Impact of ventilatory modes on the breathing variability in mechanically ventilated infants

Data-driven nonstationary signal decomposition approaches: a comparative analysis

Signal decomposition (SD) approaches aim to decompose non-stationary signals into their constituent amplitude- and frequency-modulated components. This represents an important preprocessing step in many practical signal processing pipelines, providing useful knowledge and insight into the data and relevant underlying system(s) while also facilitating tasks such as noise or artefact removal and feature extraction. The popular SD methods are mostly data-driven, striving to obtain inherent well-behaved signal components without making many prior assumptions on input data. Among those methods include empirical mode decomposition and variants, variational mode decomposition and variants, synchrosqueezed transform and variants and sliding singular spectrum analysis. With the increasing popularity and utility of these methods in wide-ranging applications, it is imperative to gain a better understanding and insight into the operation of these algorithms, evaluate their accuracy with and without noise in input data and gauge their sensitivity against algorithmic parameter changes. In this work, we achieve those tasks through extensive experiments involving carefully designed synthetic and real-life signals. Based on our experimental observations, we comment on the pros and cons of the considered SD algorithms as well as highlighting the best practices, in terms of parameter selection, for the their successful operation. The SD algorithms for both single- and multi-channel (multivariate) data fall within the scope of our work. For multivariate signals, we evaluate the performance of the popular algorithms in terms of fulfilling the mode-alignment property, especially in the presence of noise.

Neurally Adjusted Ventilatory Assist vs. Conventional Mechanical Ventilation in Adults and Children With Acute Respiratory Failure: A Systematic Review and Meta-Analysis

Background

Patient-ventilator asynchrony is a common problem in mechanical ventilation (MV), resulting in increased complications of MV. Despite there being some pieces of evidence for the efficacy of improving the synchronization of neurally adjusted ventilatory assist (NAVA), controversy over its physiological and clinical outcomes remain. Herein, we conducted a systematic review and meta-analysis to determine the relative impact of NAVA or conventional mechanical ventilation (CMV) modes on the important outcomes of adults and children with acute respiratory failure (ARF).

Methods

Qualified studies were searched in PubMed, EMBASE, Medline, Web of Science, Cochrane Library, and additional quality evaluations up to October 5, 2021. The primary outcome was asynchrony index (AI); secondary outcomes contained the duration of MV, intensive care unit (ICU) mortality, the incidence rate of ventilator-associated pneumonia, pH, and Partial Pressure of Carbon Dioxide in Arterial Blood (PaCO2). A statistical heterogeneity for the outcomes was assessed using the I ² test. A data analysis of outcomes using odds ratio (OR) for ICU mortality and ventilator-associated pneumonia incidence and mean difference (MD) for AI, duration of MV, pH, and PaCO2, with 95% confidence interval (CI), was expressed.

Results

Eighteen eligible studies (n = 926 patients) were eventually enrolled. For the primary outcome, NAVA may reduce the AI (MD = -18.31; 95% CI, -24.38 to -12.25; p < 0.001). For the secondary outcomes, the duration of MV in the NAVA mode was 2.64 days lower than other CMVs (MD = -2.64; 95% CI, -4.88 to -0.41; P = 0.02), and NAVA may decrease the ICU mortality (OR =0.60; 95% CI, 0.42 to 0.86; P = 0.006). There was no statistically significant difference in the incidence of ventilator-associated pneumonia, pH, and PaCO2 between NAVA and other MV modes.

Conclusions

Our study suggests that NAVA ameliorates the synchronization of patient-ventilator and improves the important clinical outcomes of patients with ARF compared with CMV modes.

Backup ventilation during neurally adjusted ventilatory assist in preterm infants

OBJECTIVE

To analyze the proportion of backup ventilation during neurally adjusted ventilatory assist (NAVA) in preterm infants at different postmenstrual ages (PMAs) and to analyze the trends in backup ventilation in relation to clinical deteriorations.

METHODS

A prospective observational study was conducted in 18 preterm infants born at a median (range) 27⁺⁴ (23⁺⁴ -34⁺⁴ ) weeks of gestation with a median (range) birth weight of 1,100 (460-2,820) g, who received respiratory support with either invasive or noninvasive NAVA. Data on ventilator settings and respiratory variables were collected daily; the mean values of each 24-h recording were computed for each respiratory variable. For clinical deterioration, ventilator data were reviewed at 6-h intervals for 30 h before the event.

RESULTS

A total of 354 patient days were included: 269 and 85 days during invasive and noninvasive NAVA, respectively. The time on backup ventilation (%/min) significantly decreased with increasing PMA during both invasive and noninvasive NAVA. The neural respiratory rate did not change over time. The median time on backup ventilation was less than 15%/min, and the median neural respiratory rate was more than 45 breaths/min for infants above 26⁺⁰ weeks PMA during invasive NAVA. The relative backup ventilation significantly increased before the episode of clinical deterioration.

CONCLUSION

The proportion of backup ventilation during NAVA showed how the control of breathing matured with increasing PMA. Even the most immature infants triggered most of their breaths by their own respiratory effort. An acute increase in the proportion of backup ventilation anticipated clinical deterioration.

Cardiorespiratory effects of NIV-NAVA, NIPPV, and NCPAP shortly after extubation in extremely preterm infants: A randomized crossover trial

OBJECTIVE

Investigate the cardiorespiratory effects of noninvasive neurally adjusted ventilatory assist (NIV-NAVA), nonsynchronized nasal intermittent positive pressure ventilation (NIPPV), and nasal continuous positive airway pressure (NCPAP) shortly after extubation.

HYPOTHESIS

Types of noninvasive pressure support and the presence of synchronization may affect cardiorespiratory parameters.

STUDY DESIGN

Randomized crossover trial.

PATIENT-SUBJECT SELECTION

Infants with birth weight (BW) 1250 g or under, undergoing their first planned extubation were randomly assigned to all three modes using a computer-generated sequence.

METHODOLOGY

Electrocardiogram and electrical activity of the diaphragm (Edi) were recorded for 30 min on each mode. Analysis of heart rate variability (HRV), diaphragmatic activity (Edi area, breath area, amplitude, inspiratory and expiratory times), and respiratory variability were compared between modes.

RESULTS

Twenty-three infants had full data recordings and analysis: Median (IQR) gestational age = 25.9 weeks (25.2-26.4), BW = 760 g (595-900), and postnatal age 7 (4-19) days. There were no differences in HRV between modes. A significantly reduced Edi area and breath amplitude, and increased coefficient of variation (CV) of breath amplitude were observed during NIV-NAVA and NIPPV compared to NCPAP. A higher proportion of assisted breaths (99% vs. 51%; p < .001) provided a higher mean airway pressure (MAP; 9.4 vs. 8.2 cmH₂ O; p = .002) with lower peak inflation pressures (PIPs; 14 vs. 16 cmH₂ O; p < .001) during NIV-NAVA compared to NIPPV.

CONCLUSIONS

NIV-NAVA and NIPPV applied shortly after extubation were associated with lower respiratory efforts and higher respiratory variability. These effects were more evident for NIV-NAVA where optimal patient-ventilator synchronization provided a higher MAP with lower PIPs.

Neurally Adjusted Ventilator Assist in Infants With Acute Respiratory Failure: A Literature Scoping Review

OBJECTIVES

To map the evidence for neurally adjusted ventilatory assist strategies, outcome measures, and sedation practices in infants less than 12 months with acute respiratory failure using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews guidance.

DATA SOURCES

CINAHL, MEDLINE, COCHRANE, JBI, EMBASE, PsycINFO, Google scholar, BNI, AMED. Trial registers included the following: ClinicalTrials.gov, European Union clinical trials register, International Standardized Randomized Controlled Trial Number register. Also included were Ethos, Grey literature, Google, dissertation abstracts, EMBASE conference proceedings.

STUDY SELECTION

Abstracts were screened followed by review of full text. Articles incorporating a heterogeneous population of both infants and older children were assessed, and where possible, data for infants were extracted. Fifteen articles were included. Ten articles were primary research: randomized controlled trial (n = 3), cohort studies (n = 4), retrospective data analysis (n = 2), case series (n = 1). Other articles are expert opinion (n = 2), neurally adjusted ventilatory assist updates (n = 1), and a literature review (n = 2). Three studies included exclusively infants. We also included 12 studies reporting jointly on infants and children.

DATA EXTRACTION

A standardized data extraction tool was used.

DATA SYNTHESIS

Key findings were that evidence related to neurally adjusted ventilatory assist ventilation strategies in infants and related to specific primary conditions is limited. The setting of neurally adjusted ventilatory assist level is not consistent, and how to optimize this mode of ventilation was not documented. Outcome measures varied considerably, most studies focused on improvements in respiratory and physiological variables. Sedation use is variable with regard to medication type and dose. There is an indication that less sedation is required in patients receiving neurally adjusted ventilatory assist, but no conclusive evidence to support this.

CONCLUSIONS

This review highlights a lack of standardized strategies for neurally adjusted ventilatory assist ventilation and sedation practices among infants with acute respiratory failure. Studies were limited by small sample sizes and a lack of focus on specific patient groups. Robust studies are needed to provide evidence-based clinical recommendations for the use of neurally adjusted ventilatory assist in infants with acute respiratory failure.

Diaphragmatic activity and neural breathing variability during a 5-min endotracheal continuous positive airway pressure trial in extremely preterm infants

BACKGROUND

Extremely preterm infants are often exposed to endotracheal tube continuous positive airway pressure (ETT-CPAP) trials to assess extubation readiness. The effects of ETT-CPAP trial on their diaphragmatic activity (Edi) and breathing variability is unknown.

METHODS

Prospective observational study enrolling infants with birth weight ≤1250 g undergoing their first extubation attempt. Diaphragmatic activity, expressed as the absolute minimum (Edi min) and maximum values (Edi max), area under the Edi signal, and breath-by-breath analyses for breath areas, amplitudes, widths, and neural inspiratory and expiratory times, were analyzed during mechanical ventilation (MV) and ETT-CPAP. Neural breathing variability of each of these parameters was also calculated and compared between MV and ETT-CPAP.

RESULTS

Thirteen infants with median (interquartile range) birth weight of 800 g [610-920] and gestational age of 25.4 weeks [24.4-26.3] were included. Diaphragmatic activity significantly increased during ETT-CPAP when compared to MV:Edi max (44.2 vs. 38.1 μV), breath area (449 vs. 312 μV·s), and amplitude (10.12 vs. 7.46 μV). Neural breathing variability during ETT-CPAP was characterized by increased variability for amplitude and area under the breath, and decreased for breath time and width.

CONCLUSIONS

A 5-min ETT-CPAP in extremely preterm infants undergoing extubation imposed significant respiratory load with changes in respiratory variability.

IMPACT

ETT-CPAP trials are often used to assess extubation readiness in extremely preterm infants, but its effects upon their respiratory system are not well known. Diaphragmatic activity analysis demonstrated that these infants are able to mount an important response to a short trial. A 5-min trial imposed a significant respiratory load evidenced by increased diaphragmatic activity and changes in breathing variability. Differences in breathing variability were observed between successful and failed extubations, which should be explored further in extubation readiness investigations. This type of trial cannot be recommended for preterm infants in clinical practice until clear standards and accuracy are established.

Evaluating peak inspiratory pressures and tidal volume in premature neonates on NAVA ventilation

Neurally adjusted ventilatory assist (NAVA) ventilation allows patients to determine their peak inspiratory pressure and tidal volume on a breath-by-breath basis. Apprehension exists about premature neonates' ability to self-regulate breath size. This study describes peak pressure and tidal volume distribution of neonates on NAVA and non-invasive NAVA. This is a retrospective study of stored ventilator data with exploratory analysis. Summary statistics were calculated. Distributional assessment of peak pressure and tidal volume were evaluated, overall and per NAVA level. Over 1 million breaths were evaluated from 56 subjects. Mean peak pressure was 16.4 ± 6.4 in the NAVA group, and 15.8 ± 6.4 in the NIV-NAVA group (t test, p < 0.001). Mean tidal volume was 3.5 ± 2.7 ml/kg.Conclusion:In neonates on NAVA, most pressures and volumes were within or lower than recommended ranges with pressure-limited or volume-guarantee ventilation. What is known: • Limiting peak inspiratory pressures or tidal volumes are the main strategies to minimize ventilator-induced lung injury in neonates. Neurally adjusted ventilatory assist allows neonates to regulate their own peak inspiratory pressures and tidal volumes on a breath-to-breath basis using neural feedback. What is new: • When neonates chose the size of their breaths based on neural feedback, the majority of peak inspiratory pressures and tidal volumes were within or lower than the recommended peak inspiratory pressure or tidal volume ranges with pressure-limited or volume guarantee ventilation.

Monitoring of Respiratory Muscle Function in Critically Ill Children

OBJECTIVES

This review discusses the different techniques used at the bedside to assess respiratory muscle function in critically ill children and their clinical applications.

DATA SOURCES

A scoping review of the medical literature on respiratory muscle function assessment in critically ill children was conducted using the PubMed search engine.

STUDY SELECTION

We included all scientific, peer-reviewed studies about respiratory muscle function assessment in critically ill children, as well as some key adult studies.

DATA EXTRACTION

Data extracted included findings or comments about techniques used to assess respiratory muscle function.

DATA SYNTHESIS

Various promising physiologic techniques are available to assess respiratory muscle function at the bedside of critically ill children throughout the disease process. During the acute phase, this assessment allows a better understanding of the pathophysiological mechanisms of the disease and an optimization of the ventilatory support to increase its effectiveness and limit its potential complications. During the weaning process, these physiologic techniques may help predict extubation success and therefore optimize ventilator weaning.

CONCLUSIONS

Physiologic techniques are useful to precisely assess respiratory muscle function and to individualize and optimize the management of mechanical ventilation in children. Among all the available techniques, the measurements of esophageal pressure and electrical activity of the diaphragm appear particularly helpful in the era of individualized ventilatory management.

Neurally adjusted ventilatory assist versus conventional ventilation in the pediatric population: Are there benefits?

INTRODUCTION

Neurally-adjusted ventilator assist (NAVA) is a relatively new form of ventilation in which the electrical activity of the diaphragm is sensed by a catheter. The amplitude of this electrical signal is then used to deliver an appropriately proportioned pressure supported breath to the patient. Due to the synchronous nature of the breaths and the patient-adjusted nature of the support, NAVA has been shown to have benefits over conventional ventilation. Meta-analyses were conducted of published pediatric studies to compare ventilatory endpoints between NAVA and conventional ventilation.

METHODS

Studies comparing ventilatory parameters between NAVA and conventional ventilation in pediatric patients were identified. These studies were reviewed for appropriateness for inclusion and studies of only pediatric patients with data for similar endpoints between both arms were then pooled.

RESULTS

Statistically significant differences were noted in asynchrony, peak inspiratory pressure (PIP), and oxygen saturation by pulse oximetry. Asynchrony was 17% lower with NAVA, PIP was 1.74 cmH₂ 0 lower with NAVA, and oxygen saturation was 1.1% greater with NAVA. There was no statistically significant difference in peak expiratory pressure, mean airway pressure, electrical diaphragmatic activity, respiratory rate, hydrogen ion concentration, partial pressure of oxygen, or partial pressure of carbon dioxide.

CONCLUSION

Statistically significant differences were noted in percent asynchrony, PIP, and oxygen saturation when comparing NAVA to conventional ventilation. These all tended to favor NAVA. Other than percent asynchrony, however, the other statistically significant findings were not clinically significant.

Modeling the Pulse Signal by Wave-Shape Function and Analyzing by Synchrosqueezing Transform

We apply the recently developed adaptive non-harmonic model based on the wave-shape function, as well as the time-frequency analysis tool called synchrosqueezing transform (SST) to model and analyze oscillatory physiological signals. To demonstrate how the model and algorithm work, we apply them to study the pulse wave signal. By extracting features called the spectral pulse signature, and based on functional regression, we characterize the hemodynamics from the radial pulse wave signals recorded by the sphygmomanometer. Analysis results suggest the potential of the proposed signal processing approach to extract health-related hemodynamics features.

ConceFT: concentration of frequency and time via a multitapered synchrosqueezed transform

A new method is proposed to determine the time-frequency content of time-dependent signals consisting of multiple oscillatory components, with time-varying amplitudes and instantaneous frequencies. Numerical experiments as well as a theoretical analysis are presented to assess its effectiveness.

When Interpolation-Induced Reflection Artifact Meets Time-Frequency Analysis

OBJECTIVE

While extracting the temporal dynamical features based on the time-frequency analyses, like the reassignment and synchrosqueezing transform, attracts more and more interest in biomedical data analysis, we should be careful about artifacts generated by interpolation schemes, in particular when the sampling rate is not significantly higher than the frequency of the oscillatory component we are interested in.

METHODS

We formulate the problem called the reflection effect and provide a theoretical justification of the statement. We also show examples in the anesthetic depth analysis with clear but undesirable artifacts.

RESULTS

The artifact associated with the reflection effect exists not only theoretically but practically as well. Its influence is pronounced when we apply the time-frequency analyses to extract the time-varying dynamics hidden inside the signal.

CONCLUSION

We have to carefully deal with the artifact associated with the reflection effect by choosing a proper interpolation scheme.