Obstructive Sleep Apnea and Heart Rate Variability in Male Patients with Metabolic Syndrome: Cross-Sectional Study

Novel metrics of sleep-disordered breathing are associated with outcome after ischemic stroke

OBJECTIVE/BACKGROUND

Standard measures of sleep-disordered breathing (SDB) that rely on count data may not sufficiently capture SDB severity or reflect downstream consequences of SDB. We hypothesized that novel metrics derived from pulse rate, oxygen saturation, and nasal pressure would be associated with stroke outcomes.

PATIENTS/METHODS

Shortly after ischemic stroke, participants in a population-based study were offered ApneaLink Plus testing. Signal analysis was used to generate 166 metrics from the nasal pressure cannula and finger probe, categorized as: autonomic (based on pulse rate variability), oximetry-derived, nasal pressure-derived, and mixed oxygen and nasal pressure-derived measures. Three-month outcome assessments included functional and cognitive outcomes and stroke recurrence. Tobit regression and Cox proportional hazards models were used to examine associations between each sleep apnea metric and the three outcomes, unadjusted and adjusted for multiple potential confounders. Models were adjusted for multiple comparisons.

RESULTS

Of the 530 participants, the median age was 65 (IQR: 57, 73), 49 % were female, and 64 % were Mexican American. Without covariate adjustment, 23 of 166 variables were associated with functional outcome, 43 were associated with cognitive outcome, and 1 was associated with stroke recurrence. After adjustment, 7 mixed, oximetry, or nasal pressure-based metrics and 1 autonomic metric were associated with functional outcome, but none was associated with cognitive outcome or stroke recurrence.

CONCLUSIONS

Many novel metrics of SDB were associated with important stroke outcomes, and 8 novel metrics were associated with functional outcome in adjusted models. This raises hypotheses about pathways by which SDB may negatively impact stroke outcomes.

Reduced heart rate variability is related to the number of metabolic syndrome components and manifest diabetes in the sixth Tromsø study 2007-2008

Both diabetes mellitus (DM) and the metabolic syndrome (MetS) are associated with autonomic neuropathy, which predisposes to cardiac events and death. Measures of heart rate variability (HRV) can be used to monitor the activity of the autonomic nervous system (ANS), and there are strong indications that HRV can be used to study the progression of ANS-related diabetes complications. This study aims to investigate differences in HRV in healthy, MetS and diabetic populations. Based on 7880 participants from the sixth health survey in Tromsø (Tromsø 6, 2007–2008), we found a significant negative association between the number of MetS components and HRV as estimated from short-term pulse wave signals (PRV). This decrease in PRV did not appear to be linear, instead it leveled off after the third component, with no significant difference in PRV between the MetS and DM populations. There was a significant negative association between HbA1c and PRV, showing a decrease in PRV occurring already within the normal HbA1c range. The MetS and DM populations are different from healthy controls with respect to PRV, indicating impaired ANS in both conditions. In the future, a study with assessment of PRV measurements in relation to prospective cardiovascular events seems justified.

Heart Rate Variability in the Diagnostics and CPAP Treatment of Obstructive Sleep Apnea

Obstructive sleep apnea (OSA) is the most common manifestation of sleep-related breathing disorders that are often accompanied by dysfunction of the autonomic nervous system. The main objective of the study was to assess the usefulness of heart rate variability (HRV) analysis in the diagnosis of patients with severe OSA and in the assessment of the effects of 3-month treatment with continuous positive airway pressure (CPAP). There were 54 patients enrolled in the study. The OSA group consisted of 39 patients suffering from severe OSA (apnea/hypopnea index >30/h), and the control group included 15 non-OSA patients with matched demographic characteristics and comorbidities. All patients underwent 24-h Holter electrocardiographic monitoring. HRV was analyzed using the time- and frequency-domains. We found that OSA patients had decreases in time-domains and increases in frequency-domains of HRV, compared to non-OSA controls, which strongly suggested a clinically disadvantageous shift in the balance of parasympathetic/sympathetic activity toward the latter. Further, CPAP treatment, partly, albeit significantly, reversed the OSA-induced changes in HRV. We conclude that HRV analysis may be of help in the diagnosis of OSA and in the monitoring of the effectiveness of treatment.

Nocturnal heart rate variation in diabetic and non-diabetic patients with sleep apnea syndrome

OBJECTIVES

Heart rate variability (HRV) analysis is used for the evaluation of autonomic function in the cardiovascular system. Decreased HRV is associated with disorders affecting the autonomous system such as diabetes mellitus (DM) and obstructive sleep apnea (OSA). Previous studies have shown an association between OSA and DM. However, the interrelationships of HRV with OSA and DM are not well known. The aim of this study was to assess nocturnal HRV in patients who suffered from OSA with and without DM.

METHODS

Sixty patients with OSA (27 with DM and 33 non-DM) underwent polysomnography for eight hours starting at midnight. From electrocardiogram (ECG) recordings taken as a part of polysomnography, time-domain and frequency-domain HRV parameters were evaluated to compare patients with regard to nocturnal HRV components such as low frequency (LF) and high frequency (HF), apnea-hypopnea index (AHI) and sleep parameters.

RESULTS

In the non-DM group, a direct relationship was observed between AHI and HRV rather than very low frequency (VLF) and LF/HF variables. This relationship was just significant between AHI and standard deviation of five-min average of normal R-R intervals and adjacent R-R intervals differing by 0.50 ms over 24 h (p < 0.05). In the DM group, the correlation between AHI and HRV parameters except HF and waking frequency was direct and non-significant. Intergroup comparison showed a significant difference between groups regarding AHI and HRV-index, LF and VLF (p < 0.05).

CONCLUSIONS

DM can affect HRV; however, this is not the case in OSA patients. This means that in the presence of OSA, the DM effect on HRV disappears.