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Holistic integrative analysis of circulatory parameters: breath-by-breath analysis for circulatory parameters in
Jia-Hao Chen1,2, Xing-Guo Sun1,2, Jiang Huang1,2
1Department of Internal Medicine, The Affiliated Rehabilitation Hospital of Chongqing Medical University, Chongqing, China.
Background:
The theory of Holistic Integrative Physiology and Medicine (HIPM) emphasizes the perspective of integrated regulation, which includes interconnected systems of respiration, circulation, and metabolism. Based on this perspective, we aim to comprehend the relationship between respiration and circulatory parameters such as heart rate variability (HRV) and blood pressure variability (BPV), thereby clarifying the interrelation of two essential physiological systems.
Methods:
This study conducted a retrospective analysis of data obtained during polysomnography (PSG) and cardiopulmonary exercise testing (CPET). These parameters included the mean amplitude of HRV, HRV percentage (HRV%), mean amplitude of systolic blood pressure variability (SBPV-M), mean amplitude of diastolic blood pressure variability (DBPV-M), along with the percentages of SBPV-M (SBPV-M%) and DBPV-M (DBPV-M%). Furthermore, we analyzed the relationship between nasal airflow respiratory cycles and circulatory cycles. We analyzed two groups: seven individuals without known diseases and eight patients with chronic diseases, all without sleep apnea syndrome on PSG.
Results:
Our study demonstrated significant differences between individuals without known diseases and patients with chronic diseases. In control group, the peak oxygen uptake (peak ) was 97.82±18.51 %Pred, the anaerobic threshold (AT) was 83.61±10.46 %Pred, the peak work rate was 111.09±31.01 %Pred, the HRV was 6.15±1.52 bpm and HRV% was 11.15%±3.71%, respectively. These values were significantly higher than those observed in patients with chronic diseases (P values were 0.009, 0.05, 0.005, <0.001 and 0.001). In the context of SBPV-M, DBPV-M, SBPV-M% and DBPV-M%, the values for individuals without known diseases were 2.27±0.83 mmHg, 2.12±0.40 mmHg, 2.07%±0.71%, and 3.10%±0.66%, respectively. No significant changes were seen when compared to those in patients with chronic diseases (P values were 0.36, 0.20, 0.66, and 0.08). The ratio of respiratory cycles to circulatory cycles was nearly 1:1 in both groups.
Conclusions:
This study demonstrates two principal observations: (I) precise synchronization between respiratory cycles and cardiovascular variability cycles during stable sleep phases; (II) lower HRV magnitudes observed in participants with chronic diseases compared to controls.
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