A diaphragmatic electrical activity-based optimization strategy during pressure support ventilation improves synchronization but does not impact work of breathing

RESPIRATORY MECHANICS AND NEURAL RESPIRATORY DRIVE OF UNTREATED GASPING DURING CARDIAC ARREST IN A PORCINE MODEL

ABSTRACT

Introduction: Although the effects on hemodynamics of gasping during cardiac arrest (CA) have received a lot of attention, less is known about the respiratory mechanics and physiology of respiration in gasping. This study aimed to investigate the respiratory mechanics and neural respiratory drive of gasping during CA in a porcine model. Method: Pigs weighing 34.9 ± 5.7 kg were anesthetized intravenously. Ventricular fibrillation (VF) was electrically induced and untreated for 10 min. Mechanical ventilation (MV) was ceased immediately after the onset of VF. Hemodynamic and respiratory parameters, pressure signals, diaphragmatic electromyogram data, and blood gas analysis data were recorded. Results: Gasping was observed in all the animals at a significantly lower rate (2-5 gaps/min), with higher tidal volume ( VT ; 0.62 ± 0.19 L, P < 0.01), and with lower expired minute volume (2.51 ± 1.49 L/min, P < 0.001) in comparison with the baseline. The total respiratory cycle time and the expiratory time tended to be lengthened. Statistically significant elevations in transdiaphragmatic pressure, the pressure-time product of diaphragmatic pressure, and the mean of root mean square diaphragmatic electromyogram values (RMSmean) were observed ( P < 0.05, P < 0.05, and P < 0.001, respectively); however, VT /RMSmean and transdiaphragmatic pressure/RMSmean were reduced at all time points. The partial pressure of oxygen showed a continuous decline after VF to reach statistical significance in the 10th minute (9.46 ± 0.96 kPa, P < 0.001), whereas the partial pressure of carbon dioxide tended to first rise and then fall. Conclusions: Gasping during CA was characterized by high VT , extremely low frequency, and prolonged expiratory time, which may improve hypercapnia. During gasping, increased work of breathing and insufficient neuromechanical efficacy of neural respiratory drive suggested the necessity of MV and appropriate management strategies for MV during resuscitation after CA.

High-value care for critically ill oncohematological patients: what do we know thus far?

The number of patients with cancer requiring intensive care unit admission is increasing around the world. The improvement in the pathophysiological understanding of this group of patients, as well as the increasingly better and more targeted treatment options for their underlying disease, has led to a significant increase in their survival over the past three decades. Within the organizational concepts, it is necessary to know what adds value in the care of critical oncohematological patients. Practices in medicine that do not benefit patients and possibly cause harm are called low-value practices, while high-value practices are defined as high-quality care at relatively low cost. In this article, we discuss ten domains with high-value evidence in the care of cancer patients: (1) intensive care unit admission policies; (2) intensive care unit organization; (3) etiological investigation of hypoxemia; (4) management of acute respiratory failure; (5) management of febrile neutropenia; (6) urgent chemotherapy treatment in critically ill patients; (7) patient and family experience; (8) palliative care; (9) care of intensive care unit staff; and (10) long-term impact of critical disease on the cancer population. The disclosure of such policies is expected to have the potential to change health care standards. We understand that it is a lengthy process, and initiatives such as this paper are one of the first steps in raising awareness and beginning a discussion about high-value care in various health scenarios.

Patient-Ventilator Synchrony in Neurally-Adjusted Ventilatory Assist and Variable Pressure Support Ventilation

BACKGROUND

Neurally-adjusted ventilatory assist (NAVA) improves patient-ventilator synchrony and reduces the risk of respiratory over-assistance. Variable pressure support ventilation (PSV) is a recently introduced mode of assisted ventilation that has also shown reduction in patient-ventilator asynchronies. We hypothesized that NAVA would reduce patient-ventilator asynchronies and inspiratory effort compared to variable PSV because breathing variability was intrinsically determined by the patient and not by the ventilator. This study aimed to evaluate patient-ventilator asynchronies and inspiratory effort pressure-time product (PTP) between NAVA and variable PSV in subjects with mild ARDS.

METHODS

After 24 h of controlled mechanical ventilation, subjects (P_aO2 /F_IO2 200-300 and PEEP level < 10 cm H₂O) were randomized in sequence 1:1 by using a web-based encrypted platform and assigned to NAVA or variable PSV groups. Both modes of ventilation were consecutively kept for 24 h unless there were clinical changes. The primary aim of this study was to evaluate differences in asynchrony index (AI) between variable PSV and NAVA. Our secondary aims were to evaluate the coefficient of variation (CV) of breathing patterns and inspiratory effort between the groups.

RESULTS

Thirteen subjects were randomized in the NAVA group and 13 subjects in the variable PSV group. AI over time and minute PTP (PTP_min) were not different between NAVA and variable PSV groups (AI t₀P = .52, AI t₁₂P = .27, AI t₂₄P = .12; and PTP_min-t0P = .60, PTP_min-t12P = .57, PTP_min-t24P = .85, respectively). CV for tidal volume (V_T) and pressure support (PS) was lower in variable PSV group over time compared with NAVA group (P < .05).

CONCLUSIONS

In this randomized controlled trial including subjects with mild ARDS, NAVA and variable PSV had comparable effects on patient-ventilator synchronies and PTP. However, variable PSV reduced the variability of V_T and PS when compared with NAVA.

Lung and diaphragm protective ventilation: a synthesis of recent data

INTRODUCTION

: To adhere to the Hippocratic Oath, to "first, do no harm", we need to make every effort to minimize the adverse effects of mechanical ventilation. Our understanding of the mechanisms of ventilator-induced lung injury (VILI) and ventilator-induced diaphragm dysfunction (VIDD) has increased in recent years. Research focuses now on methods to monitor lung stress and inhomogeneity and targets we should aim for when setting the ventilator. In parallel, efforts to promote early assisted ventilation to prevent VIDD have revealed new challenges, such as titrating inspiratory effort and synchronizing the mechanical with the patients' spontaneous breaths, while at the same time adhering to lung-protective targets.

AREAS COVERED

This is a narrative review of the key mechanisms contributing to VILI and VIDD and the methods currently available to evaluate and mitigate the risk of lung and diaphragm injury.

EXPERT OPINION

Implementing lung and diaphragm protective ventilation requires individualizing the ventilator settings, and this can only be accomplished by exploiting in everyday clinical practice the tools available to monitor lung stress and inhomogeneity, inspiratory effort, and patient-ventilator interaction.

Automatic Adjustment of the Inspiratory Trigger and Cycling-Off Criteria Improved Patient-Ventilator Asynchrony During Pressure Support Ventilation

Background: Patient-ventilator asynchrony is common during pressure support ventilation (PSV) because of the constant cycling-off criteria and variation of respiratory system mechanical properties in individual patients. Automatic adjustment of inspiratory triggers and cycling-off criteria based on waveforms might be a useful tool to improve patient-ventilator asynchrony during PSV.

Method: Twenty-four patients were enrolled and were ventilated using PSV with different cycling-off criteria of 10% (PS₁₀), 30% (PS₃₀), 50% (PS₅₀), and automatic adjustment PSV (PS_AUTO). Patient-ventilator interactions were measured.

Results: The total asynchrony index (AI) and NeuroSync index were consistently lower in PS_AUTO when compared with PS₁₀, PS₃₀, and PS₅₀, (P < 0.05). The benefit of PS_AUTO in reducing the total AI was mainly because of the reduction of the micro-AI but not the macro-AI. PS_AUTO significantly improved the relative cycling-off error when compared with prefixed controlled PSV (P < 0.05). PS_AUTO significantly reduced the trigger error and inspiratory effort for the trigger when compared with a prefixed trigger. However, total inspiratory effort, breathing patterns, and respiratory drive were not different among modes.

Conclusions: When compared with fixed cycling-off criteria, an automatic adjustment system improved patient-ventilator asynchrony without changes in breathing patterns during PSV. The automatic adjustment system could be a useful tool to titrate more personalized mechanical ventilation.

Neural control of pressure support ventilation improved patient-ventilator synchrony in patients with different respiratory system mechanical properties: a prospective, crossover trial

Background

Conventional pressure support ventilation (PS_P) is triggered and cycled off by pneumatic signals such as flow. Patient-ventilator asynchrony is common during pressure support ventilation, thereby contributing to an increased inspiratory effort. Using diaphragm electrical activity, neurally controlled pressure support (PS_N) could hypothetically eliminate the asynchrony and reduce inspiratory effort. The purpose of this study was to compare the differences between PS_N and PS_P in terms of patient-ventilator synchrony, inspiratory effort, and breathing pattern.

Methods

Eight post-operative patients without respiratory system comorbidity, eight patients with acute respiratory distress syndrome (ARDS) and obvious restrictive acute respiratory failure (ARF), and eight patients with chronic obstructive pulmonary disease (COPD) and mixed restrictive and obstructive ARF were enrolled. Patient-ventilator interactions were analyzed with macro asynchronies (ineffective, double, and auto triggering), micro asynchronies (inspiratory trigger delay, premature, and late cycling), and the total asynchrony index (AI). Inspiratory efforts for triggering and total inspiration were analyzed.

Results

Total AI of PS_N was consistently lower than that of PS_P in COPD (3% vs. 93%, P = 0.012 for 100% support level; 8% vs. 104%, P = 0.012 for 150% support level), ARDS (8% vs. 29%, P = 0.012 for 100% support level; 16% vs. 41%, P = 0.017 for 150% support level), and post-operative patients (21% vs. 35%, P = 0.012 for 100% support level; 15% vs. 50%, P = 0.017 for 150% support level). Improved support levels from 100% to 150% statistically increased total AI during PS_P but not during PS_N in patients with COPD or ARDS. Patients’ inspiratory efforts for triggering and total inspiration were significantly lower during PS_N than during PS_P in patients with COPD or ARDS under both support levels (P < 0.05). There was no difference in breathing patterns between PS_N and PS_P.

Conclusions

PS_N improves patient-ventilator synchrony and generates a respiratory pattern similar to PS_P independently of any level of support in patients with different respiratory system mechanical properties. PS_N, which reduces the trigger and total patient's inspiratory effort in patients with COPD or ARDS, might be an alternative mode for PS_P.

Trial Registration

ClinicalTrials.gov, NCT01979627; https://clinicaltrials.gov/ct2/show/record/NCT01979627.

Continuous assessment of neuro-ventilatory drive during 12 h of pressure support ventilation in critically ill patients

Introduction

Pressure support ventilation (PSV) should allow spontaneous breathing with a “normal” neuro-ventilatory drive. Low neuro-ventilatory drive puts the patient at risk of diaphragmatic atrophy while high neuro-ventilatory drive may causes dyspnea and patient self-inflicted lung injury. We continuously assessed for 12 h the electrical activity of the diaphragm (EAdi), a close surrogate of neuro-ventilatory drive, during PSV. Our aim was to document the EAdi trend and the occurrence of periods of “Low” and/or “High” neuro-ventilatory drive during clinical application of PSV.

Method

In 16 critically ill patients ventilated in the PSV mode for clinical reasons, inspiratory peak EAdi peak (EAdi_PEAK), pressure time product of the trans-diaphragmatic pressure per breath and per minute (PTP_DI/b and PTP_DI/min, respectively), breathing pattern and major asynchronies were continuously monitored for 12 h (from 8 a.m. to 8 p.m.). We identified breaths with “Normal” (EAdi_PEAK 5–15 μV), “Low” (EAdi_PEAK < 5 μV) and “High” (EAdi_PEAK > 15 μV) neuro-ventilatory drive.

Results

Within all the analyzed breaths (177.117), the neuro-ventilatory drive, as expressed by the EAdi_PEAK, was “Low” in 50.116 breath (28%), “Normal” in 88.419 breaths (50%) and “High” in 38.582 breaths (22%). The average times spent in “Low”, “Normal” and “High” class were 1.37, 3.67 and 0.55 h, respectively (p < 0.0001), with wide variations among patients. Eleven patients remained in the “Low” neuro-ventilatory drive class for more than 1 h, median 6.1 [3.9–8.5] h and 6 in the “High” neuro-ventilatory drive class, median 3.4 [2.2–7.8] h. The asynchrony index was significantly higher in the “Low” neuro-ventilatory class, mainly because of a higher number of missed efforts.

Conclusions

We observed wide variations in EAdi amplitude and unevenly distributed “Low” and “High” neuro ventilatory drive periods during 12 h of PSV in critically ill patients. Further studies are needed to assess the possible clinical implications of our physiological findings.

Proportional modes of ventilation: technology to assist physiology

Proportional modes of ventilation assist the patient by adapting to his/her effort, which contrasts with all other modes. The two proportional modes are referred to as neurally adjusted ventilatory assist (NAVA) and proportional assist ventilation with load-adjustable gain factors (PAV+): they deliver inspiratory assist in proportion to the patient’s effort, and hence directly respond to changes in ventilatory needs. Due to their working principles, NAVA and PAV+ have the ability to provide self-adjusted lung and diaphragm-protective ventilation. As these proportional modes differ from ‘classical’ modes such as pressure support ventilation (PSV), setting the inspiratory assist level is often puzzling for clinicians at the bedside as it is not based on usual parameters such as tidal volumes and PaCO₂ targets. This paper provides an in-depth overview of the working principles of NAVA and PAV+ and the physiological differences with PSV. Understanding these differences is fundamental for applying any assisted mode at the bedside. We review different methods for setting inspiratory assist during NAVA and PAV+ , and (future) indices for monitoring of patient effort. Last, differences with automated modes are mentioned.

Monitoring Patient Respiratory Effort During Mechanical Ventilation: Lung and Diaphragm-Protective Ventilation

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency Medicine 2020. Other selected articles can be found online at https://www.biomedcentral.com/collections/annualupdate2020. Further information about the Annual Update in Intensive Care and Emergency Medicine is available from http://www.springer.com/series/8901.

Information conveyed by electrical diaphragmatic activity during unstressed, stressed and assisted spontaneous breathing: a physiological study

Background

The electrical activity of the crural diaphragm (Eadi), a surrogate of respiratory drive, can now be measured at the bedside in mechanically ventilated patients with a specific catheter. The expected range of Eadi values under stressed or assisted spontaneous breathing is unknown. This study explored Eadi values in healthy subjects during unstressed (baseline), stressed (with a resistance) and assisted spontaneous breathing. The relation between Eadi and inspiratory effort was analyzed.

Methods

Thirteen healthy male volunteers were included in this randomized crossover study. Eadi and esophageal pressure (Peso) were recorded during unstressed and stressed spontaneous breathing and under assisted ventilation delivered in pressure support (PS) at low and high assist levels and in neurally adjusted ventilatory assist (NAVA). Overall eight different situations were assessed in each participant (randomized order). Peak, mean and integral of Eadi, breathing pattern, esophageal pressure–time product (PTPeso) and work of breathing (WOB) were calculated offline.

Results

Median [interquartile range] peak Eadi at baseline was 17 [13–22] μV and was above 10 μV in 92% of the cases. Eadi_max defined as Eadi measured at maximal inspiratory capacity reached 90 [63 to 99] μV. Median peak Eadi/Eadi_max ratio was 16.8 [15.6–27.9]%. Compared to baseline, respiratory rate and minute ventilation were decreased during stressed non-assisted breathing, whereas peak Eadi and PTPeso were increased. During unstressed assisted breathing, peak Eadi decreased during high-level PS compared to unstressed non-assisted breathing and to NAVA (p = 0.047). During stressed breathing, peak Eadi was lower during all assisted ventilation modalities compared to stressed non-assisted breathing. During assisted ventilation, across the different conditions, peak Eadi changed significantly, whereas PTPeso and WOB/min were not significantly modified. Finally, Eadi signal was still present even when Peso signal was suppressed due to high assist levels.

Conclusion

Eadi analysis provides complementary information compared to respiratory pattern and to Peso monitoring, particularly in the presence of high assist levels.

Trial registration The study was registered as NCT01818219 in clinicaltrial.gov. Registered 28 February 2013

Electronic supplementary material

The online version of this article (10.1186/s13613-019-0564-1) 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.