Holistic integrative analysis of circulatory parameters: effects of CPAP titration in patients with obstructive sleep apnea

Abstract

Background

The idea of Holistic Integrative Physiology and Medicine (HIPM) emphasizes integrated regulation, supporting the interconnected systems of respiration, circulation, and metabolism. This study aims to investigate the effects of continuous positive airway pressure (CPAP) on the physiological functions in patients with obstructive sleep apnea (OSA).

Methods

This self-controlled cohort study evaluated 20 patients with OSA for 48 hours using polysomnography (PSG). Natural sleep patterns were recorded on the first night of monitoring to provide baseline physiological data. Patients were instructed to utilize CPAP on the second night. The study involved a thorough analysis and calculation of a range of physiological parameters, including those related to respiratory, circulatory, and sleep parameters. To determine how CPAP affected each patient’s circulatory parameters, statistical comparisons were done between normal sleep and CPAP therapy.

Results

After the CPAP titration, OSA patients’ respiratory and circulatory parameters improved significantly on the second night. The apnea-hypopnea index (AHI) decreased to 4.82±3.90 events/h, heart rate (HR) averaged 60.25±7.08 bpm, systolic blood pressure (SBP) was 98.46±17.66 mmHg, and diastolic blood pressure (DBP) was 66.44±14.24 mmHg. Compared to the first night, these values significantly decreased (all P<0.001). In addition, circulatory parameter variability improved significantly (all P<0.05).

Conclusions

For patients with OSA, CPAP effectively reduces sleep apnea and related hypoxia. Moreover, it significantly improves circulatory parameters, indicating its potential as a long-term therapeutic solution.

Highlight box.

Key findings

• For patients with obstructive sleep apnea (OSA), continuous positive airway pressure (CPAP) effectively reduces sleep apnea and associated hypoxia. Moreover, it significantly improves circulatory parameters, indicating its potential as a long-term therapeutic solution.

What is known and what is new?

• CPAP is one of the commonly used methods to treat OSA.

• CPAP has been shown to significantly improve both respiratory and circulatory parameters in patients suffering from OSA. However, it is crucial to acknowledge that individuals respond differently to the CPAP therapy.

What is the implication, and what should change now?

• When CPAP is performed on OSA patients, a personalized approach to analysis and treatment adjustment is imperative.

Introduction

Obstructive sleep apnea (OSA) is a clinical illness caused by several reasons, characterized by frequent episodes of apnea and hypopnea during sleep. Such disruptions may result in sleep disorders and hypercapnia, triggering several physiological and pathological changes in the body. Recent epidemiological studies indicate that OSA is a common disease in the population, with an approximate 936 million individuals aged 30 to 69 affected globally. In China, the prevalence rate for this age range is a concerning 23.6%, with the patient count surpassing 175 million. Among these, more than 65 million individuals have a sleep apnea-hypopnea index (AHI) greater than 15 events per hour, resulting in a prevalence rate of 8.8%. The number of OSA patients in China exceeds that of both developed regions such as Europe and America, and developing regions in the Asia-Pacific and Africa, making it the highest globally (1). This epidemiological survey indicates an increasing trend in the prevalence and number of OSA patients in China when compared to previous data (2), signaling a forthcoming significant public health concern. In episodes of nocturnalapnea and hypopnea in OSA patients, there is significant fluctuation in circulatory parameters, including heart rate (HR), blood pressure (BP), heart rate variability (HRV) and blood pressure variability (BPV), a phenomenon closely linked to the onset and progression of cardiovascular and other systemic diseases (3-9). There’s a positive correlation between the alterations in circulatory parameters and AHI severity, higher AHI values indicate an increased risk of cardiovascular and cerebrovascular events (10,11). Although several studies (12-18) have explored the mechanisms of circulatory changes generated by OSA, the exact pathways are still not completely understood (19).

In order to better explore the mechanisms how respiratory changes affect circulatory parameters such as HR, BP, and oxygen saturation (SpO₂), it’s essential to recognize that people function as an integrated organic entity. The interaction between the respiratory and circulatory systems extends beyond the confines of these systems alone. The regulation of each system inside the human body is interrelated, and these systems collectively sustain physiological homeostasis (20). Therefore, an integrative perspective is required for an in-depth examination of these systems. This involves an interdisciplinary approach that includes cardiology, pulmonology, internal medicine, and other relevant specialties, facilitating a comprehensive and integrated understanding of various medical phenomena.

In recent years, the trend of interdisciplinary and medical integration has been very obvious (21,22), Under this trend, we have created a new theoretical system of the Holistic Integrative Physiology and Medicine (HIPM) (20,23-26), guided by the principles of HIPM, we present an innovative perspective on the “integrated regulation of respiration, circulation, and neurohumoral metabolism” (27). Traditionally, physiology has highlighted that respiratory control signals, including PaO₂ and PaCO₂, as well as [H⁺]a, modulate thoracic intrapulmonary pressure via pathways involving afferent nerves, the dorsal medullary respiratory control center, efferent nerves, and respiratory muscles, specifically at the peripheral chemoreceptors located in the aortic body and carotid artery, orchestrating the inspiratory and expiratory processes that underlie respiratory control (28,29). While this perspective holds merit, it is essential to recognize the interplay of the circulatory system in respiratory regulation. A compelling illustration of this interconnectedness is the presence of Cheyne-Stokes respiration (30) observed in patients with advanced congestive heart failure. Building upon this, we conceptualize an integrated circulatory loop involving both the anterior and posterior systems of the left ventricle, encompassing structures like the pulmonary vein, left atrium, left ventricle, aorta, and carotid artery. This loop underpins a comprehensive respiratory regulatory mechanism, which providing a holistic explanation for the integrated regulation spanning respiration (external), circulation, and metabolism (intracellular respiration) in human physiology. It’s imperative for breathing and circulation to synergize efficiently, ensuring that oxygen is delivered to the mitochondria—the cellular hub for energy metabolism—and in turn, guaranteeing adequate energy production to cater to the body’s demands. Additionally, baroreceptors, found within the peripheral chemoreceptors of the aortic body and carotid artery, regulate circulatory pressure. The medulla oblongata houses not only the regulatory center for circulation but also the pivotal center for respiratory regulation (28). Respiration and circulation are intrinsically linked to both cellular metabolism and systematic anatomy. Consequently, HR, blood pressure and other core parameters of circulatory system are bound to be affected by respiratory rhythm. Drawing on this understanding, we propose a hypothesis: The pronounced fluctuations in circulatory metrics (like HR, BP and their variabilities) observed in OSA patients during nocturnal hours stem from sleep-related apnea and hypopnea episodes. We further hypothesize that utilizing continuous positive airway pressure (CPAP) to rectify the respiratory patterns will lead to a reduction in average nocturnal circulatory parameters.

CPAP is a common therapy for OSA (31). The increasing usage of this treatment for patients with various degrees of OSA can be attributed to its non-invasive characteristic, cost-effectiveness, and proven therapeutic efficacy (32,33). However, most existing research predominantly examines the average and extreme values of respiratory and circulatory metrics before and after CPAP, along with CPAP’s effect on sleep stages. A significant deficiency exists in studies about continuous 48-hour physiological monitoring, comprehensive exploration of the relationship between respiratory and circulatory metric variations, and personalized pre-and post-analysis. To address this, our study initiated a comprehensive and impartial assessment. The major objective is to determine if CPAP therapy can effectively reduce the fluctuations in circulatory parameters at night by improving the abnormal breathing rhythms and patterns in patients with OSA. The study will assess changes in respiratory and circulatory parameters, including SpO₂, mean HR, mean BP, respiratory HRV and BPV during various sleep phases. We present this article in accordance with the STROBE reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-524/rc).

Methods

Research participants

This self-controlled cohort study assessed 20 individuals diagnosed with OSA, characterized by hypoxia and multiple chronic conditions, were assessed. Each participant had previously undergone comprehensive evaluations, including cardiopulmonary exercise testing (CPET) for cardiopulmonary function assessment and polysomnography (PSG) for sleep pattern analysis, at Fuwai Hospital. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The Ethics Committee of Fuwai Hospital approved the research protocol (No. 2023-2236). Informed consent was duly obtained from all participants.

Inclusion criteria:

1. Age over 18 years.

2. Clear diagnosis of at least one chronic non-communicable disease (e.g., hypertension, diabetes, hyperlipidemia, coronary heart disease, arteriosclerosis).

3. PSG evaluation showing AHI ≥15 times/hour.

4. Minimum of 7 hours of continuous PSG monitoring per night.

5. Presence of wave breathing during sleep.

Exclusion criteria:

1. Presence of severe respiratory diseases (e.g., advanced chronic obstructive pulmonary disease, cystic fibrosis).

2. Currently in the acute stage of cardiovascular or cerebrovascular diseases.

3. Pregnancy.

4. Secondary hypertension due to conditions such as renal artery stenosis or endocrine disorders.

5. Lower limb dysfunction impacting daily activities or sleep quality.

CPET evaluation

CPET scheme

The CPET was conducted using the Quark PFT Ergo system, manufactured by COSMEDS.R.L. in Italy. To ensure the accuracy of airflow exchange data, the system was calibrated daily with a metabolic simulator before serving patients. Before commencing the exercise test, participants first underwent a comprehensive static pulmonary function test in a seated position. Following this, an electromagnetically braked cycle ergometer was used. The power was incrementally increased according to the standards set by the Harbor-UCLA Medical Center (34,35).

CPET data analysis method

Data for all measured parameters were initially extracted from the software of the Quark PFT Ergo cardiopulmonary exercise test system by COSMED S.R.L., Italy. The raw data were segmented second-by-second using a breath-by-breath method (34). Analysis was then conducted following standard calculation principles.

PSG monitoring and evaluation

PSG monitoring process

The SOMNOscreenTM plus RC polysomnography instrument, manufactured by SOMNOmedics, Germany, was employed to monitor several parameters, including nasal airflow, HR, blood pressure, photoplethysmographic (PPG) pulse wave, electroencephalogram (EEG), and electromyogram (EMG). To acclimatize to the environment and equipment and mitigate the “first night effect”, all subjects were advised to wear the PSG device in the ward during daytime. The wear duration spanned continuously for 48 hours, encompassing two days and two nights. The first night was used to familiarize themselves with the wearing of equipment and ward. Participants were instructed to abstain from medications that influence sleep for a week preceding the monitoring. Additionally, during the monitoring phase, the consumption of sedatives, coffee, certain beverages, and any food or medication that could impact sleep was prohibited. Data points collected during periods of sensor detachment or malfunction and data artifacts resulting specifically from patient position changes will be excluded from the statistical analysis.

Criteria for diagnosing sleep apnea (AASM 1A criteria):

• ❖ Sleep apnea: ≥90% reduction in oronasal airflow amplitude from baseline lasting ≥10 seconds.

• ❖ Hypopnea: ≥30% reduction in oronasal airflow with either ≥3% oxygen desaturation or arousal, lasting ≥10 seconds.

PSG data calculation and analysis

The participant’s sleep state is determined based on EMG, EEG, body motion signals, and snoring detector readings. Data from PSG monitoring is segmented into sleep and awakening periods. Participants wore PSG for continuous monitoring in the ward for 48 hours. The sampling rate of nasal catheter respiratory airflow data is 128 Hz, the sampling rate of ECG R-R interval is 256 Hz, and the sampling rate of indirect blood pressure measurement based on pulse wave transit time (PTT) is 256 Hz. A non-linear relationship exists between PTT and blood pressure Using a mathematical model, blood pressure can be accurately measured without a cuff, and these measurements align well with readings from traditional cuff methods. The RS-651 sphygmomanometer from Beijing Xinxing Yangsheng Technology was used to take two blood pressure readings. The average of these readings was used to calibrate the baseline blood pressure obtained from the PSG.

Implementation and calculation of CPAP

We utilized the AirSense 10 AutoSetFH Plus C ventilator, produced by ResMed Company in Australia to conduct positive pressure sleep titration for patients with OSA during the night. The ventilator parameters were configured to AutoSet mode with a pressure range of 4 to 12 cmH₂O. The configuration includes a ramp delay boost set for 30 minutes, Response is off, and EPR level is 3. We connected the ventilator with a ResMed AirFit N10 nasal mask and the SlimLine ultrafine tube. Data on usage duration, AHI, and air leakage were retrieved during CPAP titration utilizing ResScan software (version 5.9.0.9629) supplied by the ResMed Company. To ensure proper fitting and patient comfort, all participants were directed to wear the nasal mask and commence CPAP treatment one hour before their bedtime. The CPAP data produced during this period were excluded from the statistical analysis.

Statistical analysis

The data were processed and analyzed using SPSS software, version 26. The results are reported as the mean ± standard deviation (SD) or number (%) for normally distributed and categorical variables or as the median (interquartile range) for nonnormally distributed variables unless otherwise indicated. Normally distributed continuous data were analyzed using unpaired or paired t-tests. Nonparametric continuous data were tested with the Mann-Whitney U test and Wilcoxon rank-sum test. Binomial data were analyzed using Fisher’s exact test. The significance level is set at 5%. Graphical representations were generated using Origin software.

Results

Analysis of participants’ general characteristics

This study encompassed 20 patients diagnosed with OSA, each experiencing varying degrees of hypoxia. The group consisted of 15 males and 5 females. Detailed demographic data, including age, height, weight, and BMI, are presented in Table S1. The average age of the participants was 58.50±10.79 years. Their average height and body weight were 169.15±6.42 cm and 74.50±13.95 kg, respectively, with a mean BMI of 25.92±4.08 kg/m² and a mean AHI of 28.65±10.79 events/h.

CPET core parameters analysis

For the group of OSA patients in this study, the CPET results were as follows: the value of peak oxygen uptake (peak $\dot{V}{O}_2$) was 80.17±15.93 %pred. The value of anaerobic threshold (AT) was 72.04±12.83 %pred. The value for work rate was 91.87±19.92 %pred. These detailed metrics are presented in Table S2.

Analysis of respiratory parameters before and after CPAP in OSA patients

The average sleep duration for OSA patients on the second night with CPAP was 6.94±1.08 hours. This was significantly lower than the sleep time of the first night without CPAP (P=0.01). A notable decrease in AHI was observed with CPAP utilization. The AHI in the second night with CPAP was 4.82±3.90 events per hour. This value was significantly lower than the AHI recorded on the first night without CPAP (P<0.001). The average SpO₂ and lowest SpO₂ values showed improvement with CPAP titration. During the second night with CPAP, the average SpO₂ and the lowest SpO₂ were 95.77%±0.43% and 89.05%±3.27%, respectively. These values were significantly higher than those recorded during the first night without CPAP (all P<0.001). In conclusion, the application of CPAP resulted in a significant improvement of respiratory parameters in OSA patients, as indicated by the statistical significance (all P<0.001). Additional information is provided in Table 1 and Figure 1A-1C.

Table 1. Impact of CPAP titration on respiratory parameters.

Parameter	First night without CPAP	Second night with CPAP	P value
BR, times/min	15.83±3.13	14.69±2.29	0.04
Sleep duration, h	7.89±1.15	6.94±1.08	0.01
AHI, events/h	28.65±10.79	4.82±3.90	<0.001
Mean SpO2, %	93.38±0.88	95.77±0.43	<0.001
Lowest SpO2, %	77.70±10.73	89.05±3.27	<0.001

The statistical significance of inter-group comparison between the first night and second night was calculated by paired t-test. AHI, apnea-hypopnea index; BR, breathing rate; CPAP, continuous positive airway pressure; Lowest-SpO₂, lowest value of percutaneous arterial oxygen saturation in the whole night; SpO₂, percutaneous arterial oxygen saturation.

Figure 1.

Analysis of respiration and circulatory parameter changes before and after CPAP titration in patients with OSA. This figure is divided into twelve sections (A-L), each presenting comparative charts of various respiratory and circulatory parameters in patients with OSA before and after CPAP titration: (A) the changes in AHI; (B) the variations in mean SpO₂; (C) the change in minimum SpO₂; (D) the variation in HR; (E) the variations in mean amplitude of HRV; (F) the variation in percentage of HRV; (G) the variation in SBP; (H) the variation in mean amplitude of SBPV; (I) the variation in percentage of SBPV; (J) the variation in DBP; (K) the variation in mean amplitude of DBPV; (L) the variation in percentage of DBPV. In each figure, the patterns flanking the x-axis denote the mean ± standard deviation for the first and second nights, respectively, for the data group being analyzed. The statistical differences between these two data sets were examined utilizing a paired t-test. AHI, apnea-hypopnea index; CPAP, continuous positive airway pressure; DBP, diastolic blood pressure; DBPV, diastolic blood pressure variability; HRV, heart rate variability; SBP, systolic blood pressure; SBPV, systolic blood pressure variability; SpO₂, percutaneous arterial oxygen saturation.

Analysis of circulatory parameters before and after CPAP in OSA patients

On comparison of the circulatory parameters in OSA patients, a significant reduction in average HR was seen during the second night of CPAP therapy. The HR were 60.25±7.08 bpm. This value significantly lower than the HR on the first night without CPAP (P<0.001). The breathing rate (BR) of OSA patients was 14.69±2.29 times per minute, significantly lower than that recorded on the first night (P=0.04). Similarly, HRV and HRV percentage (HRV%) decreased to 2.55±0.98 bpm and 4.17%±1.52%, respectively, indicating significant reductions compared to the first night (P=0.02 and P=0.03). Additional information is provided in Table 2 and Figure 1D-1F.

Table 2. Impact of CPAP titration on circulatory parameters.

Parameter	First night without CPAP	Second night with CPAP	P value
HR, bpm	64.15±7.32	60.25±7.08	<0.001
HRV, bpm	3.30±1.39	2.55±0.98	0.02
HRV%	5.24±2.20	4.17±1.52	0.03
SBP, mmHg	106.39±17.89	98.46±17.66	<0.001
DBP, mmHg	71.46±13.81	66.44±14.24	<0.001
SBPV, mmHg	3.42±1.27	2.67±0.64	0.02
DBPV, mmHg	3.08±0.77	2.43±0.50	<0.001
SBPV%	3.22±1.07	2.77±0.78	0.07
DBPV%	4.45±1.37	3.77±1.10	0.005

The statistical significance of inter-group comparison between the first night and second night was calculated by paired t-test. CPAP, continuous positive airway pressure; DBP, diastolic blood pressure; DBPV, diastolic blood pressure variability; HR, heart rate; HRV, heart rate variability; HRV%, percentage of mean amplitude of respiratory heart rate variability; SBP, systolic blood pressure; SBPV, systolic blood pressure variability.

Similarly, the average blood pressure during the second night with CPAP showed a reduction. The SBP was 98.46±17.66 mmHg and the DBP was 66.44±14.24 mmHg. Both these values were significantly lower than those recorded during the first night without CPAP (all P<0.001). During the second night with CPAP titration, mean value of systolic blood pressure variability (SBPV) was measured at 2.67±0.64 mmHg, whereas mean value of diastolic blood pressure variability (DBPV) was 2.43±0.50 mmHg. The percentage changes, SBPV% and DBPV%, were 2.77%±0.78% and 3.77%±1.10%, respectively. These values showed a significant decrease compared to the first night, with the exception of SBPV% (P=0.02, <0.001, 0.07, and 0.005, respectively). Additional information is provided in Table 2 and Figure 1G-1L.

The variations in respiratory and circulatory parameters of OSA patients before and after CPAP titration are depicted in Figure 2A,2B.

Figure 2.

Assessing changes in respiration and circulatory parameters before and after CPAP titration in patients with OSA. (A) Significant fluctuations in respiratory and circulatory parameters, including SpO₂, HR and BP (both SBP and DBP) during the first night. The observed fluctuations are consistent with the temporal pattern of OSA occurrences. A time delay of approximately 20 seconds exists between the rise and fall of SpO₂ and nasal airflow. This delay may be attributed to SpO₂ being a calculated value derived from the pulse wave, which results in a lower data sampling frequency and a display that follows the application of a moving average. As a result, the fourth rise and fall cycle of SpO₂ may not be fully represented. (B) Nasal airflow maintains relative stability in both cycle and amplitude during the period of CPAP usage on the second night. The circulatory parameters, including HR and BP (both SBP and DBP), exhibit small fluctuations that gradually rise and fall, following the nasal airflow cycle. Importantly, these fluctuations have notably lower baseline levels and amplitudes compared to those observed during OSA occurrences on the first night. Additionally, SpO₂ remains stable at the normal level of 96%. It’s important to note that Figure (A) and Figure (B) employ different scales to emphasize the subtle circulatory parameter fluctuations with each change in nasal airflow, allowing for a more effective visualization of their distinct characteristics. BP, blood pressure; CPAP, continuous positive airway pressure; DBP, diastolic blood pressure; Flow, nasal airflow; HR, heart rate; OSA, obstructive sleep apnea; SBP, systolic blood pressure; SpO₂, percutaneous arterial oxygen saturation.

Figure 3 illustrates the alterations noted in each patient during normal respiration on the first night and period of CPAP titration on the second night.

Figure 3.

Analysis of respiration and circulatory parameter changes during normal breathing on the first night and period of CPAP titration on the second night. (A-I) This figure is divided into nine sections, each presenting comparative charts of different respiratory and circulatory parameters in patients with OSA during normal breathing on the first night and period of CPAP titration on the second night: (A) the change in HR; (B) the change in mean amplitude of HRV; (C) the change in percentage of HRV; (D) the change in SBP; (E) the change in mean amplitude of SBPV; (F) the change in percentage of SBPV; (G) the change in DBP; (H) the change in mean amplitude of DBPV; (I) the change in percentage of DBPV. In each figure, the patterns flanking the x-axis represent the mean ± standard deviation for the normal breathing on the first night and period of CPAP titration on the second night, respectively. The statistical differences between these two sets of data were analyzed using a paired t-test. CPAP, continuous positive airway pressure; DBP, diastolic blood pressure; DBPV, diastolic blood pressure variability; HR, heart rate; HRV, heart rate variability; OSA, obstructive sleep apnea; SBP, systolic blood pressure; SBPV, systolic blood pressure variability.

Discussion

This study demonstrated significant improvements in circulatory parameters among OSA patients following the correction of nocturnal respiratory patterns, suggesting a strong correlation between circulatory function and respiratory regulation in OSA (25). These findings underscore the critical role of respiratory management in optimizing cardiovascular outcomes in this patient population.

Our data revealed significant elevations in HR, HRV, and HRV% during the initial sleep period without CPAP intervention compared to subsequent CPAP-treated nights. Although HRV is typically suppressed in OSA patients (36-38), its transient elevation during apneic episodes may represent a compensatory mechanism. However, this increased variability imposes additional hemodynamic stress, potentially exacerbating cardiovascular risk (3). Sympathetic activation during respiratory disturbances contributes to acute increases in HR and HRV parameters, with cumulative effects observed throughout the sleep period.

CPAP therapy significantly improved HRV-related parameters in the majority of patients, though interindividual variability was noted. The standard CPAP pressure range (4–12 cmH₂O) may not be optimal for all patients, highlighting the necessity for personalized treatment strategies. Our findings emphasize the importance of customizing CPAP protocols to optimize autonomic function while minimizing cardiovascular strain

According to the HIPM perspective, the integrated regulation of respiration, circulation, and metabolism constitutes a fundamental physiological principle (20,23-26,39). This regulatory framework is primarily mediated through arterial blood gas oscillations {PaO₂, PaCO₂, and [H+]a}, which serve as primary respiratory modulators. Experimental evidence has confirmed the existence of these oscillatory patterns, providing a mechanistic basis for understanding respiratory control (40-43).

Under normal physiological conditions, venous blood, following gas exchange in the pulmonary capillaries, transforms into arterial blood enriched with these wave signals. The oxygenated blood then flows into the left heart, reaching the rapid-response chemoreceptors located in the aortic arch and carotid body. This mechanism initiates the transition between respiratory phases. However, the regulation by peripheral fast-response chemoreceptors operates in a ‘strong-strong’ and ‘weak-weak’ mode, which alone does not produce steady respiration. Thus, a steady respiratory rhythm requires the synchronization of slow-response chemoreceptors. A key aspect of this coordination is the ‘phase dislocation’—a time discrepancy of approximately 30 seconds between the rapid-response and slow-response chemoreceptors in detecting the same respiratory signal (25). Moreover, respiratory regulatory signals can directly and indirectly change sympathetic and parasympathetic neuronal activities via peripheral chemoreceptors, hence influencing cardiovascular function and inducing fluctuations in circulatory parameters.

In OSA patients, especially those with chronic diseases, sleep-related apnea and hypopnea lead to decreased amplitude of PaO₂, PaCO₂, and [H⁺]a wave signals. This decrease leads to a reduced amplitude in following respiratory cycles due to the ‘strong-strong’ and ‘weak-weak’ response patterns of peripheral fast-response chemoreceptors, resulting in a corresponding decrease inHRV. After about 30 seconds, the slow-response chemoreceptors in the respiratory center detect the diminished signal amplitude and enhance the sensitivity of the peripheral fast-response chemoreceptors via efferent neurons. This effect enhances the amplitude of respiratory cycles and increases HR (25). The interaction of these mechanisms results in an increased mean amplitude of fluctuation in circulatory parameters in OSA patients during sleep, as observed in our study.

CPAP intervention significantly reduced the frequency of respiratory disturbances, leading to improved respiratory stability and decreased cardiovascular variability. This stabilization was particularly evident in HRV and BPV parameters, demonstrating the therapeutic efficacy of CPAP in modulating both respiratory and cardiovascular function.

Our investigation further revealed significantly elevated BPV during apneic episodes compared to periods of normal respiration. CPAP therapy reduced both mean arterial pressure and BPV, demonstrating its antihypertensive effects. However, a pivotal randomized controlled trial has shown that although CPAP improves daytime sleepiness, quality of life, mood and work attendance in patients with moderate to severe OSA and patients with pre-existing cardiovascular disease, it does not significantly reduce the primary composite endpoint (cardiovascular death, myocardial infarction, stroke or hospitalization due to heart failure/unstable angina pectoris/transient ischemic attack) (44).

The pathological elevation of BPV warrants particular attention due to its well-established association with cardiovascular and cerebrovascular morbidity. Increased BPV may accelerate atherogenesis, impair cerebral autoregulation, and promote vascular remodeling (9,45-47). Effective management of nocturnal BPV in OSA patients, particularly those with pre-existing cardiovascular conditions, is therefore clinically imperative.

Despite demonstrated therapeutic efficacy, CPAP adherence remains a significant clinical challenge. The current CPAP utilization rate in mainland China (approximately 45%) remains substantially lower than in Western countries, particularly in outpatient settings (48). This disparity underscores the need for enhanced patient education and awareness regarding OSA pathophysiology and CPAP benefits.

Limitations

A main limitation of this study is limited sample size. A limited number of participants may fail to provide a comprehensive representation, hence potentially distorting the results. Moreover, the broad age range among participants may bring variability absent in a more homogeneous group. Age-related physiological differences can significantly impact both respiratory and circulatory parameters, limiting the ability to get precise findings from this diverse cohort. This study focused on the immediate effects of a solitary CPAP titration session. It may not consider long-term impacts or the potential benefits of continued CPAP titration over time.

Conclusions

Our findings demonstrate the therapeutic efficacy of CPAP in improving respiratory and cardiovascular parameters in OSA patients. The HIPM framework provides a valuable paradigm for understanding the complex interplay between respiratory control and cardiovascular function in OSA. Future research should focus on optimizing therapeutic protocols and improving treatment adherence to maximize clinical outcomes in this patient population.

Supplementary

The article’s supplementary files as

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The Ethics Committee of Fuwai Hospital approved the research protocol (No. 2023-2236). Informed consent was duly obtained from all participants.

Data Sharing Statement

Available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-524/dss

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DOI: 10.21037/jtd-24-524