Study of multiparameter respiratory pattern complexity in surgical critically ill patients during weaning trials

Pulse respiration quotient as a measure sensitive to changes in dynamic behavior of cardiorespiratory coupling such as body posture and breathing regime

Objective: In this research we explored the (homeo)dynamic character of cardiorespiratory coupling (CRC) under the influence of different body posture and breathing regimes. Our tool for it was the pulse respiration quotient (PRQ), representing the number of heartbeat intervals per breathing cycle. We obtained non-integer PRQ values using our advanced Matlab^® algorithm and applied it on the signals of 20 healthy subjects in four conditions: supine position with spontaneous breathing (Supin), standing with spontaneous breathing (Stand), supine position with slow (0.1 Hz) breathing (Supin01) and standing with slow (0.1 Hz) breathing (Stand01). Main results: Linear features of CRC (in PRQ signals) were dynamically very sensitive to posture and breathing rhythm perturbations. There are obvious increases in PRQ mean level and variability under the separated and joined influence of orthostasis and slow (0.1 Hz) breathing. This increase was most pronounced in Stand01 as the state of joint influences. Importantly, PRQ dynamic modification showed greater sensitivity to body posture and breathing regime changes than mean value and standard deviation of heart rhythm and breathing rhythm. In addition, as a consequence of prolonged supine position, we noticed the tendency to integer quantization of PRQ (especially after 14 min), in which the most common quantization number was 4:1 (demonstrated in other research reports as well). In orthostasis and slow breathing, quantization can also be observed, but shifted to other values. We postulate that these results manifest resonance effects induced by coupling patterns from sympathetic and parasympathetic adjustments (with the second as dominant factor). Significance: Our research confirms that cardiorespiratory coupling adaptability could be profoundly explored by precisely calculated PRQ parameter since cardiorespiratory regulation in healthy subjects is characterized by a high level of autonomic adaptability (responsiveness) to posture and breathing regime, although comparisons with pathological states has yet to be performed. We found Stand01 to be the most provoking state for the dynamic modification of PRQ (cardiorespiratory inducement). As such, Stand01 has the potential of using for PRQ tuning by conditioning the cardiorespiratory autonomic neural networks, e.g., in the cases where PRQ is disturbed by environmental (i.e., microgravity) or pathologic conditions.

Breathing rate variability in obstructive sleep apnea during wakefulness

STUDY OBJECTIVES

Obstructive sleep apnea (OSA) is defined by pauses in breathing during sleep, but daytime breathing dysregulation may also be present. Sleep may unmask breathing instability in OSA that is usually masked by behavioral influences during wakefulness. A breath-hold (BH) challenge has been used to demonstrate breathing instability. One measure of breathing stability is breathing rate variability (BRV). We aimed to assess BRV during rest and in response to BH in OSA.

METHODS

We studied 62 participants (31 with untreated OSA: respiratory event index [mean ± SD] 20 ± 15 events/h, 12 females, age 51 ± 14 years, body mass index [BMI] 32 ± 8 kg/m²; 31 controls: 17 females, age 47 ± 13 years; BMI 26 ± 4 kg/m²). Breathing movements were collected using a chest belt for 5 minutes of rest and during a BH protocol (60 seconds baseline, 30 seconds BH, 90 seconds recovery, 3 repeats). From the breathing movements, we calculated median breathing rate (BR) and interquartile BRV at rest. We calculated change in BRV during BH recovery from baseline. Group comparisons of OSA vs control were conducted using analysis of covariance with age, sex, and BMI as covariates.

RESULTS

We found 10% higher BRV in OSA vs controls (P < .05) during rest. In response to BH, BRV increased 7% in OSA vs 1% in controls (P < .001). Resting BR was not significantly different in OSA and controls, and sex and age did not have any significant interaction effects. BMI was associated with BR at rest (P < .05) and change in BRV with BH (P < .001), but no significant BMI-by-group interaction effect was observed.

CONCLUSIONS

The findings suggest breathing instability as reflected by BRV is high in OSA during wakefulness, both at rest and in response to a stimulus. Breathing instability together with high blood pressure variability in OSA may reflect a compromised cardiorespiratory consequence in OSA during wakefulness.

CITATION

Pal A, Martinez F, Akey MA, et al. Breathing rate variability in obstructive sleep apnea during wakefulness. J Clin Sleep Med. 2022;18(3):825-833.

Automated Classification of Whole Body Plethysmography Waveforms to Quantify Breathing Patterns

Whole body plethysmography (WBP) monitors respiratory rate and depth but conventional analysis fails to capture the diversity of waveforms. Our first purpose was to develop a waveform cluster analysis method for quantifying dynamic changes in respiratory waveforms. WBP data, from adult Sprague-Dawley rats, were sorted into time domains and principle component analysis was used for hierarchical clustering. The clustering method effectively sorted waveforms into categories including sniffing, tidal breaths of varying duration, and augmented breaths (sighs). We next used this clustering method to quantify breathing after opioid (fentanyl) overdose and treatment with ampakine CX1942, an allosteric modulator of AMPA receptors. Fentanyl caused the expected decrease in breathing, but our cluster analysis revealed changes in the temporal appearance of inspiratory efforts. Ampakine CX1942 treatment shifted respiratory waveforms toward baseline values. We conclude that this method allows for rapid assessment of breathing patterns across extended data recordings. Expanding analyses to include larger portions of recorded WBP data may provide insight on how breathing is affected by disease or therapy.

Biosignal-Based Digital Biomarkers for Prediction of Ventilator Weaning Success

We evaluated new features from biosignals comprising diverse physiological response information to predict the outcome of weaning from mechanical ventilation (MV). We enrolled 89 patients who were candidates for weaning from MV in the intensive care unit and collected continuous biosignal data: electrocardiogram (ECG), respiratory impedance, photoplethysmogram (PPG), arterial blood pressure, and ventilator parameters during a spontaneous breathing trial (SBT). We compared the collected biosignal data's variability between patients who successfully discontinued MV (n = 67) and patients who did not (n = 22). To evaluate the usefulness of the identified factors for predicting weaning success, we developed a machine learning model and evaluated its performance by bootstrapping. The following markers were different between the weaning success and failure groups: the ratio of standard deviations between the short-term and long-term heart rate variability in a Poincaré plot, sample entropy of ECG and PPG, α values of ECG, and respiratory impedance in the detrended fluctuation analysis. The area under the receiver operating characteristic curve of the model was 0.81 (95% confidence interval: 0.70-0.92). This combination of the biosignal data-based markers obtained during SBTs provides a promising tool to assist clinicians in determining the optimal extubation time.

Development and validation of a sample entropy-based method to identify complex patient-ventilator interactions during mechanical ventilation

Patient-ventilator asynchronies can be detected by close monitoring of ventilator screens by clinicians or through automated algorithms. However, detecting complex patient-ventilator interactions (CP-VI), consisting of changes in the respiratory rate and/or clusters of asynchronies, is a challenge. Sample Entropy (SE) of airway flow (SE-Flow) and airway pressure (SE-Paw) waveforms obtained from 27 critically ill patients was used to develop and validate an automated algorithm for detecting CP-VI. The algorithm's performance was compared versus the gold standard (the ventilator's waveform recordings for CP-VI were scored visually by three experts; Fleiss' kappa = 0.90 (0.87-0.93)). A repeated holdout cross-validation procedure using the Matthews correlation coefficient (MCC) as a measure of effectiveness was used for optimization of different combinations of SE settings (embedding dimension, m, and tolerance value, r), derived SE features (mean and maximum values), and the thresholds of change (Th) from patient's own baseline SE value. The most accurate results were obtained using the maximum values of SE-Flow (m = 2, r = 0.2, Th = 25%) and SE-Paw (m = 4, r = 0.2, Th = 30%) which report MCCs of 0.85 (0.78-0.86) and 0.78 (0.78-0.85), and accuracies of 0.93 (0.89-0.93) and 0.89 (0.89-0.93), respectively. This approach promises an improvement in the accurate detection of CP-VI, and future study of their clinical implications.

Slow 0.1 Hz Breathing and Body Posture Induced Perturbations of RRI and Respiratory Signal Complexity and Cardiorespiratory Coupling

Objective: We explored the physiological background of the non-linear operating mode of cardiorespiratory oscillators as the fundamental question of cardiorespiratory homeodynamics and as a prerequisite for the understanding of neurocardiovascular diseases. We investigated 20 healthy human subjects for changes using electrocardiac RR interval (RRI) and respiratory signal (Resp) Detrended Fluctuation Analysis (DFA, α1RRI, α2RRI, α1Resp, α2Resp), Multiple Scaling Entropy (MSERRI1-4, MSERRI5-10, MSEResp1-4, MSEResp5-10), spectral coherence (CohRRI-Resp), cross DFA (ρ1 and ρ2) and cross MSE (XMSE1-4 and XMSE5-10) indices in four physiological conditions: supine with spontaneous breathing, standing with spontaneous breathing, supine with 0.1 Hz breathing and standing with 0.1 Hz breathing. Main results: Standing is primarily characterized by the change of RRI parameters, insensitivity to change with respiratory parameters, decrease of CohRRI-Resp and insensitivity to change of in ρ1, ρ2, XMSE1-4, and XMSE5-10. Slow breathing in supine position was characterized by the change of the linear and non-linear parameters of both signals, reflecting the dominant vagal RRI modulation and the impact of slow 0.1 Hz breathing on Resp parameters. CohRRI-Resp did not change with respect to supine position, while ρ1 increased. Slow breathing in standing reflected the qualitatively specific state of autonomic regulation with striking impact on both cardiac and respiratory parameters, with specific patterns of cardiorespiratory coupling. Significance: Our results show that cardiac and respiratory short term and long term complexity parameters have different, state dependent patterns. Sympathovagal non-linear interactions are dependent on the pattern of their activation, having different scaling properties when individually activated with respect to the state of their joint activation. All investigated states induced a change of α1 vs. α2 relationship, which can be accurately expressed by the proposed measure-inter-fractal angle θ. Short scale (α1 vs. MSE1-4) and long scale (α2 vs. MSE5-10) complexity measures had reciprocal interrelation in standing with 0.1 Hz breathing, with specific cardiorespiratory coupling pattern (ρ1 vs. XMSE1-4). These results support the hypothesis of hierarchical organization of cardiorespiratory complexity mechanisms and their recruitment in ascendant manner with respect to the increase of behavioral challenge complexity. Specific and comprehensive cardiorespiratory regulation in standing with 0.1 Hz breathing suggests this state as the potentially most beneficial maneuver for cardiorespiratory conditioning.

Ventilatory pattern variability as a biometric for severity of acute lung injury in rats

We hypothesize that ventilatory pattern variability (VPV) varies with the magnitude of acute lung injury (ALI). In adult male rats, we instilled a low- or high- dose of bleomycin or saline (PBS) intratracheally. While representative samples of pulmonary tissue indicated graded lung injury, coefficient of variation (CV) of TTOT did not differ among the 3 groups. Broncho-alveolar lavage fluid (BALF), respiratory rate (fR), mutual information were greater in ALI than sham rats; but did not differ between bleomycin doses. However, nonlinear complexity index (NLCI), which is the difference in sample entropy between original and surrogate data sets was greater for high- versus low- dose; but did not differ between low-dose and sham groups. Further, NLCI correlated to an injury index based on protein concentration of BALF and failure to gain weight. Finally, Receiver Operator Curves (ROCs) indicated that both mutual information and NLCI had greater sensitivity and specificity than fR and CVTTOT in identifying ALI. Thus, nonlinear analyses of VPV can distinguish ALI and out performs fR as a biometric.

Univariate and multivariate conditional entropy measures for the characterization of short-term cardiovascular complexity under physiological stress

OBJECTIVE

A defining feature of physiological systems under the neuroautonomic regulation is their dynamical complexity. The most common approach to assess physiological complexity from short-term recordings, i.e. to compute the rate of entropy generation of an individual system by means of measures of conditional entropy (CE), does not consider that complexity may change when the investigated system is part of a network of physiological interactions. This study aims at extending the concept of short-term complexity towards the perspective of network physiology, defining multivariate CE measures whereby multiple physiological processes are accounted for in the computation of entropy rates.

APPROACH

Univariate and multivariate CE measures are computed using state-of-the-art methods for entropy estimation and applied to time series of heart period (H), systolic (S) and diastolic (D) arterial pressure, and respiration (R) variability measured in healthy subjects monitored in a resting state and during conditions of postural and mental stress.

MAIN RESULTS

Compared with the traditional univariate metric of short-term complexity, multivariate measures provide additional information with plausible physiological interpretation, such as (i) the dampening of respiratory sinus arrhythmia and activation of the baroreflex control during postural stress; (ii) the increased complexity of heart period and blood pressure variability during mental stress, reflecting the effect of respiratory influences and upper cortical centers; (iii) the strong influence of D on S, mediated by left ventricular ejection fraction and vascular properties; (iv) the role of H in reducing the complexity of D, related to cardiac run-off effects; and (v) the unidirectional role of R in influencing cardiovascular variability.

SIGNIFICANCE

Our results document the importance of employing a network perspective in the evaluation of the short-term complexity of cardiovascular and respiratory dynamics across different physiological states.

Recurrence Plots: a New Tool for Quantification of Cardiac Autonomic Nervous System Recovery after Transplant

Objective

To evaluate a possible evolutionary post-heart transplant return of autonomic function using quantitative and qualitative information from recurrence plots.

Methods

Using electrocardiography, 102 RR tachograms of 45 patients (64.4% male) who underwent heart transplantation and that were available in the database were analyzed at different follow-up periods. The RR tachograms were collected from patients in the supine position for about 20 minutes. A time series with 1000 RR intervals was analyzed, a recurrence plot was created, and the following quantitative variables were evaluated: percentage of determinism, percentage of recurrence, average diagonal length, Shannon entropy, and sample entropy, as well as the visual qualitative aspect.

Results

Quantitative and qualitative signs of heart rate variability recovery were observed after transplantation.

Conclusion

There is evidence that autonomic innervation of the heart begins to happen gradually after transplantation. Quantitative and qualitative analyses of recurrence can be useful tools for monitoring cardiac transplant patients and detecting the gradual return of heart rate variability.

Kölliker-Fuse nuclei regulate respiratory rhythm variability via a gain-control mechanism

Respiration varies from breath to breath. On the millisecond timescale of spiking, neuronal circuits exhibit variability due to the stochastic properties of ion channels and synapses. Does this fast, microscopic source of variability contribute to the slower, macroscopic variability of the respiratory period? To address this question, we modeled a stochastic oscillator with forcing; then, we tested its predictions experimentally for the respiratory rhythm generated by the in situ perfused preparation during vagal nerve stimulation (VNS). Our simulations identified a relationship among the gain of the input, entrainment strength, and rhythm variability. Specifically, at high gain, the periodic input entrained the oscillator and reduced variability, whereas at low gain, the noise interacted with the input, causing events known as "phase slips", which increased variability on a slow timescale. Experimentally, the in situ preparation behaved like the low-gain model: VNS entrained respiration but exhibited phase slips that increased rhythm variability. Next, we used bilateral muscimol microinjections in discrete respiratory compartments to identify areas involved in VNS gain control. Suppression of activity in the nucleus tractus solitarii occluded both entrainment and amplification of rhythm variability by VNS, confirming that these effects were due to the activation of the Hering-Breuer reflex. Suppressing activity of the Kölliker-Fuse nuclei (KFn) enhanced entrainment and reduced rhythm variability during VNS, consistent with the predictions of the high-gain model. Together, the model and experiments suggest that the KFn regulates respiratory rhythm variability via a gain control mechanism.

Ineffective efforts in ICU assisted ventilation: Exploring causalities via multiscale analysis

Intensive Care Unit (ICU) is a data intensive environment, requiring continuous monitoring of patient's physiology and response to treatment. In assisted ventilation, where patient effort that triggers the ventilator and there is need for patient-ventilator coupling, attention is required in cases where patient's effort that doesn't trigger the ventilator at all. When synchronization between the patient's attempt to breath and the assisted ventilation event is lost, an ineffective effort (IE) event takes place. A series of relevant bioparameters continuously monitored, are meant to guide the medical professionals in appropriately adapting the operation and treatment, in order to minimize IEs. The purpose of this work is to investigate the causal relations between physiological or ventilation parameters and IE events. A multiscale approach is proposed, based on wavelet similarity and localized phase relationship. The proposed method indicates the existence of distinct frequency zones correlated with the IE experienced by the patient.

Automated analysis of respiratory behavior in extremely preterm infants and extubation readiness

BACKGROUND

Rates of extubation failure of extremely preterm infants remain high. Analysis of breathing patterns variability during spontaneous breathing under endotracheal tube continuous positive airway pressure (ETT-CPAP) is a potential tool to predict extubation readiness.

OBJECTIVE

To investigate if automated analysis of respiratory signals would reveal differences in respiratory behavior between infants that were successfully extubated or not.

METHODS

Respiratory Inductive Plethysmography (RIP) signals were recorded during ETT-CPAP just prior to extubation. Signals were digitized, and analyzed using an Automated Unsupervised Respiratory Event Analysis (AUREA). Extubation failure was defined as reintubation within 72 hr. Statistical differences between infants who were successfully extubated or failed were calculated.

RESULTS

A total of 56 infants were enrolled and one was excluded due to instability during the ETT-CPAP; 11 out of 55 infants studied failed extubation (20%). No differences in demographics were observed between the success and failure groups. Significant differences on the variability of some respiratory parameters or 'metrics' estimated by AUREA were observed between the 2 groups. Indeed, a simple classification using the variability of two metrics of respiratory behavior predicted extubation failure with high accuracy.

CONCLUSION

Automated analysis of respiratory behavior during a short ETT-CPAP period may help in the prediction of extubation readiness in extremely preterm infants.

Comparison of heart and respiratory rate variability measures using an intermittent incremental submaximal exercise model

To better understand the alterations in cardiorespiratory variability during exercise, the present study characterized the patterns of change in heart rate variability (HRV), respiratory rate variability (RRV), and combined cardiorespiratory variability (HRV-RRV) during an intermittent incremental submaximal exercise model. Six males and six females completed a submaximal exercise protocol consisting of an initial baseline resting period followed by three 10-min bouts of exercise at 20%, 40%, and 60% of maximal aerobic capacity (V̇O2max). The R-R interval and interbreath interval variability were measured at baseline rest and throughout the submaximal exercise. A group of 93 HRV, 83 RRV, and 28 HRV-RRV measures of variability were tracked over time through a windowed analysis using a 5-min window size and 30-s window step. A total of 91 HRV measures were able to detect the presence of exercise, whereas only 46 RRV and 3 HRV-RRV measures were able to detect the same stimulus. Moreover, there was a loss of overall HRV and RRV, loss of complexity of HRV and RRV, and loss of parasympathetic modulation of HRV (up to 40% V̇O2max) with exercise. Conflicting changes in scale-invariant structure of HRV and RRV with increases in exercise intensity were also observed. In summary, in this simultaneous evaluation of HRV and RRV, we found more consistent changes across HRV metrics compared with RRV and HRV-RRV.

Fluctuation analysis of respiratory impedance waveform in asthmatic patients: effect of airway obstruction

Fluctuation analysis has great potential to contribute to pulmonary clinical science and practice. We evaluated the relationship between asthma and the respiratory impedance recurrence period density entropy (RPDEnZrs) and the variability (SDZrs). A non-invasive and simple protocol for assessing respiratory mechanics during spontaneous breathing was used in a group of 74 subjects with various levels of airway obstruction. Airway obstruction resulted in a reduction in the RPDEnZrs that was significantly correlated with both spirometric indices of airway obstruction (R = 0.48, p < 0.0001) and mean respiratory impedance (R = -0.83, p < 0.0001). These results suggest that the impedance pattern becomes less complex in asthmatic patients, which may explain the reduction in respiratory systems' adaptability to daily life activities. Preliminary evaluations indicate that RPDEnZrs may contribute to the asthma diagnosis, presenting accuracies of 82 and 87 % in patients with moderate and severe airway obstruction, respectively. On the other hand, SDZrs increased with obstruction (p < 0.0001) and was inversely correlated with spirometric indices of obstruction (R = -0.42, p = 0.0003) and directly associated with mean impedance (R = 0.88, p < 0.0001). This analysis contributes to elucidate previous studies and identified respiratory changes in patients with moderate and severe obstruction with an adequate accuracy (85 and 87 %, respectively).

Weaning infants from mechanical ventilation

Protracted mechanical ventilation is associated with increased morbidity and mortality in preterm infants and thus the earliest possible weaning from mechanical ventilation is desirable. Weaning protocols may be helpful in achieving more rapid reduction in support. There is no clear consensus regarding the level of support at which an infant is ready for extubation. An improved ability to predict when a preterm infant has a high likelihood of successful extubation is highly desirable. In this article, available evidence is reviewed and reasonable evidence-based recommendations for expeditious weaning and extubation are provided.

Weaning from mechanical ventilation

PURPOSE OF REVIEW

Liberation from mechanical ventilation is a defining moment for intubated patients, and thus a critical clinical decision. Extubating the patient too early exposes the patient to extubation failure and reintubation. Waiting too long increases the complications of prolonged intubation. Tools to help the physician with this critical decision and to test readiness have been available for decades, and are continuously being improved. New methods to improve extubation outcomes are also being developed. This review covers the latest studies in order to help physicians take advantage of the latest developments in a rapidly evolving field.

RECENT FINDINGS

This review highlights the recent advances in assessing and testing for readiness of weaning and liberation from mechanical ventilation, the cause of weaning failure, the value of weaning protocols, and the role of noninvasive positive pressure ventilation in liberating patients from invasive mechanical ventilation.

SUMMARY

Recent findings are shedding more light on this topic, and transforming 'the artistic' aspect of weaning and liberation from mechanical ventilation into a more 'scientific' approach that will expedite liberation from mechanical ventilation yet without encountering high failure rates, and without exposing patients to unnecessary risks.

Vagal-dependent nonlinear variability in the respiratory pattern of anesthetized, spontaneously breathing rats

Physiological rhythms, including respiration, exhibit endogenous variability associated with health, and deviations from this are associated with disease. Specific changes in the linear and nonlinear sources of breathing variability have not been investigated. In this study, we used information theory-based techniques, combined with surrogate data testing, to quantify and characterize the vagal-dependent nonlinear pattern variability in urethane-anesthetized, spontaneously breathing adult rats. Surrogate data sets preserved the amplitude distribution and linear correlations of the original data set, but nonlinear correlation structure in the data was removed. Differences in mutual information and sample entropy between original and surrogate data sets indicated the presence of deterministic nonlinear or stochastic non-Gaussian variability. With vagi intact (n = 11), the respiratory cycle exhibited significant nonlinear behavior in templates of points separated by time delays ranging from one sample to one cycle length. After vagotomy (n = 6), even though nonlinear variability was reduced significantly, nonlinear properties were still evident at various time delays. Nonlinear deterministic variability did not change further after subsequent bilateral microinjection of MK-801, an N-methyl-D-aspartate receptor antagonist, in the Kölliker-Fuse nuclei. Reversing the sequence (n = 5), blocking N-methyl-D-aspartate receptors bilaterally in the dorsolateral pons significantly decreased nonlinear variability in the respiratory pattern, even with the vagi intact, and subsequent vagotomy did not change nonlinear variability. Thus both vagal and dorsolateral pontine influences contribute to nonlinear respiratory pattern variability. Furthermore, breathing dynamics of the intact system are mutually dependent on vagal and pontine sources of nonlinear complexity. Understanding the structure and modulation of variability provides insight into disease effects on respiratory patterning.