Objective: Respiration disturbs cardiovascular and cerebrovascular controls but its role is not fully elucidated. Methods: Respiration can be classified as a confounder if its observation reduces the strength of the causal relationship from source to target. Respiration is a suppressor if the opposite situation holds. We prove that a confounding/suppression (C/S) test can be accomplished by evaluating the sign of net redundancy/synergy balance in the predictability framework based on multivariate autoregressive modelling. In addition, we suggest that, under the hypothesis of Gaussian processes, the C/S test can be given in the transfer entropy decomposition framework as well. Experimental protocols: We applied the C/S test to variability series of respiratory movements, heart period, systolic arterial pressure, mean arterial pressure, and mean cerebral blood flow recorded in 17 pathological individuals (age: 64 +/- 8 yrs; 17 males) before and after induction of propofol-based general anesthesia prior to coronary artery bypass grafting, and in 13 healthy subjects (age: 27 +/- 8 yrs; 5 males) at rest in supine position and during head-up tilt with a table inclination of 60 degrees. Results: Respiration behaved systematically as a confounder for cardiovascular and cerebrovascular controls. In addition, its role was affected by propofol-based general anesthesia but not by a postural stimulus of limited intensity. Conclusion: The C/S test can be fruitfully exploited to categorize the role of respiration over causal variability interactions. Significance: The application of the C/S test could favor the comprehension of the role of respiration in cardiovascular and cerebrovascular regulations.

Categorizing the role of respiration in cardiovascular and cerebrovascular variability interactions / A. Porta, F. Gelpi, V. Bari, B. Cairo, B. De Maria, D. Tonon, G. Rossato, M. Ranucci, L. Faes. - In: IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING. - ISSN 0018-9294. - 69:6(2022 Jun), pp. 2065-2076. [10.1109/TBME.2021.3135313]

Categorizing the role of respiration in cardiovascular and cerebrovascular variability interactions

A. Porta
Primo
;
F. Gelpi
Secondo
;
V. Bari;B. Cairo;
2022

Abstract

Objective: Respiration disturbs cardiovascular and cerebrovascular controls but its role is not fully elucidated. Methods: Respiration can be classified as a confounder if its observation reduces the strength of the causal relationship from source to target. Respiration is a suppressor if the opposite situation holds. We prove that a confounding/suppression (C/S) test can be accomplished by evaluating the sign of net redundancy/synergy balance in the predictability framework based on multivariate autoregressive modelling. In addition, we suggest that, under the hypothesis of Gaussian processes, the C/S test can be given in the transfer entropy decomposition framework as well. Experimental protocols: We applied the C/S test to variability series of respiratory movements, heart period, systolic arterial pressure, mean arterial pressure, and mean cerebral blood flow recorded in 17 pathological individuals (age: 64 +/- 8 yrs; 17 males) before and after induction of propofol-based general anesthesia prior to coronary artery bypass grafting, and in 13 healthy subjects (age: 27 +/- 8 yrs; 5 males) at rest in supine position and during head-up tilt with a table inclination of 60 degrees. Results: Respiration behaved systematically as a confounder for cardiovascular and cerebrovascular controls. In addition, its role was affected by propofol-based general anesthesia but not by a postural stimulus of limited intensity. Conclusion: The C/S test can be fruitfully exploited to categorize the role of respiration over causal variability interactions. Significance: The application of the C/S test could favor the comprehension of the role of respiration in cardiovascular and cerebrovascular regulations.
autonomic nervous system; cardiac neural control; cerebrovascular autoregulation; confounding; general anesthesia; head-up tilt; heart rate variability; Multivariate autoregressive model; predictability decomposition; redundancy; suppression; synergy; transfer entropy;
Settore ING-INF/06 - Bioingegneria Elettronica e Informatica
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/946350
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