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It is still not known whether the oscillation in heart rate (HR) induced by sleep‐disordered breathing (SDB) in patients with heart failure entails significant chronotropic effects. We hypothesised that since cyclical changes in ventilation and arterial blood gases during SDB affect HR through multiple and complexly interacting mechanisms characterised by large inter‐subject variability, chronotropic effects may change from patient to patient. A total of 42 patients with moderate‐to‐severe chronic heart failure with systolic dysfunction underwent an in‐hospital sleep study. Chronotropic effects of SDB were quantified by comparing the distribution of instantaneous HR during SDB with that during periods without SDB (noSDB) within the same night in each patient. Based on distribution changes from noSDB to SDB, 12, nine, 11, and 10 patients showed a significant tachycardic, bradycardic, tachycardic and bradycardic, and neither significant tachycardic nor significant bradycardic effect, respectively. Tachycardic and bradycardic effects were primarily due to an increase in the rate rather than in the magnitude of cyclical HR elevations and reductions, and were more prevalent and severe in patients with dominant obstructive and central events, respectively. The apnea–hypopnea index did not differ between groups. Conversely, the time spent with an oxygen saturation of <90% was greater in the tachycardic and tachycardic‐bradycardic groups compared to the bradycardic group. These findings indicate that HR distribution changes induced by SDB can vary from patient to patient revealing four distinct and well‐characterised chronotropic effects. These effects are related to the degree of hypoxic burden brought about by SDB and are affected by the type of sleep apnea (central/obstructive). [ABSTRACT FROM AUTHOR]

Fluctuations in sleep-wake state are thought to contribute to the respiratory instability of Cheyne-Stokes respiration in patients with heart failure by promoting the rhythmic occurrence of central apnea and ventilatory overshoot. There are no data, however, on the relationship between vigilance state and respiratory events. In this study we used a novel method to detect the occurrence of state transitions (time resolution: 0.25 s, minimum duration of state changes: 2 s) and to assess their time relationship with apnoeic events. We also evaluated whether end-apnoeic arousals are associated with a ventilatory overshoot. A polysomnographic, daytime laboratory recording (25 min) was performed during Cheyne-Stokes respiration in 16 patients with heart failure. Automatic state classification included wakefulness and non-rapid eye movement sleep stages 1-2. As a rule, wakefulness occurred during hyperpnoeic phases, and non-rapid eye movement sleep occurred during apnoeic events. Ninety-two percent of the observed central apneas ( N = 272) were associated with a concurrent wakefulness → non-rapid eye movement sleep → wakefulness transition. The delay between wakefulness → non-rapid eye movement sleep transitions and apnea onset was −0.3 [−3.1, 3.0] s [median (lower quartile, upper quartile); P = 0.99 testing the null hypothesis: median delay = 0], and the delay between non-rapid eye movement sleep → wakefulness transitions and apnea termination was 0.2 [−0.5, 1.2] s ( P = 0.7). A positive/negative delay indicates that the state transition occurred before/after the onset or termination of apnea. Non-rapid eye movement sleep → wakefulness transitions synchronous with apnea termination were associated with a threefold increase in tidal volume and a twofold increase in ventilation (all P < 0.001), indicating ventilatory overshoot. These findings highlight that wakefulness → non-rapid eye movement sleep → wakefulness transitions parallel apnoeic events during Cheyne-Stokes respiration in patients with heart failure. The relationships between state changes and respiratory events are consistent with the notion that state fluctuations promote ventilatory instability. [ABSTRACT FROM AUTHOR]

Home monitoring is the most practical means of collecting sleep data in large‐scale research investigations. Because the portion of recording time with poor‐quality data is higher than in attended polysomnography, a quantitative assessment of the quality of each signal should be recommended. Currently, only qualitative or semi‐quantitative assessments are carried out, likely because of the lack of computer‐based applications to carry out this task efficiently. This paper presents an innovative computer‐assisted procedure designed to perform a quantitative quality assessment of standard respiratory signals recorded by Type 2 and Type 3 portable sleep monitors. The proposed system allows to assess the quality (good versus bad) of consecutive 1‐min segments of thoraco‐abdominal movements, oronasal, nasal airflow and oxygen saturation through an automatic classifier. The performance of the classifier was evaluated in a sample of 30 unattended polysomnography recordings, comparing the computer output with the consensus of two expert scorers. The difference (computer versus scorers) in the percentage of good‐quality segments was on average very small, ranging from −3.1% (abdominal movements) to 0.8% (nasal flow), with an average total classification accuracy from 90.2 (oronasal flow) to 94.9 (nasal flow), a Sensitivity from 0.93 (oronasal flow) to 0.98 (nasal flow), and a Specificity from 0.74 (nasal flow) to 0.86 (abdominal movements). In practical applications, the scorer can run a check‐and‐edit procedure, further improving the classification accuracy. Considering a sample of 270 unattended polysomnography recordings (recording time: 545 ± 44 min), the average time taken for the check‐and‐edit procedure of each recording was 6.9 ± 2.1 min for all respiratory signals. [ABSTRACT FROM AUTHOR]

Objective. To determine the optimal frequency and site of stimulation for transcutaneous vagus nerve stimulation (tVNS) to induce acute changes in the autonomic profile (heart rate (HR), heart rate variability (HRV)) in healthy subjects (HS) and patients with heart failure (HF). Approach. We designed three single-blind, randomized, cross-over studies: (1) to compare the acute effect of left tVNS at 25 Hz and 10 Hz ( n = 29, age 60 ± 7 years), (2) to compare the acute effect of left and right tVNS at the best frequency identified in study 1 ( n = 28 age 61 ± 7 years), and (3) to compare the acute effect of the identified optimal stimulation protocol with sham stimulation in HS and HF patients ( n = 30, age 59 ± 5 years, and n = 32, age 63 ± 7 years, respectively). Main results. In study 1, left tragus stimulation at 25 Hz was more effective than stimulation at 10 Hz in decreasing HR (-1.0 ± 1.2 bpm, p < 0.001 and -0.5 ± 1.6 bpm, respectively) and inducing vagal effects (significant increase in RMSSD, and HF power). In study 2, the HR reduction was greater with left than right tragus stimulation (-0.9 ± 1.5 bpm, p < 0.01 and -0.3 ± 1.4 bpm, respectively). In study 3 in HS, left tVNS at 25 Hz significantly reduced HR, whereas sham stimulation did not (-1.1 ± 1.2 bpm, p < 0.01 and -0.2 ± 2.9 bpm, respectively). In HF patients, both active and sham stimulation produced negligible effects. Significance. Left tVNS at 25 Hz is effective in acute modulation of cardiovascular autonomic control (HR, HRV) in HS but not in HF patients (NCT05789147)., (© 2024 Institute of Physics and Engineering in Medicine.)

In this manuscript we present an overview of novel signal processing techniques developed by our group to reduce scoring time in the assessment of the severity of sleep-related breathing disorders in heart failure patients and to detect sleep/wake fluctuations during periodic breathing. Besides describing these methods, we present the results of validation experiments. Our work shows that novel signal processing techniques can reduce costs and resources needed to screen the patients and can provide relevant information for better understanding the role of wake/sleep transitions in the development and maintenance of breathing disorders.

In this study we investigated the existence and the nature of rhythmic changes in EEG associated with ventilatory oscillations in heart failure (HF) patients with periodic breathing (PB). Since nonlinear mechanisms are thought to be involved in the generation of EEG, we hypothesized that a mathematical approach based on nonlinear methods would provide relevant information on the association between EEG and ventilatory oscillations. We studied five patients who developed a sustained non-obstructive PB pattern during a 20 min laboratory recording. The time course of the fractal dimension of the EEG signal (HFD) was estimated dividing this signal into 2 s segments, with a 1.5 s overlap and computing for each EEG segment the fractal dimension using the Higuchi's algorithm. From the lung volume signal, an instantaneous minute ventilation (IMV) signal was also computed. The relationship between IMV and HFD was assessed by bivariate spectral analysis, computing the magnitude square coherence function (MSC). In four patients the value of the MSC was very high, ranging from 0.75 to 0.91, while in one patient the value was only 0.29. Our results suggest that in patients with PB, rhythmic changes in the EEG signal are very common and, when present, they are associated with ventilatory oscillations. We have also demonstrated that such oscillations can be detected very effectively by a technique based on nonlinear methods.

This study was conceived to analyze EEG state transitions and their relationship with ventilatory oscillations during daytime supine periodic breathing (PB) in heart failure patients. To this purpose, a semi-automated, frequency-based methodology was developed, and testing was carried out in 5 patients with PB. We found that apneas and hypopneas very often (86% on average) begin in synchrony with transitions from wakefulness to theta activity, and end in synchrony with the opposite transition. These results suggest that in these patients chemical instability secondary to the impaired hemodynamics coexists and interacts with state instability.