Sinoatrial Beat to Beat Variability Assessed by Contraction Strength in Addition to the Interbeat Interval

Ahammer, Helmut; Scheruebel, Susanne; Arnold, Robert; Mayrhofer-Reinhartshuber, Michael; Lang, Petra; Dolgos, Ádám; Pelzmann, Brigitte; Zorn-Pauly, Klaus

doi:10.3389/fphys.2018.00546

Cited by 2 publications

(2 citation statements)

References 40 publications

(53 reference statements)

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“…5) may be explained by the decreased acetylcholine (ACh) release in HF. In an animal study Ahammer et al reported that decreased ACh increased beat-to-beat contraction strength variability of murine atrial preparation [51]. In that study hearts were removed, and the atria were dissected from the ventricles.…”

Section: Discussionmentioning

confidence: 99%

Heart Failure Readmission Prediction Using Seismocardiogram Signal

Dhar,

Hossen,

Gamage

et al. 2024

Preprint

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Heart failure (HF) is considered a global pandemic because of increasing prevalence, high mortality rate, frequent hospitalization and associated economic burden. This study explores a noninvasive method that may help in managing HF patients by predicting HF readmission. Methods: Seismocardiogram (SCG) signal is the low frequency chest vibration produced by the mechanical activity of heart. SCG signal was acquired from 101 patients with HF including in those readmitted to the hospital during the study period. Features were extracted from SCG signals. Several conventional machine learning (ML) models were developed using selected SCG and heart rate variability features. Furthermore, SCG signals were transformed into images using a time-frequency distribution method. Images were used to train a deep learning model. The models were able to predict the readmission status of the HF patients. Results: ML algorithms achieved higher accuracy than the deep learning model in classifying the readmitted and non-readmitted HF patients. K-nearest neighbor (KNN) achieved the highest classification accuracy (89.4% accuracy, 87.8% sensitivity, and 90.1% specificity). The study results suggest that SCG signal may be useful for readmission prediction of HF patients. Significance: Use of SCG signal may help the management of HF patients and improve their quality of life.

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Section: Discussionmentioning

confidence: 99%

Heart Failure Readmission Prediction Using Seismocardiogram Signal

Dhar,

Hossen,

Gamage

et al. 2024

Preprint

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“…Intact SAN/atrial tissue was isolated from the excised mouse heart in Tyrode’s solution prewarmed to 37 °C as described previously ( 17 , 40 ). The right and the left atria were pinned flat to the bottom of a 35-mm cell culture dish coated with Sylgard (Sylgard 184 Silicone elastomer kit; Dow Corning) of ~2-mm thickness.…”

Section: Methodsmentioning

confidence: 99%

Lipopolysaccharide-induced sepsis impairs M2R-GIRK signaling in the mouse sinoatrial node

Shrestha

Zorn-Pauly

Mesirca

et al. 2023

Proc. Natl. Acad. Sci. U.S.A.

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Sepsis has emerged as a global health burden associated with multiple organ dysfunction and 20% mortality rate in patients. Numerous clinical studies over the past two decades have correlated the disease severity and mortality in septic patients with impaired heart rate variability (HRV), as a consequence of impaired chronotropic response of sinoatrial node (SAN) pacemaker activity to vagal/parasympathetic stimulation. However, the molecular mechanism(s) downstream to parasympathetic inputs have not been investigated yet in sepsis, particularly in the SAN. Based on electrocardiography, fluorescence Ca 2+ imaging, electrophysiology, and protein assays from organ to subcellular level, we report that impaired muscarinic receptor subtype 2-G protein-activated inwardly-rectifying potassium channel (M2R-GIRK) signaling in a lipopolysaccharide-induced proxy septic mouse model plays a critical role in SAN pacemaking and HRV. The parasympathetic responses to a muscarinic agonist, namely I KACh activation in SAN cells, reduction in Ca 2+ mobilization of SAN tissues, lowering of heart rate and increase in HRV, were profoundly attenuated upon lipopolysaccharide-induced sepsis. These functional alterations manifested as a direct consequence of reduced expression of key ion-channel components (GIRK1, GIRK4, and M2R) in the mouse SAN tissues and cells, which was further evident in the human right atrial appendages of septic patients and likely not mediated by the common proinflammatory cytokines elevated in sepsis.

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Sinoatrial Beat to Beat Variability Assessed by Contraction Strength in Addition to the Interbeat Interval

Cited by 2 publications

References 40 publications

Heart Failure Readmission Prediction Using Seismocardiogram Signal

Heart Failure Readmission Prediction Using Seismocardiogram Signal

Lipopolysaccharide-induced sepsis impairs M2R-GIRK signaling in the mouse sinoatrial node

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