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志物。我们将结合实验方法和计算模型来研究covid - 19后患者的呼吸困难和呼吸行为、它们之间的相互作用以及呼吸信号处理的假设。我们使用一个既定的再呼吸模式，允许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，在这个再呼吸实验中，与健康个体相比，有器质性原因不明的呼吸困难的患者在呼吸困难方面表现出特征性的、可测量的偏差。这些偏差仅在特定情况下发生，表明中枢神经系统（CNS）对呼吸信息的处理发生了改变。在本研究中，我们将使用这一范式来研究这种特征性变化（感知呼吸困难和/或生理呼吸参数和模式）是否发生在covid后呼吸困难患者中，以及它们是否会因不同的环境而改变。在个体患者的水平上，实验方法和理论模型的结合使我们能够测试有关呼吸信号在呼吸困难发展过程中处理的详细假设。为此，我们开发了一个呼吸困难处理的初步数学模型。它在预测先前研究的平均数据和使用再呼吸范式的个体受试者的初步试点数据方面已经显示出良好的结果。目的：病理生理标志物是减少对covid后患者的耻辱感和个性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.