Efficacy of ventilator waveform observation for detection of patient-ventilator asynchrony during NIV: a multicentre study

An overview of patient-ventilator asynchrony in children

INTRODUCTION

Mechanically ventilated children often have patient-ventilator asynchrony (PVA). When a ventilated patient has spontaneous effort, the ventilator attempts to synchronize with the patient, but PVA represents a mismatch between patient respiratory effort and ventilator delivered breaths.

AREAS COVERED

This review will focus on subtypes of patient ventilator asynchrony, methods to detect or measure PVA, risk factors for and characteristics of patients with PVA subtypes, potential clinical implications, treatment or prevention strategies, and future areas for research. Throughout this review, we will provide pediatric specific considerations.

EXPERT OPINION

PVA in pediatric patients supported by mechanical ventilation occurs frequently and is understudied. Pediatric patients have unique physiologic and pathophysiologic characteristics which affect PVA. While recognition of PVA and its subtypes is important for bedside clinicians, the clinical implications and risks versus benefits of treatment targeted at reducing PVA remain unknown. Future research should focus on harmonizing PVA terminology, refinement of automated detection technologies, determining which forms of PVA are harmful, and development of PVA-specific ventilator interventions.

Comparison of Web-Based and On-Site Lung Simulators for Education in Mechanical Ventilation

BACKGROUND

Training in mechanical ventilation is a key goal in critical care fellowship education. Web-based simulators offer a cost-effective and readily available alternative to traditional on-site simulators. However, it is unclear how effective they are as teaching tools. In this study, we evaluated the test scores of fellows who underwent mechanical ventilation training by using a web-based simulator compared with fellows who used an on-site simulator during a mechanical ventilation course.

METHODS

This was a nonrandomized controlled trial conducted as part of a mechanical ventilation course that involved 70 first-year critical care fellows. The course was identical except for the simulation technology used. One group of instructors used a traditional on-site simulator, the ASL 5000 Lung Solution (n = 39). The second group was instructed in using a web-based simulator, VentSim (n = 31). Each fellow completed a pre-course test and a post-course test by using a validated, case-based ventilator waveform examination that consisted of 5 questions with a total possible score of 100. The primary outcome was a comparison of the mean scores on the posttest between the 2 groups. The study was designed as a non-inferiority trial with a predetermined margin of 10 points.

RESULTS

There was no significant difference in the mean ± SD pretest scores between the web-based and the on-site groups (21.1 ± 12.6 and 26.9 ± 13.6 respectively; P = .11). The mean ± SD posttest scores were 45.6 ± 25.0 for the web-based simulator and 43.4 ± 16.5 for on-site simulator (mean difference 2.2; one-sided 95% CI -7.0 to ∞; P non-inferiority = .02 [non-inferiority confirmed]). Changes in mean ± SD scores (posttest - pretest) were 25.9 ± 20.9 for the web-based simulator and 16.5 ± 15.9 for the on-site simulator (mean difference 9.4, one-sided 95% CI 0.9 to ∞; P non-inferiority < .001 [non-inferiority confirmed]).

CONCLUSIONS

In the education of first-year critical care fellows on mechanical ventilation waveform analysis, a web-based mechanical ventilation simulator was non-inferior to a traditional on-site mechanical ventilation simulator.

Patient-ventilator asynchrony classification in mechanically ventilated patients: Model-based or machine learning method?

BACKGROUND AND OBJECTIVE

Patient-ventilator asynchrony (PVA) is associated with poor clinical outcomes and remains under-monitored. Automated PVA detection would enable complete monitoring standard observational methods do not allow. While model-based and machine learning PVA approaches exist, they have variable performance and can miss specific PVA events. This study compares a model and rule-based algorithm with a machine learning PVA method by retrospectively validating both methods using an independent patient cohort.

METHODS

Hysteresis loop analysis (HLA) which is a rule-based method (RBM) and a tri-input convolutional neural network (TCNN) machine learning model are used to classify 7 different types of PVA, including: 1) flow asynchrony; 2) reverse triggering; 3) premature cycling; 4) double triggering; 5) delayed cycling; 6) ineffective efforts; and 7) auto triggering. Class activation mapping (CAM) heatmaps visualise sections of respiratory waveforms the TCNN model uses for decision making, improving result interpretability. Both PVA classification methods were used to classify incidence in an independent retrospective clinical cohort of 11 mechanically ventilated patients for validation and performance comparison.

RESULTS

Self-validation with the training dataset shows overall better HLA performance (accuracy, sensitivity, specificity: 97.5 %, 96.6 %, 98.1 %) compared to the TCNN model (accuracy, sensitivity, specificity: 89.5 %, 98.3 %, 83.9 %). In this study, the TCNN model demonstrates higher sensitivity in detecting PVA, but HLA was better at identifying non-PVA breathing cycles due to its rule-based nature. While the overall AI identified by both classification methods are very similar, the intra-patient distribution of each PVA type varies between HLA and TCNN.

CONCLUSION

The collective findings underscore the efficacy of both HLA and TCNN in PVA detection, indicating the potential for real-time continuous monitoring of PVA. While ML methods such as TCNN demonstrate good PVA identification performance, it is essential to ensure optimal model architecture and diversity in training data before widespread uptake as standard care. Moving forward, further validation and adoption of RBM methods, such as HLA, offers an effective approach to PVA detection while providing clear distinction into the underlying patterns of PVA, better aligning with clinical needs for transparency, explicability, adaptability and reliability of these emerging tools for clinical care.

[High-flow nasal oxygen therapy and hypercapnic acute respiratory failure]

Humidified high-flow nasal oxygen therapy (HFNO) has, in recent years, come to assume a key role in the management of hypoxemic acute respiratory failure (ARF). While non-invasive ventilation (NIV) currently represents the first-line ventilatory strategy in patients exhibiting hypercapnic ARF, the operating principles and physiological effects of HFNO could be interesting and useful in the initial management of hypercapnic ARF and/or after extubation, particularly in acute exacerbations of chronic obstructive pulmonary disease. Under these conditions, HFNO could be used either alone continuously or in combination with NIV during breaks in spontaneous breathing, depending on the severity and etiology of the underlying hypercapnic ARF.

[Non-invasive Mechanical Ventilation in Acute Respiratory Failure. Clinical Practice Guidelines - on behalf of the German Society of Pneumology and Ventilatory Medicine]

The guideline update outlines the advantages as well as the limitations of NIV in the treatment of acute respiratory failure in daily clinical practice and in different indications.Non-invasive ventilation (NIV) has a high value in therapy of hypercapnic acute respiratory failure, as it significantly reduces the length of ICU stay and hospitalization as well as mortality.Patients with cardiopulmonary edema and acute respiratory failure should be treated with continuous positive airway pressure (CPAP) and oxygen in addition to necessary cardiological interventions. This should be done already prehospital and in the emergency department.In case of other forms of acute hypoxaemic respiratory failure with only mild or moderately disturbed gas exchange (PaO2/FiO2 > 150 mmHg) there is no significant advantage or disadvantage compared to high flow nasal oxygen (HFNO). In severe forms of ARDS NIV is associated with high rates of treatment failure and mortality, especially in cases with NIV-failure and delayed intubation.NIV should be used for preoxygenation before intubation. In patients at risk, NIV is recommended to reduce extubation failure. In the weaning process from invasive ventilation NIV essentially reduces the risk of reintubation in hypercapnic patients. NIV is regarded useful within palliative care for reduction of dyspnea and improving quality of life, but here in concurrence to HFNO, which is regarded as more comfortable. Meanwhile NIV is also recommended in prehospital setting, especially in hypercapnic respiratory failure and pulmonary edema.With appropriate monitoring in an intensive care unit NIV can also be successfully applied in pediatric patients with acute respiratory insufficiency.

Knowledge and associated factors of healthcare professionals in detecting patient-ventilator asynchrony using waveform analysis at intensive care units of the federal public hospitals in Addis Ababa, Ethiopia, 2023

BACKGROUND

The interaction between the patient and the ventilator is often disturbed, resulting in patient-ventilator asynchrony (PVA). Asynchrony can lead to respiratory failure, increased artificial ventilation time, prolonged hospitalization, and escalated healthcare costs. Professionals' knowledge regarding waveform analysis has significant implications for improving patient outcomes and minimizing ventilation-related adverse events. Studies investigating the knowledge of healthcare professionals on patient-ventilator asynchrony and its associated factors in the Ethiopian context are limited. Therefore, this study aimed to assess the knowledge of healthcare professionals about using waveform analysis to detect asynchrony.

METHODS

A multicenter cross-sectional study was conducted on 237 healthcare professionals (HCPs) working in the intensive care units (ICUs) of federal public hospitals in Addis Ababa, Ethiopia, from December 2022 to May 2023. The data were collected using a structured and pretested interviewer-administered questionnaire. Then, the collected data were cleaned, coded, and entered into Epi data V-4.2.2 and exported to SPSS V-27 for analysis. After description, associations were analyzed using binary logistic regression. Variables with a P-value of < 0.25 in the bivariable analysis were transferred to the multivariable analysis. Statistical significance was declared using 95% confidence intervals, and the strengths of associations were reported using adjusted odds ratios (AORs).

RESULTS

A total of 237 HCPs participated in the study with a response rate of 100%. Half (49.8%) of the participants were females. The mean age of the participants was 29 years (SD = 3.57). Overall, 10.5% (95% CI: 6.9-15.2) of the participants had good knowledge of detecting PVA using waveform analysis. In the logistic regression, the number of MV-specific trainings and the training site had a statistically significant association with knowledge of HCPs. HCPs who attended more frequent MV training were more likely to have good knowledge than their counterparts [AOR = 6.88 (95% CI: 2.61-15.45)]. Additionally, the odds of good knowledge among professionals who attended offsite training were 2.6 times higher than those among professionals trained onsite [AOR = 2.63 (95% CI: 1.36-7.98)].

CONCLUSION

The knowledge of ICU healthcare professionals about the identification of PVA using waveform analysis is low. In addition, the study also showed that attending offsite MV training and repeated MV training sessions were independently associated with good knowledge. Consequently, the study findings magnify the relevance of providing frequent and specific training sessions focused on waveform analysis to boost the knowledge of HCPs.

Applying Noninvasive Ventilation in Treatment of Acute Exacerbation of COPD Using Evidence-Based Interprofessional Clinical Practice

When administered as first-line intervention to patients admitted with acute hypercapnic respiratory failure secondary to COPD exacerbation in conjunction with guideline-recommended therapies, noninvasive ventilation (NIV) has been shown to reduce mortality and endotracheal intubation. Opportunities to increase uptake of NIV continue to exist despite inclusion of this therapy in clinical guidelines. Identifying patients appropriate for NIV, and subsequently providing close monitoring to determine an improvement in clinical condition involves a team consisting of physician, nurse, and respiratory therapist in institutions that successfully implement NIV. We describe to our knowledge the first known evidence-based algorithm speaking to initiation, titration, monitoring, and weaning of NIV in treatment of acute exacerbation of COPD that incorporates the necessary interprofessional collaboration among physicians, nurses, and respiratory therapists caring for these patients.

Comparison of the effectiveness of the helmet interface using flow meters versus the mechanical ventilator for non-invasive ventilation in patients with coronavirus disease 2019. Controlled and randomized clinical trial

Introduction

This study aimed to compare the effectiveness of two methods for non-invasive mechanical ventilation in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) - using a helmet interface with a flow meter and positive end-expiratory pressure valve versus a traditional mechanical ventilator.

Material and methods

We conducted a single-center randomized clinical trial involving 100 adult SARS-CoV-2 patients in a specialized private hospital. Participants were randomly assigned to two groups: one using the helmet interface with a flow meter and positive end-expiratory pressure valve and the other employing conventional mechanical ventilation. Our study included participant selection, blood gas analysis, assessment of respiratory rate, peripheral oxygen saturation, modified Borg scale scores, and a visual analog scale.

Results

The study showed no significant difference in intubation rates between the mechanical ventilation (54.3%) and helmet interface with flow meter and positive end-expiratory pressure valve (46.8%) groups (p = 0.37). Additionally, the helmet group had a shorter average duration of use (3.4 ±1.6 days) compared to the mechanical ventilation group (4.0 ±1.9 days). The helmet group also had a shorter average hospitalization duration (15.9 ±7.9 days) compared to the mechanical ventilation group (17.1 ±9.5 days).

Conclusions

This single-center randomized clinical trial found no statistically significant differences between the two methods of non-invasive ventilation. Implications for clinical practice: using the helmet interface with the flow meter and positive end-expiratory pressure valve can simplify device installation, potentially reducing the need for intubation, making it a valuable tool for nurses and physiotherapists in daily clinical practice.

The Ability of Critical Care Physicians to Identify Patient-Ventilator Asynchrony Using Waveform Analysis: A National Survey

BACKGROUND

Improved patient-ventilator asynchrony (PVA) identification using waveform analysis by critical care physicians (CCPs) may improve patient outcomes. This study aimed to assess the ability of CCPs to identify different types of PVAs using waveform analysis as well as factors related to this ability.

METHODS

We surveyed 12 university-affiliated medical ICUs (MICUs) in Tunisia. CCPs practicing in these MICUs were asked to visually identify 4 clinical cases, each corresponding to a different PVA. We collected the following characteristics regarding CCPs: scientific grade, years of experience, prior training in mechanical ventilation, prior exposure to waveform analysis, and the characteristics of the MICUs in which they practice. Respondents were categorized into 2 groups based on their ability to correctly identify PVAs (defined as the correct identification of at least 3 of the 4 PVA cases). Univariate analysis was performed to identify factors related to the correct identification of PVA.

RESULTS

Among 136 included CCPs, 72 (52.9%) responded to the present survey. The respondents comprised 59 (81.9%) residents, and 13 (18.1%) senior physicians. Further, 50 (69.4%) respondents had attended prior training in mechanical ventilation. Moreover, 21 (29.2%) of the respondents could correctly identify PVAs. Double-triggering was the most frequently identified PVA type, 43 (59.7%), followed by auto-triggering, 36 (50%); premature cycling, 28 (38.9%); and ineffective efforts, 25 (34.7%). Univariate analysis indicated that senior physicians had a better ability to correctly identify PVAs than residents (7 [53.8%] vs 14 [23.7%], P = .044).

CONCLUSIONS

The present study revealed a significant deficiency in the accurate visual identification of PVAs among CCPs in the MICUs. When compared to residents, senior physicians exhibited a notably superior aptitude for correctly recognizing PVAs.

Specific Training Improves the Detection and Management of Patient-Ventilator Asynchrony

BACKGROUND

Patient-ventilator asynchrony is common in patients undergoing mechanical ventilation. The proportion of health-care professionals capable of identifying and effectively managing different types of patient-ventilator asynchronies is limited. A few studies have developed specific training programs, but they mainly focused on improving patient-ventilator asynchrony detection without assessing the ability of health-care professionals to determine the possible causes.

METHODS

We conducted a 36-h training program focused on patient-ventilator asynchrony detection and management for health-care professionals from 20 hospitals in Latin America and Spain. The training program included 6 h of a live online lesson during which 120 patient-ventilator asynchrony cases were presented. After the 6-h training lesson, health-care professionals were required to complete a 1-h training session per day for the subsequent 30 d. A 30-question assessment tool was developed and used to assess health-care professionals before training, immediately after the 6-h training lecture, and after the 30 d of training (1-month follow-up).

RESULTS

One hundred sixteen health-care professionals participated in the study. The median (interquartile range) of the total number of correct answers in the pre-training, post-training, and 1-month follow-up were significantly different (12 [8.75-15], 18 [13.75-22], and 18.5 [14-23], respectively). The percentages of correct answers also differed significantly between the time assessments. Study participants significantly improved their performance between pre-training and post-training (P < .001). This performance was maintained after a 1-month follow-up (P = .95) for the questions related to the detection, determination of cause, and management of patient-ventilator asynchrony.

CONCLUSIONS

A specific 36-h training program significantly improved the ability of health-care professionals to detect patient-ventilator asynchrony, determine the possible causes of patient-ventilator asynchrony, and properly manage different types of patient-ventilator asynchrony.

Reverse Triggered Breath during Pressure Support Ventilation and Neurally Adjusted Ventilatory Assist at Increasing Propofol Infusion

BACKGROUND

Reverse triggered breath (RTB) has been extensively described during assisted-controlled modes of ventilation. We aimed to assess whether RTB occurs during Pressure Support Ventilation (PSV) and Neurally Adjusted Ventilatory Assist (NAVA) at varying depths of propofol sedation.

METHODS

This is a retrospective analysis of a prospective crossover randomized controlled trial conducted in an Intensive Care Unit (ICU) of a university hospital. Fourteen intubated patients for acute respiratory failure received six trials of 25 minutes randomly applying PSV and NAVA at three different propofol infusions: awake, light, and deep sedation. We assessed the occurrence of RTBs at each protocol step. The incidence level of RTBs was determined through the RTB index, which was calculated by dividing RTBs by the total number of breaths triggered and not triggered.

RESULTS

RTBs occurred during both PSV and NAVA. The RTB index was greater during PSV than during NAVA at mild (1.5 [0.0; 5.3]% vs. 0.6 [0.0; 1.1]%) and deep (5.9 [0.7; 9.0]% vs. 1.7 [0.9; 3.5]%) sedation.

CONCLUSIONS

RTB occurs in patients undergoing assisted mechanical ventilation. The level of propofol sedation and the mode of ventilation may influence the incidence of RTBs.

Advanced Point-of-care Bedside Monitoring for Acute Respiratory Failure

Advanced respiratory monitoring involves several mini- or noninvasive tools, applicable at bedside, focused on assessing lung aeration and morphology, lung recruitment and overdistention, ventilation-perfusion distribution, inspiratory effort, respiratory drive, respiratory muscle contraction, and patient-ventilator asynchrony, in dealing with acute respiratory failure. Compared to a conventional approach, advanced respiratory monitoring has the potential to provide more insights into the pathologic modifications of lung aeration induced by the underlying disease, follow the response to therapies, and support clinicians in setting up a respiratory support strategy aimed at protecting the lung and respiratory muscles. Thus, in the clinical management of the acute respiratory failure, advanced respiratory monitoring could play a key role when a therapeutic strategy, relying on individualization of the treatments, is adopted.

Monitoring the patient-ventilator asynchrony during non-invasive ventilation

Patient-ventilator asynchrony is a major issue during non-invasive ventilation and may lead to discomfort and treatment failure. Therefore, the identification and prompt management of asynchronies are of paramount importance during non-invasive ventilation (NIV), in both pediatric and adult populations. In this review, we first define the different forms of asynchronies, their classification, and the method of quantification. We, therefore, describe the technique to properly detect patient-ventilator asynchronies during NIV in pediatric and adult patients with acute respiratory failure, separately. Then, we describe the actions that can be implemented in an attempt to reduce the occurrence of asynchronies, including the use of non-conventional modes of ventilation. In the end, we analyzed what the literature reports on the impact of asynchronies on the clinical outcomes of infants, children, and adults.

Advantages and drawbacks of helmet noninvasive support in acute respiratory failure

INTRODUCTION

Non-invasive ventilation (NIV) represents an effective strategy for managing acute respiratory failure. Facemask NIV is strongly recommended in acute exacerbation of chronic obstructive pulmonary disease (AECOPD) with hypercapnia and acute cardiogenic pulmonary edema (ACPE). Its role in managing acute hypoxemic respiratory failure (AHRF) remains a debated issue. NIV and continuous positive airway pressure (CPAP) delivered through the helmet are recently receiving growing interest for AHRF management.

AREAS COVERED

In this narrative review, we discuss the clinical applications of helmet support compared to the other available noninvasive strategies in the different phenotypes of acute respiratory failure.

EXPERT OPINION

Helmets enable the use of high positive end-expiratory pressure, which may protect from self-inflicted lung injury: in AHRF, the possible superiority of helmet support over other noninvasive strategies in terms of clinical outcome has been hypothesized in a network metanalysis and a randomized trial, but has not been confirmed by other investigations and warrants confirmation. In AECOPD patients, helmet efficacy may be inferior to that of face masks, and its use prompts caution due to the risk of CO₂ rebreathing. Helmet support can be safely applied in hypoxemic patients with ACPE, with no advantages over facemasks.

How to recognize patients at risk of self-inflicted lung injury

INTRODUCTION

Patient self-inflicted lung injury (P-SILI) has been proposed as a form of lung injury caused by strong inspiratory efforts consequent to a high respiratory drive in patients with hypoxemic acute respiratory failure (hARF). Increased respiratory drive and effort may lead to variable combinations of deleterious phenomena, such as excessive transpulmonary pressure, pendelluft, intra-tidal recruitment, local lung volutrauma, and pulmonary edema. Gas exchange and respiratory mechanics derangements further increase respiratory drive and effort, thus inducing a vicious circle. Forms of partial ventilatory support may further add to the detrimental effects of P-SILI. Since P-SILI may worsen patient outcome, strategies aimed at identifying and preventing P-SILI would be of great importance.

AREAS COVERED

We systematically searched Pubmed since inception until 15 April 2022 to review the patho-physiological mechanisms of P-SILI and the strategies to identify those patients at risk of P-SILI.

EXPERT OPINION

Although the concept of P-SILI has been increasingly supported by experimental and clinical data, no study has insofar demonstrated the efficacy of any strategy to identify it in the clinical setting. Further research is thus needed to ascertain the detrimental effects of spontaneous breathing and identify patients with hARF at high risk of developing P-SILI.

Comfort During Non-invasive Ventilation

Non-invasive ventilation (NIV) has been shown to be effective in avoiding intubation and improving survival in patients with acute hypoxemic respiratory failure (ARF) when compared to conventional oxygen therapy. However, NIV is associated with high failure rates due, in most cases, to patient discomfort. Therefore, increasing attention has been paid to all those interventions aimed at enhancing patient's tolerance to NIV. Several practical aspects have been considered to improve patient adaptation. In particular, the choice of the interface and the ventilatory setting adopted for NIV play a key role in the success of respiratory assistance. Among the different NIV interfaces, tolerance is poorest for the nasal and oronasal masks, while helmet appears to be better tolerated, resulting in longer use and lower NIV failure rates. The choice of fixing system also significantly affects patient comfort due to pain and possible pressure ulcers related to the device. The ventilatory setting adopted for NIV is associated with varying degrees of patient comfort: patients are more comfortable with pressure-support ventilation (PSV) than controlled ventilation. Furthermore, the use of electrical activity of the diaphragm (EADi)-driven ventilation has been demonstrated to improve patient comfort when compared to PSV, while reducing neural drive and effort. If non-pharmacological remedies fail, sedation can be employed to improve patient's tolerance to NIV. Sedation facilitates ventilation, reduces anxiety, promotes sleep, and modulates physiological responses to stress. Judicious use of sedation may be an option to increase the chances of success in some patients at risk for intubation because of NIV intolerance consequent to pain, discomfort, claustrophobia, or agitation. During the Coronavirus Disease-19 (COVID-19) pandemic, NIV has been extensively employed to face off the massive request for ventilatory assistance. Prone positioning in non-intubated awake COVID-19 patients may improve oxygenation, reduce work of breathing, and, possibly, prevent intubation. Despite these advantages, maintaining prone position can be particularly challenging because poor comfort has been described as the main cause of prone position discontinuation. In conclusion, comfort is one of the major determinants of NIV success. All the strategies aimed to increase comfort during NIV should be pursued.

Current Practice of High Flow through Nasal Cannula in Exacerbated COPD Patients

Acute Exacerbation of Chronic Obstructive Pulmonary Disease is a form of severe Acute Respiratory Failure (ARF) requiring Conventional Oxygen Therapy (COT) in the case of absence of acidosis or the application of Non-Invasive Ventilation (NIV) in case of respiratory acidosis. In the last decade, High Flow through Nasal Cannula (HFNC) has been increasingly used, mainly in patients with hypoxemic ARF. However, some studies were also published in AECOPD patients, and some evidence emerged. In this review, after describing the mechanism underlying potential clinical benefits, we analyzed the possible clinical application of HFNC to AECOPD patients. In the case of respiratory acidosis, the gold-standard treatment remains NIV, supported by strong evidence in favor. However, HFNC may be considered as an alternative to NIV if the latter fails for intolerance. HFNC should also be considered and preferred to COT at NIV breaks and weaning. Finally, HFNC should also be preferred to COT as first-line oxygen treatment in AECOPD patients without respiratory acidosis.

Patient-Ventilator Synchronization During Non-invasive Ventilation: A Pilot Study of an Automated Analysis System

Background: Patient-ventilator synchronization during non-invasive ventilation (NIV) can be assessed by visual inspection of flow and pressure waveforms but it remains time consuming and there is a large inter-rater variability, even among expert physicians. SyncSmart™ software developed by Breas Medical (Mölnycke, Sweden) provides an automatic detection and scoring of patient-ventilator asynchrony to help physicians in their daily clinical practice. This study was designed to assess performance of the automatic scoring by the SyncSmart software using expert clinicians as a reference in patient with chronic respiratory failure receiving NIV.

Methods: From nine patients, 20 min data sets were analyzed automatically by SyncSmart software and reviewed by nine expert physicians who were asked to score auto-triggering (AT), double-triggering (DT), and ineffective efforts (IE). The study procedure was similar to the one commonly used for validating the automatic sleep scoring technique. For each patient, the asynchrony index was computed by automatic scoring and each expert, respectively. Considering successively each expert scoring as a reference, sensitivity, specificity, positive predictive value (PPV), κ-coefficients, and agreement were calculated.

Results: The asynchrony index assessed by SynSmart was not significantly different from the one assessed by the experts (18.9 ± 17.7 vs. 12.8 ± 9.4, p = 0.19). When compared to an expert, the sensitivity and specificity provided by SyncSmart for DT, AT, and IE were significantly greater than those provided by an expert when compared to another expert.

Conclusions:SyncSmart software is able to score asynchrony events within the inter-rater variability. When the breathing frequency is not too high (<24), it therefore provides a reliable assessment of patient-ventilator asynchrony; AT is over detected otherwise.

Oxygenation strategies during flexible bronchoscopy: a review of the literature

During flexible fiberoptic bronchoscopy (FOB) the arterial partial pressure of oxygen can drop, increasing the risk for respiratory failure. To avoid desaturation episodes during the procedure several oxygenation strategies have been proposed, including conventional oxygen therapy (COT), high flow nasal cannula (HFNC), continuous positive airway pressure (CPAP) and non-invasive ventilation (NIV). By a review of the current literature, we merely describe the clinical practice of oxygen therapies during FOB. We also conducted a pooled data analysis with respect to oxygenation outcomes, comparing HFNC with COT and NIV, separately. COT showed its benefits in patients undergoing FOB for broncho-alveolar lavage (BAL) or brushing for cytology, in those with peripheral arterial oxyhemoglobin saturation < 93% prior to the procedure or affected by obstructive disorder. HFNC is preferable over COT in patients with mild to moderate acute respiratory failure (ARF) undergoing FOB, by improving oxygen saturation and decreasing the episodes of desaturation. On the opposite, CPAP and NIV guarantee improved oxygenation outcomes as compared to HFNC, and they should be preferred in patients with more severe hypoxemic ARF during FOB.

The use of head helmets to deliver noninvasive ventilatory support: a comprehensive review of technical aspects and clinical findings

A helmet, comprising a transparent hood and a soft collar, surrounding the patient’s head can be used to deliver noninvasive ventilatory support, both as continuous positive airway pressure and noninvasive positive pressure ventilation (NPPV), the latter providing active support for inspiration. In this review, we summarize the technical aspects relevant to this device, particularly how to prevent CO₂ rebreathing and improve patient–ventilator synchrony during NPPV. Clinical studies describe the application of helmets in cardiogenic pulmonary oedema, pneumonia, COVID-19, postextubation and immune suppression. A section is dedicated to paediatric use. In summary, helmet therapy can be used safely and effectively to provide NIV during hypoxemic respiratory failure, improving oxygenation and possibly leading to better patient-centred outcomes than other interfaces.

Intelligent decision support with machine learning for efficient management of mechanical ventilation in the intensive care unit - A critical overview

BACKGROUND

Effective management of Mechanical Ventilation (MV) is vital for reducing morbidity, mortality, and cost of healthcare.

OBJECTIVE

This study aims to synthesize evidence for effective MV management through Intelligent decision support (IDS) with Machine Learning (ML).

METHOD

Databases that include EBSCO, IEEEXplore, Google Scholar, SCOPUS, and the Web of Science were systematically searched to identify studies on IDS for effective MV management regarding Tidal Volume (TV), asynchrony, weaning, and other outcomes such as the risk of Prolonged Mechanical ventilation (PMV). The quality of the articles identified was assessed with a modified Joanna Briggs Institute (JBI) critical appraisal checklist for cross-sessional research.

RESULTS

A total of 26 articles were identified for the study that has IDS for TV (n = 2, 7.8 %), asynchrony (n = 9, 34.6 %), weaning (n = 12, 46.2 %), and others (n = 3, 11.5 %). It was affirmed that implementing IDS in MV management will enhance seamless ICU patient management following the utilization of various Machine Learning (ML) algorithms in decision support. The studies relied on (n = 14) ML algorithms to predict the TV, asynchrony, weaning, risk of PMV and Positive End-Expiratory Pressure (PEEP) changes of 11-20262 ICU patients records with model inputs ranging from (n = 1) for timeseries analysis of TV to (n = 47) for weaning prediction.

CONCLUSIONS

The small data size, poor study design, and result reporting, with the heterogeneity of techniques used in the various studies, hampered the development of a unified approach for managing MV efficiency in TV monitoring, asynchrony, and weaning predictions. Notwithstanding, the ensemble model was able to predict TV, asynchrony, and weaning to a higher accuracy than the other algorithms.

Patient-Ventilator Asynchrony in Critical Care Settings: National Outcomes of Ventilator Waveform Analysis

BACKGROUND

Patient-ventilator asynchrony (PVA) is a prevalent and often underrecognized problem in mechanically ventilated patients. Ventilator waveform analysis is a noninvasive and reliable means of detecting PVAs, but the use of this tool has not been broadly studied.

METHODS

Our observational analysis leveraged a validated evaluation tool to assess the ability of critical care practitioners (CCPs) to detect different PVA types as presented in three videos. This tool consisted of three videos of common PVAs (i.e., double-triggering, auto-triggering, and ineffective triggering). Data were collected via an evaluation sheet distributed to 39 hospitals among the various CCPs, including respiratory therapists (RTs), nurses, and physicians.

RESULTS

A total of 411 CCPs were assessed; of these, only 41 (10.2%) correctly identified the three PVA types, while 92 (22.4%) correctly detected two types and 174 (42.3%) correctly detected one; 25.3% did not recognize any PVA. There were statistically significant differences between trained and untrained CCPs in terms of recognition (three PVAs, p < 0.001; two PVAs, p = 0.001). The majority of CCPs who identified one or zero PVAs were untrained, and such differences among groups were statistically significant (one PVA, p = 0.001; zero PVAs, p = 0.004). Female gender and prior training on ventilator waveforms were found to increase the odds of identifying more than two PVAs correctly, with odds ratios (ORs) (95% confidence intervals [CIs]) of 1.93 (1.07-3.49) and 5.41 (3.26-8.98), respectively. Profession, experience, and hospital characteristics were not found to correlate with increased odds of detecting PVAs; this association generally held after applying a regression model on the RT profession, with the ORs (95% CIs) of prior training (2.89 [1.28-6.51]) and female gender (2.49 [1.15-5.39]) showing the increased odds of detecting two or more PVAs.

CONCLUSION

Common PVAs detection were found low in critical care settings, with about 25% of PVA going undetected by CCPs. Female gender and prior training on ventilator graphics were the only significant predictive factors among CCPs and RTs in correctly identifying PVAs. There is an urgent need to establish teaching and training programs, policies, and guidelines vis-à-vis the early detection and management of PVAs in mechanically ventilated patients, so as to improve their outcomes.

High Flow Through Nasal Cannula in Stable and Exacerbated Chronic Obstructive Pulmonary Disease Patients

BACKGROUND

High-Flow through Nasal Cannula (HFNC) is a system delivering heated humidified air-oxygen mixture at a flow up to 60 L/min. Despite increasing evidence in hypoxemic acute respiratory failure, a few is currently known in chronic obstructive pulmonary disease (COPD) patients.

OBJECTIVE

To describe the rationale and physiologic advantages of HFNC in COPD patients, and to systematically review the literature on the use of HFNC in stable and exacerbated COPD patients, separately.

METHODS

A search strategy was launched on MEDLINE. Two authors separately screened all potential references. All (randomized, non-randomized and quasi-randomized) trials dealing with the use of HFNC in both stable and exacerbated COPD patients in MEDLINE have been included in the review.

RESULTS

Twenty-six studies have been included. HFNC: 1) provides heated and humidified airoxygen admixture; 2) washes out the anatomical dead space of the upper airway; 3) generates a small positive end-expiratory pressure; 4) guarantees a more stable inspired oxygen fraction, as compared to conventional oxygen therapy (COT); and 5) is more comfortable as compared to both COT and non-invasive ventilation (NIV). In stable COPD patients, HFNC improves gas exchange, the quality of life and dyspnea with a reduced cost of muscle energy expenditure, compared to COT. In exacerbated COPD patients, HFNC may be an alternative to NIV (in case of intolerance) and to COT at extubation or NIV withdrawal.

CONCLUSION

Though evidence of superiority still lacks and further studies are necessary, HFNC might play a role in the treatment of both stable and exacerbated COPD patients.

Ventilator- and interface-related factors influencing patient-ventilator asynchrony during noninvasive ventilation

Patient-ventilator asynchrony (PVA) is common in patients receiving noninvasive ventilation (NIV). This occurs primarily when the triggering and cycling-off of ventilatory assistance are not synchronized with the patient's inspiratory efforts and could result in increased work of breathing and niv failure. In general, five types of asynchrony can occur during NIV: ineffective inspiratory efforts, double-triggering, auto-triggering, short-ventilatory cycling, and long-ventilatory cycling. Many factors that affect PVA are mostly related to the degree of air leakage, level of pressure support, and the type and properties of the interface used. Careful monitoring and adjustment of these factors are essential to reduce PVA and improve patient comfort. In this article, we discuss the machine and interface-related factors that influence PVA during NIV and its effect on the respiratory mechanics during pressure support ventilation, which is the ventilatory mode used most commonly during NIV. For that, we critically evaluated studies that assessed ventilator- and interface-related factors that influence PVA during NIV and proposed therapeutic solutions.

The use of non-invasive ventilation in an exacerbation of chronic obstructive pulmonary disease: a case study

This article aims to assist nurses and other health professionals to care for patients who have type 2 respiratory failure as a result of chronic obstructive pulmonary disease, and who require non-invasive ventilation. It outlines findings of a case study that are commonplace in the acute medical setting and aims to highlight important factors that impact on patient care and patient outcome, and to help nursing staff to implement recommended and best practices.

Identifying and managing patient-ventilator asynchrony: An international survey

OBJECTIVE

To describe the main factors associated with proper recognition and management of patient-ventilator asynchrony (PVA).

DESIGN

An analytical cross-sectional study was carried out.

SETTING

An international study conducted in 20 countries through an online survey.

PARTICIPANTS

Physicians, respiratory therapists, nurses and physiotherapists currently working in the Intensive Care Unit (ICU).

MAIN VARIABLES OF INTEREST

Univariate and multivariate logistic regression models were used to establish associations between all variables (profession, training in mechanical ventilation, type of training program, years of experience and ICU characteristics) and the ability of HCPs to correctly identify and manage 6 PVA.

RESULTS

A total of 431 healthcare professionals answered a validated survey. The main factors associated to proper recognition of PVA were: specific training program in mechanical ventilation (MV) (OR 2.27; 95%CI 1.14-4.52; p=0.019), courses with more than 100h completed (OR 2.28; 95%CI 1.29-4.03; p=0.005), and the number of ICU beds (OR 1.037; 95%CI 1.01-1.06; p=0.005). The main factor influencing the management of PVA was the correct recognition of 6 PVAs (OR 118.98; 95%CI 35.25-401.58; p<0.001).

CONCLUSION

Identifying and managing PVA using ventilator waveform analysis is influenced by many factors, including specific training programs in MV, the number of ICU beds, and the number of recognized PVAs.

High-flow nasal therapy versus noninvasive ventilation in COPD patients with mild-to-moderate hypercapnic acute respiratory failure: study protocol for a noninferiority randomized clinical trial

Background

Noninvasive ventilation (NIV) is indicated to treat respiratory acidosis due to exacerbation of chronic obstructive pulmonary disease (COPD). Recent nonrandomized studies also demonstrated some physiological effects of high-flow nasal therapy (HFNT) in COPD patients. We designed a prospective, unblinded, multicenter, randomized controlled trial to assess the noninferiority of HFNT compared to NIV with respect to the reduction of arterial partial pressure of carbon dioxide (PaCO₂) in patients with hypercapnic acute respiratory failure with mild-to-moderate respiratory acidosis.

Methods

We will enroll adult patients with acute hypercapnic respiratory failure, as defined by arterial pH between 7.25 and 7.35 and PaCO₂ ≥ 55 mmHg. Patients will be randomly assigned 1:1 to receive NIV or HFNT. NIV will be applied through a mask with a dedicated ventilator in pressure support mode. Positive end-expiratory pressure will be set at 3–5 cmH₂O with inspiratory support to obtain a tidal volume between 6 and 8 ml/kg of ideal body weight. HFNT will be initially set at a temperature of 37 °C and a flow of 60 L/min. At 2 and 6 h we will assess arterial blood gases, vital parameters, respiratory rate, treatment intolerance and failure, need for endotracheal intubation, time spent under mechanical ventilation (both invasive and NIV), intensive care unit and hospital length of stay, and hospital mortality.

Based on an α error of 5% and a β error of 80%, with a standard deviation for PaCO₂ equal to 15 mmHg and a noninferiority limit of 10 mmHg, we computed a sample size of 56 patients. Considering potential drop-outs and nonparametric analysis, the final computed sample size was 80 patients (40 per group).

Discussion

HFNT is more comfortable than NIV in COPD patients recovering from an episode of exacerbation. If HFNT would not be inferior to NIV, HFNT could be considered as an alternative to NIV to treat COPD patients with mild-to-moderate respiratory acidosis.

Trial registration

ClinicalTrials.gov, NCT03370666. Registered on December 12, 2017.

Electronic supplementary material

The online version of this article (10.1186/s13063-019-3514-1) contains supplementary material, which is available to authorized users.

Patient-ventilator asynchrony in adult critically ill patients

INTRODUCTION

Patient-ventilator asynchrony is considered a major clinical problem for mechanically ventilated patients. It occurs during partial ventilatory support, when the respiratory muscles and the ventilator interact to contribute generating the volume output. In this review article, we consider all studies published on patient-ventilator asynchrony in the last 25 years.

EVIDENCE ACQUISITION

We selected 62 studies. The different forms of asynchrony are first defined and classified. We also describe the methods used for detecting and quantifying asynchronies. We then outline the outcome variables considered for evaluating the clinical consequences of asynchronies. The methodology for detection and quantification of patient-ventilator asynchrony are quite heterogeneous. In particular, the Asynchrony Index is calculated differently among studies.

EVIDENCE SYNTHESIS

Sixteen studies established some relationship between asynchronies and one or more clinical outcomes, such as duration of mechanical ventilation (seven studies), mortality (five studies), length of intensive care and hospital stay (four studies), patient comfort (four studies), quality of sleep (three studies), and rate of tracheotomy (three studies). In patients with severe patient-ventilator asynchrony, four of seven studies (57%) report prolonged duration of mechanical ventilation, one of five (20%) increased mortality, one of four (25%) longer intensive care and hospital lengths of stay, four of four (100%) worsened comfort, three of four (75%) deteriorated quality of sleep, and one of three (33%) increased rate of tracheotomy.

CONCLUSIONS

Given the varying outcomes considered and the erratic results, it remains unclear whether asynchronies really affects patient outcome, and the relationship between asynchronies and outcome is causative or associative.

Patient-ventilator asynchronies: types, outcomes and nursing detection skills

BACKGROUND

Mechanical ventilation is often employed as partial ventilatory support where both the patient and the ventilator work together. The ventilator settings should be adjusted to maintain a harmonious patient-ventilator interaction. However, this balance is often altered by many factors able to generate a patient ventilator asynchrony (PVA). The aims of this review were: to identify PVAs, their typologies and classifications; to describe how and to what extent their occurrence can affect the patients' outcomes; to investigate the levels of nursing skill in detecting PVAs.

METHODS

Literature review performed on Cochrane Library, Medline and CINAHL databases.

RESULTS

1610 records were identified; 43 records were included after double blind screening. PVAs have been classified with respect to the phase of the respiratory cycle or based on the circumstance of occurrence. There is agreement on the existence of 7 types of PVAs: ineffective effort, double trigger, premature cycling, delayed cycling, reverse triggering, flow starvation and auto-cycling. PVAs can be identified through the ventilator graphics monitoring of pressure and flow waveforms.  The influence on patient outcomes varies greatly among studies but PVAs are mostly associated with poorer outcomes. Adequately trained nurses can learn and retain how to correctly detect PVAs.

CONCLUSIONS

Since its challenging interpretation and the potential advantages of its implementation, ventilator graphics monitoring can be classified as an advanced competence for ICU nurses. The knowledge and skills to adequately manage PVAs should be provided by specific post-graduate university courses.

High-intensity non-invasive ventilation in stable hypercapnic COPD: Evidence of efficacy and practical advice

Patients with end-stage chronic obstructive pulmonary disease (COPD) frequently develop chronic hypercapnic respiratory failure (CHRF), with disabling symptoms and poor survival. The use of long-term nocturnal non-invasive ventilation (NIV) to treat CHRF in COPD has long been subject of debate due to conflicting evidence. However, since the introduction of high-intensity NIV (HI-NIV) in COPD, physiological and clinical benefits have been shown. HI-NIV refers to specific ventilator settings used for NIV aimed at achieving normocapnia or the lowest partial arterial carbon dioxide pressure (PaCO₂ ) values as possible. This review will provide an overview of existing evidence of the efficacy of HI-NIV stable COPD patients with CHRF. Secondly, we will discuss hypotheses underlying NIV benefit in stable hypercapnic COPD, providing insight into better patient selection and hopefully more individually titrated HI-NIV. Finally, we will provide practical advice on how to initiate and follow-up patients on HI-NIV, with special emphasis on monitoring that should be available during the initiation and follow-up of HI-NIV, and will discuss more extended monitoring techniques that could improve HI-NIV treatment in the future.

Looking under the bonnet of patient-ventilator asynchrony during noninvasive ventilation: does it add value?

Noninvasive ventilation (NIV) has significant advantages over invasive ventilation in certain situations, such as hypercapnic respiratory failure due to an acute exacerbation of chronic obstructive pulmonary disease (COPD), acute cardiogenic pulmonary oedema, respiratory failure in immunocompromised patients and weaning from invasive ventilation in patients with COPD, in terms of reducing mortality, duration of hospital stay, the need for intubation and infectious complications [1–5].

During noninvasive ventilation it is reasonable to try to abolish clinically apparent patient-ventilator asynchronies but the use of more invasive tests to detect subtle asynchronies cannot be justifiedhttp://ow.ly/rXoA30gCm8O