Medullary Astrocytes Mediate Irregular Breathing Patterns Generation in Chronic Heart Failure Through Purinergic P2X7 Receptor Signalling

2021 ◽  
Author(s):  
Camilo Toledo ◽  
David Cristobal Andrade ◽  
Hugo S. Diaz ◽  
Karla G. Schwarz ◽  
Esteban Diaz-Jara ◽  
...  
Keyword(s):  
Heart Failure ◽  
Chronic Heart Failure ◽  
P2x7 Receptor ◽  
Breathing Patterns ◽  
Receptor Signalling ◽  
Purinergic P2x7 Receptor ◽  
Irregular Breathing

scholarly journals Effects of enriched-potassium diet on cardiorespiratory outcomes in experimental non-ischemic chronic heart failure

2021 ◽  
Vol 54 (1) ◽  
Author(s):  
Karla G. Schwarz ◽  
Katherin V. Pereyra ◽  
Camilo Toledo ◽  
David C. Andrade ◽  
Hugo S. Díaz ◽  
...  
Keyword(s):  
Heart Failure ◽  
Chronic Heart Failure ◽  
Cardiac Function ◽  
Chow Diet ◽  
Sympathetic Outflow ◽  
Breathing Patterns ◽  
Cardiac Arrhythmogenesis ◽  
Normal Chow ◽  
Normal Chow Diet ◽  
Irregular Breathing

Abstract Background Chronic heart failure (CHF) is a global health problem. Increased sympathetic outflow, cardiac arrhythmogenesis and irregular breathing patterns have all been associated with poor outcomes in CHF. Several studies showed that activation of the renin-angiotensin system (RAS) play a key role in CHF pathophysiology. Interestingly, potassium (K+) supplemented diets showed promising results in normalizing RAS axis and autonomic dysfunction in vascular diseases, lowering cardiovascular risk. Whether subtle increases in dietary K+ consumption may exert similar effects in CHF has not been previously tested. Accordingly, we aimed to evaluate the effects of dietary K+ supplementation on cardiorespiratory alterations in rats with CHF. Methods Adult male Sprague–Dawley rats underwent volume overload to induce non-ischemic CHF. Animals were randomly allocated to normal chow diet (CHF group) or supplemented K+ diet (CHF+K+ group) for 6 weeks. Cardiac arrhythmogenesis, sympathetic outflow, baroreflex sensitivity, breathing disorders, chemoreflex function, respiratory–cardiovascular coupling and cardiac function were evaluated. Results Compared to normal chow diet, K+ supplemented diet in CHF significantly reduced arrhythmia incidence (67.8 ± 15.1 vs. 31.0 ± 3.7 events/hour, CHF vs. CHF+K+), decreased cardiac sympathetic tone (ΔHR to propranolol: − 97.4 ± 9.4 vs. − 60.8 ± 8.3 bpm, CHF vs. CHF+K+), restored baroreflex function and attenuated irregular breathing patterns. Additionally, supplementation of the diet with K+ restores normal central respiratory chemoreflex drive and abrogates pathological cardio-respiratory coupling in CHF rats being the outcome an improved cardiac function. Conclusion Our findings support that dietary K+ supplementation in non-ischemic CHF alleviate cardiorespiratory dysfunction.

scholarly journals Characterization of the respiratory pattern in patients with chronic heart failure applying joint symbolic dynamics

2017 ◽  
Author(s):  
◽  
T. F. Molina-Ramírez
Keyword(s):  
Heart Failure ◽  
Chronic Heart Failure ◽  
Symbolic Dynamics ◽  
Clinical Decision Making ◽  
Periodic Breathing ◽  
Clinical Decision ◽  
Classification Method ◽  
Respiratory Pattern ◽  
Breathing Patterns ◽  
Linear Discriminant

This work proposes a method to characterize the respiratory pattern of patients with chronic heart failure (CHF) to determine non-periodic breathing (nPB), periodic breathing (PB) and Cheyne-Stokes respiration (CSR) through non-linear, symbolic analysis of biological signals. A total of 43 patients were examined for their cardiorespiratory profiles, their ECG and respiratory pattern signals were processed, analyzed and studied for parameters that could be of potential use in clinical decision making, specifically in patient classification. Patients in the study were characterized through their cardiorespiratory signals, applying joint symbolic dynamics (JSD) analysis to cardiac beat and respiratory interval durations. The most statistically significant parameters across all groups were identified through a Kruskal-Wallis two tailed test (α = 0.05) and a linear discriminant analysis (LDA) classification method based on such parameters was developed. The best result achieved with this classification method uses 10 features to discriminate patients with a 97.67% Accuracy (Acc). The best features to discriminate among groups are related to cardiorespiratory interaction rather than just respiration patterns alone. Results further support the idea that abnormal breathing patterns derive from physiological abnormalities in chronic heart failure.

scholarly journals Oscillatory Breathing Patterns During Wakefulness in Patients With Chronic Heart Failure

Circulation ◽  
1999 ◽  
Vol 100 (24) ◽  
pp. 2418-2424 ◽  
Author(s):  
Piotr Ponikowski ◽  
Stefan D. Anker ◽  
Tuan Peng Chua ◽  
Darrel Francis ◽  
Waldemar Banasiak ◽  
...  
Keyword(s):  
Heart Failure ◽  
Chronic Heart Failure ◽  
Breathing Patterns

Astrocytes within the retrotrapezoid nucleus maintain irregular breathing patterns in heart failure: role of P2X7 receptors

2020 ◽  
Vol 34 (S1) ◽  
pp. 1-1
Author(s):  
Rodrigo Del Rio ◽  
Camilo Toledo ◽  
David C. Andrade ◽  
Katherin Pereyra ◽  
Karla G. Schwarz ◽  
...  
Keyword(s):  
Heart Failure ◽  
Breathing Patterns ◽  
P2x7 Receptors ◽  
Retrotrapezoid Nucleus ◽  
Irregular Breathing

scholarly journals Characterization of the respiratory pattern in patients with chronic heart failure applying joint symbolic dynamics

2017 ◽  
Author(s):  
◽  
T. F. Molina-Ramírez
Keyword(s):  
Heart Failure ◽  
Chronic Heart Failure ◽  
Symbolic Dynamics ◽  
Clinical Decision Making ◽  
Periodic Breathing ◽  
Clinical Decision ◽  
Classification Method ◽  
Respiratory Pattern ◽  
Breathing Patterns ◽  
Linear Discriminant

This work proposes a method to characterize the respiratory pattern of patients with chronic heart failure (CHF) to determine non-periodic breathing (nPB), periodic breathing (PB) and Cheyne-Stokes respiration (CSR) through non-linear, symbolic analysis of biological signals. A total of 43 patients were examined for their cardiorespiratory profiles, their ECG and respiratory pattern signals were processed, analyzed and studied for parameters that could be of potential use in clinical decision making, specifically in patient classification. Patients in the study were characterized through their cardiorespiratory signals, applying joint symbolic dynamics (JSD) analysis to cardiac beat and respiratory interval durations. The most statistically significant parameters across all groups were identified through a Kruskal-Wallis two tailed test (α = 0.05) and a linear discriminant analysis (LDA) classification method based on such parameters was developed. The best result achieved with this classification method uses 10 features to discriminate patients with a 97.67% Accuracy (Acc). The best features to discriminate among groups are related to cardiorespiratory interaction rather than just respiration patterns alone. Results further support the idea that abnormal breathing patterns derive from physiological abnormalities in chronic heart failure.

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