminished) with aging. Since altered responses to drugs can result from differing drug demonstrations, tissue sensitivities, differing homeostatic reflex responses, or a combination of these factors, it is important to evaluate the contributions of altered reflex responses to the altered pharmacodynamic responses of elderly individuals to drugs. This is especially important with vasoactive drugs which may activate baroreceptor responses and are the most frequently prescribed drugs in the elderly population. Therefore, we now propose to further develop and validate methods for analysis of bioelectric time series information. In addition to refining methods for analysis of beat-to-beat variation in heart rate, we will develop a method for analysis of beat-to-beat variability in blood pressure, and breath-to-breath variability in respiration. We will then develop a model in which heart rate, blood pressure, and respiration time series are interrelated by transfer functions and in which the interactions between variables can be evaluated and quantitated as to time course, magnitude, and contribution to in vivo effects. We will then use this combined bioelectric time series model to (1) analyze effects during drug administration to identify and quantitate contributions of reflex (parasympathetic or beta-adrenergic) responses in combination with drug dose or concentration data to net drug effect in vivo and (2) test the hypotheses that aging changes time series content of blood pressure and respiration and the interrelationship between heart rate, blood pressure and respiration; and, that age-related changes in reflex responses are a major determinant of altered drug responses in the elderly that may be predictable and quantifiable. Finally, based on results from these investigations, we will reduce the model to the simplest form that adequately describes and predicts physiologic and drug responses in humans.

我们提出，生物电时间序列，如心电图（ECG）， 血压记录和呼吸记录， 一个人的状态，以及药物对一个人状态的影响， 单变量分析技术和简单的平均效应测量 不足以描述。 我们已经证明，快速傅立叶 基于变换（FFT）的方法来分析心跳间的变异性， 维拉帕米给药期间心率（ECG数据） 已证实的效应（与以下因素相关的频率变异性降低） 呼吸或迷走神经介导的副交感神经调节），而这些调节不是 在平均心率响应或其他时域分析中检测到 心率反应 此外，我们和其他人已经表明， ECG数据的域分析可以识别压力反射反应的激活 - 潜在地允许间接药物的鉴定和定量 通过反射反应激活产生的效应，可能会显著影响净 体内药效 我们还使用这些分析技术来显示 衰老会改变基础心率变异性和 心率对姿势动作的反应。 在这些初始/试点 研究，很明显，呼吸方法（以及速率） 改变心率数据的频率内容，需要考虑 在评估心率数据中，以及用于解释最佳方法 频域数据尚未开发。 我们还证明了药效学的年龄相关变化 药代动力学。 特别是，压力反射反应似乎是 随着年龄的增长而改变（减少）。 因为对药物的反应改变 不同的药物表现，组织敏感性， 稳态反射反应，或这些因素的组合，它是 重要的是要评估改变反射反应的贡献， 改变老年人对药物的药效学反应。 这是 对于可能激活压力感受器的血管活性药物尤其重要 反应，是老年人最常用的处方药 人口 因此，我们现在建议进一步开发和验证方法， 生物电时间序列信息分析。 除了精炼 方法分析心跳心跳的变化，我们将 开发一种分析血液中心跳间变异性的方法 压力和呼吸的呼吸间变异性。 然后我们将 开发一个模型，其中心率、血压和呼吸时间 系列通过传递函数相互关联，其中相互作用 可以评估和量化变量之间的时间过程， 幅度以及对体内效应的贡献。 然后我们会用这个 组合生物电时间序列模型，以（1）分析药物治疗期间的效果 给药以识别和定量反射的贡献 （副交感神经或β-肾上腺素能）反应与药物联合 剂量或浓度数据与体内净药物效应的关系，以及（2）测试 假设年龄改变血压的时间序列内容， 呼吸和心率、血压之间的相互关系 和呼吸;而且，与年龄相关的反射反应变化是一个 老年人药物反应改变的主要决定因素， 可预测的和可量化的。 最后，根据这些结果， 调查，我们将减少模型的最简单的形式， 充分描述和预测人体的生理和药物反应。