Effect of Neurally Adjusted Ventilatory Assist on Patient-Ventilator Interaction in Mechanically Ventilated Adults: A Systematic Review and Meta-Analysis

Convolutional long short-term memory neural network integrated with classifier in classifying type of asynchrony breathing in mechanically ventilated patients

BACKGROUND AND OBJECTIVE

Asynchronous breathing (AB) occurs when a mechanically ventilated patient's breathing does not align with the mechanical ventilator (MV). Asynchrony can negatively impact recovery and outcome, and/or hinder MV management. A model-based method to accurately classify different AB types could automate detection and have a measurable clinical impact.

METHODS

This study presents an approach using a 1-dimensional (1D) of airway pressure data as an input to the convolutional long short-term memory neural network (CNN-LSTM) with a classifier method to classify AB types into three categories: 1) reverse Triggering (RT); 2) premature cycling (PC); and 3) normal breathing (NB), which cover normal breathing and 2 primary forms of AB. Three types of classifier are integrated with the CNN-LSTM model which are random forest (RF), support vector machine (SVM) and logistic regression (LR). Clinical data inputs include measured airway pressure from 7 MV patients in IIUM Hospital ICU under informed consent with a total of 4500 breaths. Model performance is first assessed in a k-fold cross-validation assessing accuracy in comparison to the proposed CNN-LSTM integrated with each type of classifier. Then, confusion matrices are used to summarize classification performance for the CNN without classifier, CNN-LSTM without classifier, and CNN-LSTM with each of the 3 classifiers (RF, SVM, LR).

RESULTS AND DISCUSSION

The 1D CNN-LSTM with classifier method achieves 100 % accuracy using 5-fold cross validation. The confusion matrix results showed that the combined CNN-LSTM model with classifier performed better, demostrating higher accuracy, sensitivity, specificity, and F1 score, all exceeding 83.5 % across all three breathing categories. The CNN model without classifier and CNN-LSTM model without classifier displayed comparatively lower performance, with average values of F1 score below 71.8 % for all three breathing categories.

CONCLUSION

The results validate the effectiveness of the CNN-LSTM neural network model with classifier in accurately detecting and classifying the different categories of AB and NB. Overall, this model-based approach has the potential to precisely classify the type of AB and differentiate normal breathing. With this developed model, a better MV management can be provided at the bedside, and these results justify prospective clinical testing.

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.

Neurally Adjusted Ventilatory Assist in Newborns

Patient-ventilator asynchrony is very common in newborns. Achieving synchrony is quite challenging because of small tidal volumes, high respiratory rates, and the presence of leaks. Leaks also cause unreliable monitoring of respiratory metrics. In addition, ventilator adjustment must take into account that infants have strong vagal reflexes and demonstrate central apnea and periodic breathing, with a high variability in breathing pattern. Neurally adjusted ventilatory assist (NAVA) is a mode of ventilation whereby the timing and amount of ventilatory assist is controlled by the patient's own neural respiratory drive. As NAVA uses the diaphragm electrical activity (Edi) as the controller signal, it is possible to deliver synchronized assist, both invasively and noninvasively (NIV-NAVA), to follow the variability in breathing pattern, and to monitor patient respiratory drive, independent of leaks. This article provides an updated review of the physiology and the scientific literature pertaining to the use of NAVA in children (neonatal and pediatric age groups). Both the invasive NAVA and NIV-NAVA publications since 2016 are summarized, as well as the use of Edi monitoring. Overall, the use of NAVA and Edi monitoring is feasible and safe. Compared with conventional ventilation, NAVA improves patient-ventilator interaction, provides lower peak inspiratory pressure, and lowers oxygen requirements. Evidence from several studies suggests improved comfort, less sedation requirements, less apnea, and some trends toward reduced length of stay and more successful extubation.

Comparison of advanced closed-loop ventilation modes with pressure support ventilation for weaning from mechanical ventilation in adults: A systematic review and meta-analysis

PURPOSE

To compare neurally adjusted ventilatory assist (NAVA), proportional assist ventilation (PAV), adaptive support ventilation (ASV) and Smartcare pressure support (Smartcare/PS) with standard pressure support ventilation (PSV) regarding their effectiveness for weaning critically ill adults from invasive mechanical ventilation (IMV).

METHODS

Electronic databases were searched to identify parallel-group randomized controlled trials (RCTs) comparing NAVA, PAV, ASV, or Smartcare/PS with PSV, in adult patients under IMV through July 28, 2021. Primary outcome was weaning success. Secondary outcomes included weaning time, total MV duration, reintubation or use of non-invasive MV (NIMV) within 48 h after extubation, in-hospital and intensive care unit (ICU) mortality, in-hospital and ICU length of stay (LOS) (PROSPERO registration No:CRD42021270299).

RESULTS

Twenty RCTs were finally included. Compared to PSV, NAVA was associated with significantly lower risk for in-hospital and ICU death and lower requirements for post-extubation NIMV. Moreover, PAV showed significant advantage over PSV in terms of weaning rates, MV duration and ICU LOS. No significant differences were found between ASV or Smart care/PS and PSV.

CONCLUSIONS

Moderate certainty evidence suggest that PAV increases weaning success rates, shortens MV duration and ICU LOS compared to PSV. It is also noteworthy that NAVA seems to improve in-hospital and ICU survival.

Patient-ventilator asynchrony, impact on clinical outcomes and effectiveness of interventions: a systematic review and meta-analysis

Background

Patient–ventilator asynchrony (PVA) is a common problem in patients undergoing invasive mechanical ventilation (MV) in the intensive care unit (ICU), and may accelerate lung injury and diaphragm mis-contraction. The impact of PVA on clinical outcomes has not been systematically evaluated. Effective interventions (except for closed-loop ventilation) for reducing PVA are not well established.

Methods

We performed a systematic review and meta-analysis to investigate the impact of PVA on clinical outcomes in patients undergoing MV (Part A) and the effectiveness of interventions for patients undergoing MV except for closed-loop ventilation (Part B). We searched the Cochrane Central Register of Controlled Trials, MEDLINE, EMBASE, ClinicalTrials.gov, and WHO-ICTRP until August 2020. In Part A, we defined asynchrony index (AI) ≥ 10 or ineffective triggering index (ITI) ≥ 10 as high PVA. We compared patients having high PVA with those having low PVA.

Results

Eight studies in Part A and eight trials in Part B fulfilled the eligibility criteria. In Part A, five studies were related to the AI and three studies were related to the ITI. High PVA may be associated with longer duration of mechanical ventilation (mean difference, 5.16 days; 95% confidence interval [CI], 2.38 to 7.94; n = 8; certainty of evidence [CoE], low), higher ICU mortality (odds ratio [OR], 2.73; 95% CI 1.76 to 4.24; n = 6; CoE, low), and higher hospital mortality (OR, 1.94; 95% CI 1.14 to 3.30; n = 5; CoE, low). In Part B, interventions involving MV mode, tidal volume, and pressure-support level were associated with reduced PVA. Sedation protocol, sedation depth, and sedation with dexmedetomidine rather than propofol were also associated with reduced PVA.

Conclusions

PVA may be associated with longer MV duration, higher ICU mortality, and higher hospital mortality. Physicians may consider monitoring PVA and adjusting ventilator settings and sedatives to reduce PVA. Further studies with adjustment for confounding factors are warranted to determine the impact of PVA on clinical outcomes.

Trial registration protocols.io (URL: https://www.protocols.io/view/the-impact-of-patient-ventilator-asynchrony-in-adu-bsqtndwn, 08/27/2020).

Supplementary Information

The online version contains supplementary material available at 10.1186/s40560-021-00565-5.

Multicenter Experience with Neurally Adjusted Ventilatory Assist in Infants with Severe Bronchopulmonary Dysplasia

OBJECTIVE

The aim of this study is to determine patterns of neurally adjusted ventilatory assist (NAVA) use in ventilator-dependent preterm infants with evolving or established severe bronchopulmonary dysplasia (sBPD) among centers of the BPD Collaborative, including indications for its initiation, discontinuation, and outcomes.

STUDY DESIGN

Retrospective review of infants with developing or established sBPD who were placed on NAVA after ≥4 weeks of mechanical ventilation and were ≥ 30 weeks of postmenstrual age (PMA).

RESULTS

Among the 13 sites of the BPD collaborative, only four centers (31%) used NAVA in the management of infants with evolving or established BPD. A total of 112 patients met inclusion criteria from these four centers. PMA, weight at the start of NAVA and median number of days on NAVA, were different among the four centers. The impact of NAVA therapy was assessed as being successful in 67% of infants, as defined by the ability to achieve respiratory stability at a lower level of ventilator support, including extubation to noninvasive positive pressure ventilation or support with a home ventilator. In total 87% (range: 78-100%) of patients survived until discharge.

CONCLUSION

We conclude that NAVA can be used safely and effectively in selective infants with sBPD. Indications and current strategies for the application of NAVA in infants with evolving or established BPD, however, are highly variable between centers. Although this pilot study suggests that NAVA may be successfully used for the management of infants with BPD, sufficient experience and well-designed clinical studies are needed to establish standards of care for defining the role of NAVA in the care of infants with sBPD.

Neurally adjusted ventilatory assist as a weaning mode for adults with invasive mechanical ventilation: a systematic review and meta-analysis

Background

Prolonged ventilatory support is associated with poor clinical outcomes. Partial support modes, especially pressure support ventilation, are frequently used in clinical practice but are associated with patient–ventilation asynchrony and deliver fixed levels of assist. Neurally adjusted ventilatory assist (NAVA), a mode of partial ventilatory assist that reduces patient–ventilator asynchrony, may be an alternative for weaning. However, the effects of NAVA on weaning outcomes in clinical practice are unclear.

Methods

We searched PubMed, Embase, Medline, and Cochrane Library from 2007 to December 2020. Randomized controlled trials and crossover trials that compared NAVA and other modes were identified in this study. The primary outcome was weaning success which was defined as the absence of ventilatory support for more than 48 h. Summary estimates of effect using odds ratio (OR) for dichotomous outcomes and mean difference (MD) for continuous outcomes with accompanying 95% confidence interval (CI) were expressed.

Results

Seven studies (n = 693 patients) were included. Regarding the primary outcome, patients weaned with NAVA had a higher success rate compared with other partial support modes (OR = 1.93; 95% CI 1.12 to 3.32; P = 0.02). For the secondary outcomes, NAVA may reduce duration of mechanical ventilation (MD = − 2.63; 95% CI − 4.22 to − 1.03; P = 0.001) and hospital mortality (OR = 0.58; 95% CI 0.40 to 0.84; P = 0.004) and prolongs ventilator-free days (MD = 3.48; 95% CI 0.97 to 6.00; P = 0.007) when compared with other modes.

Conclusions

Our study suggests that the NAVA mode may improve the rate of weaning success compared with other partial support modes for difficult to wean patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13054-021-03644-z.

Neurally adjusted ventilatory assist versus pressure support ventilation in patient-ventilator interaction and clinical outcomes: a meta-analysis of clinical trials

Background

The objective of this study was to conduct a meta-analysis comparing neurally adjusted ventilatory assist (NAVA) with pressure support ventilation (PSV) in adult ventilated patients with patient-ventilator interaction and clinical outcomes.

Methods

The PubMed, the Web of Science, Scopus, and Medline were searched for appropriate clinical trials (CTs) comparing NAVA with PSV for the adult ventilated patients. RevMan 5.3 was performed for comparing NAVA with PSV in asynchrony index (AI), ineffective efforts, auto-triggering, double asynchrony, premature asynchrony, breathing pattern (Peak airway pressure (Paw_peek), mean airway pressure (Paw_mean), tidal volume (V_T, mL/kg), minute volume (MV), respiratory muscle unloading (peak electricity of diaphragm (EAdi_peak), P 0.1, V_T/EAdi), clinical outcomes (ICU mortality, duration of ventilation days, ICU stay time, hospital stay time).

Results

Our meta-analysis included 12 studies involving a total of 331 adult ventilated patients, AI was significantly lower in NAVA group [mean difference (MD) -12.82, 95% confidence interval (CI): -21.20 to -4.44, I²=88%], and using subgroup analysis, grouped by mechanical ventilation, the results showed that NAVA also had lower AI than PSV (Mechanical ventilation, MD -9.52, 95% CI: -17.85 to -1.20, I²=87%), (Non-invasive ventilation (NIV), MD -24.55, 95% CI: -35.40 to -13.70, I²=0%). NAVA was significantly lower than the PSV in auto-triggering (MD -0.28, 95% CI: -0.51 to -0.05, I²=10%), and premature triggering (MD -2.49, 95% CI: -3.77 to -1.21, I²=29%). There were no significant differences in double triggering, ineffective efforts, breathing pattern (Paw_mean, Paw_peak, V_T, MV), and respiratory muscle unloading (EAdi_peak, P 0.1, V_T/EAdi). For clinical outcomes, NAVA was significantly lower than the PSV (MD -2.82, 95% CI: -5.55 to -0.08, I²=0%) in the duration of ventilation, but two groups did not show significant differences in ICU mortality, ICU stay time, and hospital stay time.

Conclusions

NAVA is more beneficial in patient-ventilator interaction than PSV, and could decrease the duration of ventilation.