A Systematic Review of a Polyvagal Perspective on Embodied Contemplative Practices as Promoters of Cardiorespiratory Coupling and Traumatic Stress Recovery for PTSD and OCD: Research Methodologies and State of the Art

Baseline respiratory sinus arrhythmia (RSA) has been proposed as a transdiagnostic biomarker of stress vulnerability across psychopathologies, and a reliable association between PTSD, OCD and lower resting RSA was found. Contemplative practices have been linked to the activation of the vagus as well as to an increased RSA that, according to the polyvagal theory, reflects the activation of the ventral vagal complex (VVC) and may promote PTSD and OCD recovery. PubMed and Scopus databases were selected to conduct a search following the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) 2020 guidelines, and A MeaSurement Tool to Assess systematic Reviews-2 (AMSTAR-2) was used to appraise the methodological quality for this systematic review. Six articles met the inclusion criteria (one cross-sectional study, one study with pre-post measurements, two cohort studies and two RCT studies). Mindfulness-related interventions promoted parasympathetic activity, an increased vagal tone and improvements in PTSD and OCD symptoms. According to the polyvagal theory, mindfulness-related and compassion-related meditations would be conceptualized as neural exercises expanding the capacity of the ventral vagal complex to regulate the present state and to promote resilience. Clinical and methodological issues are discussed.

Linear and Non-linear Quantification of the Respiratory Sinus Arrhythmia Using Support Vector Machines

Respiratory sinus arrhythmia (RSA) is a form of cardiorespiratory coupling. It is observed as changes in the heart rate in synchrony with the respiration. RSA has been hypothesized to be due to a combination of linear and nonlinear effects. The quantification of the latter, in turn, has been suggested as a biomarker to improve the assessment of several conditions and diseases. In this study, a framework to quantify RSA using support vector machines is presented. The methods are based on multivariate autoregressive models, in which the present samples of the heart rate variability are predicted as combinations of past samples of the respiration. The selection and tuning of a kernel in these models allows to solve the regression problem taking into account only the linear components, or both the linear and the nonlinear ones. The methods are tested in simulated data as well as in a dataset of polysomnographic studies taken from 110 obstructive sleep apnea patients. In the simulation, the methods were able to capture the nonlinear components when a weak cardiorespiratory coupling occurs. When the coupling increases, the nonlinear part of the coupling is not detected and the interaction is found to be of linear nature. The trends observed in the application in real data show that, in the studied dataset, the proposed methods captured a more prominent linear interaction than the nonlinear one.

Cardiorespiratory coupling is associated with exercise capacity in patients with chronic obstructive pulmonary disease

Background The interaction between the pulmonary function and cardiovascular mechanics is a crucial issue, particularly when treating patients with chronic obstructive pulmonary disease (COPD). Synchrogram index is a new parameter that can quantify this interaction and has the potential to apply in COPD patients. Our objective in this study was to characterize cardiorespiratory interactions in terms of cardiorespiratory coupling (CRC) using the synchrogram index of the heart rate and respiratory flow signals in patients with chronic obstructive pulmonary disease. Methods This is a cross-sectional and preliminary data from a prospective study, which examines 55 COPD patients. K-means clustering analysis was applied to cluster COPD patients based on the synchrogram index. Linear regression and multivariable regression analysis were used to determine the correlation between the synchrogram index and the exercise capacity assessed by a six-minute walking test (6MWT). Results The 55 COPD patients were separated into a synchronized group (median 0.89 (0.64–0.97), n = 43) and a desynchronized group (median 0.23 (0.02–0.51), n = 12) based on K-means clustering analysis. Synchrogram index was correlated significantly with six minutes walking distance (r = 0.42, p = 0.001) and distance saturation product (r = 0.41, p = 0.001) assessed by 6MWT, and still was an independent variable by multivariable regression analysis. Conclusion This is the first result studying the heart–lung interaction in terms of cardiorespiratory coupling in COPD patients by the synchrogram index, and COPD patients are clustered into synchronized and desynchronized groups. Cardiorespiratory coupling is associated with exercise capacity in patients with COPD.