Dysfunctional respiratory processing in patients with post-COVID? – An experimental-computational approach investigating the interaction between breathing behaviour and symptom perception

在这项拟议的研究中，我们的目标是开发客观的COVID后呼吸困难的病理生理标记物。我们将结合实验方法和计算模型来研究呼吸困难和呼吸行为，它们的相互作用，以及关于COVID后患者呼吸信号处理的假设。我们使用一种已建立的重复呼吸范例，以确定呼吸困难和生理参数之间的相互作用。先前的研究表明，在这个重复呼吸实验中，与健康人相比，原因不明的呼吸困难患者在呼吸困难方面表现出特征的、可测量的偏差。这些偏差只发生在特定的环境中，表明中枢神经系统(CNS)对呼吸信息的处理发生了变化。在目前的研究中，我们将使用这一范式来调查COVID后呼吸困难患者是否会发生这种特征变化(感觉到的呼吸困难和/或生理呼吸参数和模式)，以及它们是否会因不同的情况而改变。在个体患者水平上对呼吸困难的实验方法和理论建模的结合使我们能够测试关于呼吸信号在呼吸困难发展中的处理的详细假设。为此，我们开发了一个初步的呼吸处理的数学模型。它已经在使用重复呼吸范式预测来自先前研究的平均数据和来自个别受试者的初始试点数据方面显示出良好的结果。目的：病理生理标记物是减少COVID后患者耻辱和个体化诊断和治疗计划的重要第一步。

In the proposed study, we aim to develop objective, pathophysiological markers of breathlessness in post-COVID. We will combine experimental methods with computational modeling to investigate breathlessness and respiratory behavior, their interaction, and hypotheses about respiratory signal processing in post-COVID patients. We use an established rebreathing paradigm that allows determination of the interaction between breathlessness and physiological parameters. Previous studies have shown that in this rebreathing experiment, patients with organically unexplained breathlessness exhibit characteristic, measurable deviations in breathlessness compared to healthy individuals. These deviations occur only in specific contexts and indicate altered processing of respiratory information in the central nervous system (CNS). In the present study, we will use this paradigm to investigate whether such characteristic changes (in perceived breathlessness and/or in physiological respiratory parameters and patterns) occur in patients with post-COVID breathlessness, and whether they are altered by different contexts. The combination of an experimental approach and theoretical modeling of breathlessness at the level of individual patients allows us to test detailed hypotheses about the processing of respiratory signals in the development of breathlessness. For this purpose, we have developed a preliminary mathematical model of breathlessness processing. It already shows good results in predicting mean data from previous studies and initial pilot data from individual subjects using the rebreathing paradigm. Objective, pathophysiological markers are an important first step towards reducing stigma and individualized planning of diagnosis and therapy in patients with post-COVID.