Flow Index: a novel, non-invasive, continuous, quantitative method to evaluate patient inspiratory effort during pressure support ventilation

Flow Index as a Noninvasive Method to Evaluate Inspiratory Effort in Patients on Pressure Support Ventilation

Background: The Flow Index was recently developed as a bedside method based on flow waveforms to assess patient inspiratory effort during invasive mechanical ventilation. The aim of this study is to externally validate the Flow Index by assessing its ability to identify low and high inspiratory effort breaths. Methods: Secondary analysis of a randomized controlled trial. The association between Flow Index and patient inspiratory effort (pressure generated by the respiratory muscles [ΔPmus] and pressure-time product from the start of inspiratory flow [PTPinsp]) was evaluated using linear mixed effects models. The discrimination capacity (area under the curve [AUC]) of the Flow Index to identify low and high inspiratory effort breaths was analyzed. Results: A total of 1,095 breaths from 38 subjects were included in the analysis. Flow Index had moderate discriminatory power in identifying low inspiratory effort breaths (AUC of 0.73 and 0.77 for low inspiratory effort defined with ΔPmus and PTPinsp, respectively). Discriminatory power in identifying high inspiratory effort breaths was low (AUC of 0.68 and 0.65 for ΔPmus and PTPinsp, respectively). Conclusions: Flow Index demonstrated moderate discriminatory power in identifying low inspiratory effort breaths, whereas discriminatory power in identifying high inspiratory effort breaths was low.

ARDS Weaning: The Impact of Abnormal Breathing Patterns Detected by Electric Tomography Impedance and Respiratory Mechanics Monitoring

Background: After the improvement of the initial phase of ARDS, when the patients begin spontaneous breathing and weaning from mechanical ventilation, some patients may present abnormal breathing patterns, whose evaluation of the repercussions were poorly studied. This study proposed to evaluate abnormal breathing patterns through the use of electrical impedance tomography (EIT), and clinical, respiratory mechanics, and ventilatory parameters according to the types of weaning from mechanical ventilation. Methods: This was a prospective cohort study of subjects with ARDS who were considered able to be weaned from mechanical ventilation in the clinical-surgical ICU. Weaning types were defined as simple, difficult, and prolonged weaning. EIT, ventilatory, lung mechanics, and clinical data were collected. Data were collected at baseline in a controlled ventilatory mode and, after neuromuscular blocker withdrawal, data were collected after 30 min, 2 h, and 24 h. EIT parameter analysis was performed for ventilation distribution in the lung regions, pendelluft, breath-stacking, reverse-trigger, double-trigger, and asynchrony index. Results: The study included 25 subjects who were divided into 3 groups (9/25 simple, 8/25 difficult, and 8/25 prolonged weaning). The prolonged weaning group showed more delirium, ICU-acquired weakness, stay in ICU, and hospital and ICU mortality. During the change from controlled to spontaneous mode, we observed increased tidal volumes and driving pressures, which were mainly found in the prolonged weaning group when compared with the simple weaning group. The prolonged weaning group showed a higher flow index, more asynchronies during volume-assisted ventilation, a higher incidence of pendelluft, and redistribution of ventilation to posterior regions visualized by EIT. Conclusions: The present study showed abnormal breathing patterns in the prolonged weaning group. The clinical occult findings of abnormal breathing patterns could be monitored, mainly through EIT and with better assessment of pulmonary mechanics.

Monitoring effort and respiratory drive in patients with acute respiratory failure

PURPOSE OF REVIEW

Accurate monitoring of respiratory drive and inspiratory effort is crucial for optimizing ventilatory support during acute respiratory failure. This review evaluates current and emerging bedside methods for assessing respiratory drive and effort.

RECENT FINDINGS

While electrical activity of the diaphragm and esophageal pressure remain the reference standards for assessing respiratory drive and effort, their clinical utility is largely limited to research. At the bedside, airway occlusion maneuvers are the most useful tools: P0.1 is a reliable marker of drive and detects abnormal inspiratory efforts, while occlusion pressure (Pocc) may outperform P0.1 in identifying excessive effort. The Pressure-Muscle-Index (PMI) can help detecting insufficient inspiratory effort, though its accuracy depends on obtaining a stable plateau pressure. Other techniques, such as central venous pressure swings (ΔCVP), are promising but require further investigation. Emerging machine learning and artificial intelligence based algorithms could play a pivotal role in automated respiratory monitoring in the near future.

SUMMARY

Although Pes and EAdi remain reference methods, airway occlusion maneuvers are currently the most practical bedside tools for monitoring respiratory drive and effort. Noninvasive alternatives such as ΔCVP deserve further evaluation. Artificial intelligence and machine learning may soon provide automated solutions for bedside monitoring of respiratory drive and effort.

Assessing agreement among non-invasive indicators for inspiratory effort during pressure support ventilation

Background

During pressure support ventilation (PSV), the accuracy of non-invasive indicators in diagnosing high or low inspiratory effort has been validated. However, the correlation and agreement of these indicators remain unclear. This study aims to investigate the correlation and agreement among non-invasive inspiratory effort indicators, and to compare characteristics of inspiratory effort in neurocritical and non-neurocritical patients.

Methods

This was a single-centre prospective observational study. We collected three non-invasive inspiratory effort indicators, pressure muscular index (PMI), the maximal negative swing of airway pressure during expiratory occlusion (ΔPocc), and the airway occlusion pressure during the first 100ms (P0.1). Cutoff values for these indicators derived from esophageal pressure-time product (PTPmus) were chosen for this study. The correlation and agreement of these indicators were analyzed using Spearman's rank correlation test and linear weighted Kappa analysis. Characteristics of PSV settings and inspiratory effort in neurocritical and non-neurocritical patients were compared.

Results

Ninety-seven patients were enrolled in this study. Correlation analysis showed a moderate correlation between PMI and ΔPocc (rho = -0.524, p < 0.001), ΔPocc and P0.1 (rho = 0.588, p < 0.001), while no correlation between PMI and P0.1 (rho = -0.140, p = 0.172). There was a moderate agreement between ΔPocc and P0.1 (k = 0.459, p < 0.001), a fair agreement between PMI and ΔPocc (k = 0.362, p < 0.001), but no agreement between PMI and P0.1 (k = 0.134, p = 0.072). The correlation of these indicators was similar in neurocritical patients compared with non-neurocritical patients, but agreement was poor.

Conclusion

The study showed that PMI and ΔPocc had moderate correlation and fair agreement, ΔPocc and P0.1 had moderate correlation and agreement, while PMI and P0.1 had no correlation and agreement.

Monitoring respiratory muscles effort during mechanical ventilation

PURPOSE OF REVIEW

To summarize basic physiological concepts of breathing effort and outline various methods for monitoring effort of inspiratory and expiratory muscles.

RECENT FINDINGS

Esophageal pressure (Pes) measurement is the reference standard for respiratory muscle effort quantification, but various noninvasive screening tools have been proposed. Expiratory occlusion pressures (P0.1 and Pocc) could inform about low and high effort and the resulting lung stress, with Pocc outperforming P0.1 in identifying high effort. The pressure muscle index during an inspiratory hold could unveil inspiratory muscle effort, however obtaining a reliable inspiratory plateau can be difficult. Surface electromyography has the potential for inspiratory effort estimation, yet this is technically challenging for real-time assessment. Expiratory muscle activation is common in the critically ill warranting their assessment, that is, via gastric pressure monitoring. Expiratory muscle activation also impacts inspiratory effort interpretation which could result in both under- and overestimation of the resulting lung stress. There is likely a future role for machine learning applications to automate breathing effort monitoring at the bedside.

SUMMARY

Different tools are available for monitoring the respiratory muscles' effort during mechanical ventilation - from noninvasive screening tools to more invasive quantification methods. This could facilitate a lung and respiratory muscle-protective ventilation approach.

Use of pressure muscle index to predict the contribution of patient's inspiratory effort during pressure support ventilation: a prospective physiological study

Background

The successful implementation of assisted ventilation depends on matching the patient's effort with the ventilator support. Pressure muscle index (PMI), an airway pressure based measurement, has been used as noninvasive monitoring to assess the patient's inspiratory effort. The authors aimed to evaluate the feasibility of pressure support adjustment according to the PMI target and the diagnostic performance of PMI to predict the contribution of the patient's effort during ventilator support.

Methods

In this prospective physiological study, 22 adult patients undergoing pressure support ventilation were enrolled. After an end-inspiratory airway occlusion, airway pressure reached a plateau, and the magnitude of change in plateau from peak airway pressure was defined as PMI. Pressure support was adjusted to obtain the PMI which was closest to -1, 0, +1, +2, and + 3 cm H2O. Each pressure support level was maintained for 20 min. Esophageal pressure was monitored. Pressure-time products of respiratory muscle and ventilator insufflation were measured, and the fraction of pressure generated by the patient was calculated to represent the contribution of the patient's inspiratory effort.

Results

A total of 105 datasets were collected at different PMI-targeted pressure support levels. The differences in PMI between the target and the obtained value were all within ±1 cm H2O. As targeted PMI increased, pressure support settings decreased significantly from a median (interquartile range) of 11 (10-12) to 5 (4-6) cm H2O (p < 0.001), which resulted in a significant increase in pressure-time products of respiratory muscle [from 2.9 (2.1-5.0) to 6.8 (5.3-8.1) cm H2O•s] and the fraction of pressure generated by the patient [from 25% (19-31%) to 72% (62-87%)] (p < 0.001). The area under receiver operating characteristic curves for PMI to predict 30 and 70% contribution of patient's effort were 0.93 and 0.95, respectively. High sensitivity (all 1.00), specificity (0.86 and 0.78), and negative predictive value (all 1.00), but low positive predictive value (0.61 and 0.43) were obtained to predict either high or low contribution of patient's effort.

Conclusion

Our results preliminarily suggested the feasibility of pressure support adjustment according to the PMI target from the ventilator screen. PMI could reliably predict the high and low contribution of a patient's effort during assisted ventilation.Clinical trial registration: ClinicalTrials.gov, identifier NCT05970393.

Advanced Respiratory Monitoring during Extracorporeal Membrane Oxygenation

Advanced respiratory monitoring encompasses a diverse range of mini- or noninvasive tools used to evaluate various aspects of respiratory function in patients experiencing acute respiratory failure, including those requiring extracorporeal membrane oxygenation (ECMO) support. Among these techniques, key modalities include esophageal pressure measurement (including derived pressures), lung and respiratory muscle ultrasounds, electrical impedance tomography, the monitoring of diaphragm electrical activity, and assessment of flow index. These tools play a critical role in assessing essential parameters such as lung recruitment and overdistention, lung aeration and morphology, ventilation/perfusion distribution, inspiratory effort, respiratory drive, respiratory muscle contraction, and patient-ventilator synchrony. In contrast to conventional methods, advanced respiratory monitoring offers a deeper understanding of pathological changes in lung aeration caused by underlying diseases. Moreover, it allows for meticulous tracking of responses to therapeutic interventions, aiding in the development of personalized respiratory support strategies aimed at preserving lung function and respiratory muscle integrity. The integration of advanced respiratory monitoring represents a significant advancement in the clinical management of acute respiratory failure. It serves as a cornerstone in scenarios where treatment strategies rely on tailored approaches, empowering clinicians to make informed decisions about intervention selection and adjustment. By enabling real-time assessment and modification of respiratory support, advanced monitoring not only optimizes care for patients with acute respiratory distress syndrome but also contributes to improved outcomes and enhanced patient safety.

State of the art: Monitoring of the respiratory system during veno-venous extracorporeal membrane oxygenation

Monitoring the patient receiving veno-venous extracorporeal membrane oxygenation (VV ECMO) is challenging due to the complex physiological interplay between native and membrane lung. Understanding these interactions is essential to understand the utility and limitations of different approaches to respiratory monitoring during ECMO. We present a summary of the underlying physiology of native and membrane lung gas exchange and describe different tools for titrating and monitoring gas exchange during ECMO. However, the most important role of VV ECMO in severe respiratory failure is as a means of avoiding further ergotrauma. Although optimal respiratory management during ECMO has not been defined, over the last decade there have been advances in multimodal respiratory assessment which have the potential to guide care. We describe a combination of imaging, ventilator-derived or invasive lung mechanic assessments as a means to individualise management during ECMO.

Neural Network-Enabled Identification of Weak Inspiratory Efforts during Pressure Support Ventilation Using Ventilator Waveforms

During pressure support ventilation (PSV), excessive assist results in weak inspiratory efforts and promotes diaphragm atrophy and delayed weaning. The aim of this study was to develop a classifier using a neural network to identify weak inspiratory efforts during PSV, based on the ventilator waveforms. Recordings of flow, airway, esophageal and gastric pressures from critically ill patients were used to create an annotated dataset, using data from 37 patients at 2-5 different levels of support, computing the inspiratory time and effort for every breath. The complete dataset was randomly split, and data from 22 patients (45,650 breaths) were used to develop the model. Using a One-Dimensional Convolutional Neural Network, a predictive model was developed to characterize the inspiratory effort of each breath as weak or not, using a threshold of 50 cmH₂O*s/min. The following results were produced by implementing the model on data from 15 different patients (31,343 breaths). The model predicted weak inspiratory efforts with a sensitivity of 88%, specificity of 72%, positive predictive value of 40%, and negative predictive value of 96%. These results provide a 'proof-of-concept' for the ability of such a neural-network based predictive model to facilitate the implementation of personalized assisted ventilation.

Paced breathing and respiratory movement responses evoked by bidirectional constant current stimulation in anesthetized rabbits

Objective: Diaphragm pacing (DP) is a long-term and effective respiratory assist therapy for patients with central alveolar hypoventilation and high cervical spinal cord injury. The existing DP system has some limitations, especially high price, inconvenience preoperative evaluation methods and diaphragm fatigue easily. Our objective was to develop a DP system and evaluated reliability through hardware testing and animal experiments. Methods: A DP system with bidirectional constant current was designed, manufactured and tested. Effects of a wide range of stimulus amplitudes (range: .5-2.5 mA) and frequencies (range: 10-250 Hz) on airflow and corresponding inspired volume were investigated during DP. Differences in airflow characteristics under various stimulation parameters were evaluated using power function. ECG interference in diaphragm electromyography (EMGdi) was filtered out using stationary wavelet transform to obtain pure EMGdi (EMGdi_p). 80-min period with a tendency for diaphragm fatigue by root mean square (RMS) and centroid frequency (f _c ) of EMGdi_p was studied. Results: The increase of stimulus frequency and amplitude in animals resulted in different degrees of increase in envoked volume. Significant difference in Airflow Index (b) between anesthesia and DP provided a simple, non-invasive and feasible solution for phrenic nerve conduction function test. Increased stimulation duration with the developed DP system caused less diaphragm fatigue. Conclusion: A modular, inexpensive and reliable DP was successfully developed. Its effectiveness was confirmed in animal experiments. Significance: This study is useful for design of future implantable diaphragmatic pacemakers for improving diaphragm fatigue and convenient assessment of respiratory activity in experiments.

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.

Validation of the flow index to detect low inspiratory effort during pressure support ventilation

Background

Bedside assessment of low levels of inspiratory effort, which are probably insufficient to prevent muscle atrophy, is challenging. The flow index, which is derived from the analysis of the inspiratory portion of the flow–time waveform, has been recently introduced as a non-invasive parameter to evaluate the inspiratory effort. The primary objective of the present study was to provide an external validation of the flow index to detect low inspiratory effort.

Methods

Datasets containing flow, airway pressure, and esophageal pressure (P_es)–time waveforms were obtained from a previously published study in 100 acute brain-injured patients undergoing pressure support ventilation. Waveforms data were analyzed offline. A low inspiratory effort was defined by one of the following criteria, work of breathing (WOB) less than 0.3 J/L, P_es–time product (PTP_es) per minute less than 50 cmH₂O•s/min, or inspiratory muscle pressure (P_mus) less than 5 cmH₂O, adding “or occurrence of ineffective effort more than 10%” for all criteria. The flow index was calculated according to previously reported method. The association of flow index with P_es-derived parameters of effort was investigated. The diagnostic accuracy of the flow index to detect low effort was analyzed.

Results

Moderate correlations were found between flow index and WOB, P_mus, and PTP_es per breath and per minute (Pearson’s correlation coefficients ranged from 0.546 to 0.634, P < 0.001). The incidence of low inspiratory effort was 62%, 51%, and 55% using the definition of WOB, PTP_es per minute, and P_mus, respectively. The area under the receiver operating characteristic curve for flow index to diagnose low effort was 0.88, 0.81, and 0.88, for the three respective definition. By using the cutoff value of flow index less than 2.1, the diagnostic performance for the three definitions showed sensitivity of 0.95–0.96, specificity of 0.57–0.71, positive predictive value of 0.70–0.84, and negative predictive value of 0.90–0.93.

Conclusions

The flow index is associated with P_es-based inspiratory effort measurements. Flow index can be used as a valid instrument to screen low inspiratory effort with a high probability to exclude cases without the condition.

Respiratory drive, inspiratory effort, and work of breathing: review of definitions and non-invasive monitoring tools for intensive care ventilators during pandemic times

Technological advances in mechanical ventilation have been essential to increasing the survival rate in intensive care units. Usually, patients needing mechanical ventilation use controlled ventilation to override the patient’s respiratory muscles and favor lung protection. Weaning from mechanical ventilation implies a transition towards spontaneous breathing, mainly using assisted mechanical ventilation. In this transition, the challenge for clinicians is to avoid under and over assistance and minimize excessive respiratory effort and iatrogenic diaphragmatic and lung damage. Esophageal balloon monitoring allows objective measurements of respiratory muscle activity in real time, but there are still limitations to its routine application in intensive care unit patients using mechanical ventilation. Like the esophageal balloon, respiratory muscle electromyography and diaphragmatic ultrasound are minimally invasive tools requiring specific training that monitor respiratory muscle activity. Particularly during the coronavirus disease pandemic, non invasive tools available on mechanical ventilators to monitor respiratory drive, inspiratory effort, and work of breathing have been extended to individualize mechanical ventilation based on patient’s needs. This review aims to identify the conceptual definitions of respiratory drive, inspiratory effort, and work of breathing and to identify non invasive maneuvers available on intensive care ventilators to measure these parameters. The literature highlights that although respiratory drive, inspiratory effort, and work of breathing are intuitive concepts, even distinguished authors disagree on their definitions.

Flow Index accurately identifies breaths with low or high inspiratory effort during pressure support ventilation

Background

Flow Index, a numerical expression of the shape of the inspiratory flow-time waveform recorded during pressure support ventilation, is associated with patient inspiratory effort. The aim of this study was to assess the accuracy of Flow Index in detecting high or low inspiratory effort during pressure support ventilation and to establish cutoff values for the Flow index to identify these conditions. The secondary aim was to compare the performance of Flow index,of breathing pattern parameters and of airway occlusion pressure (P_0.1) in detecting high or low inspiratory effort during pressure support ventilation.

Methods

Data from 24 subjects was included in the analysis, accounting for a total of 702 breaths. Breaths with high inspiratory effort were defined by a pressure developed by inspiratory muscles (P_musc) greater than 10 cmH₂O while breaths with low inspiratory effort were defined by a P_musc lower than 5 cmH₂O. The areas under the receiver operating characteristic curves of Flow Index and respiratory rate, tidal volume,respiratory rate over tidal volume and P_0.1 were analyzed and compared to identify breaths with low or high inspiratory effort.

Results

P_musc, P_0.1, Pressure Time Product and Flow Index differed between breaths with high, low and intermediate inspiratory effort, while RR, RR/V_T and V_T/kg of IBW did not differ in a statistically significant way. A Flow index higher than 4.5 identified breaths with high inspiratory effort [AUC 0.89 (CI 95% 0.85–0.93)], a Flow Index lower than 2.6 identified breaths with low inspiratory effort [AUC 0.80 (CI 95% 0.76–0.83)].

Conclusions

Flow Index is accurate in detecting high and low spontaneous inspiratory effort during pressure support ventilation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13054-021-03855-4.