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Xia YHW, Victor MH, Morais CCA, Costa ELV, Amato MBP. Esophageal balloon catheter system identification to improve respiratory effort time features and amplitude determination. Physiol Meas 2024; 45:015002. [PMID: 38086063 DOI: 10.1088/1361-6579/ad14aa] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 12/12/2023] [Indexed: 01/11/2024]
Abstract
Objective. Understanding a patient's respiratory effort and mechanics is essential for the provision of individualized care during mechanical ventilation. However, measurement of transpulmonary pressure (the difference between airway and pleural pressures) is not easily performed in practice. While airway pressures are available on most mechanical ventilators, pleural pressures are measured indirectly by an esophageal balloon catheter. In many cases, esophageal pressure readings take other phenomena into account and are not a reliable measure of pleural pressure.Approach.A system identification approach was applied to provide accurate pleural measures from esophageal pressure readings. First, we used a closed pressurized chamber to stimulate an esophageal balloon and model its dynamics. Second, we created a simplified version of an artificial lung and tried the model with different ventilation configurations. For validation, data from 11 patients (five male and six female) were used to estimate respiratory effort profile and patient mechanics.Main results.After correcting the dynamic response of the balloon catheter, the estimates of resistance and compliance and the corresponding respiratory effort waveform were improved when compared with the adjusted quantities in the test bench. The performance of the estimated model was evaluated using the respiratory pause/occlusion maneuver, demonstrating improved agreement between the airway and esophageal pressure waveforms when using the normalized mean squared error metric. Using the corrected muscle pressure waveform, we detected start and peak times 130 ± 50 ms earlier and a peak amplitude 2.04 ± 1.46 cmH2O higher than the corresponding estimates from esophageal catheter readings.Significance.Compensating the acquired measurements with system identification techniques makes the readings more accurate, possibly better portraying the patient's situation for individualization of ventilation therapy.
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Affiliation(s)
- Yu Hao Wang Xia
- Laboratório de Pneumologia LIM-09, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
- Medical Electrical Devices Laboratory (LabMed), Electronics Engineering, Aeronautics Institute of Technology, Sao Jose dos Campos, SP, Brazil
| | - Marcus Henrique Victor
- Laboratório de Pneumologia LIM-09, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
- Medical Electrical Devices Laboratory (LabMed), Electronics Engineering, Aeronautics Institute of Technology, Sao Jose dos Campos, SP, Brazil
| | - Caio César Araújo Morais
- Laboratório de Pneumologia LIM-09, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Eduardo Leite Vieira Costa
- Laboratório de Pneumologia LIM-09, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
| | - Marcelo Britto Passos Amato
- Laboratório de Pneumologia LIM-09, Hospital das Clinicas HCFMUSP, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, SP, Brazil
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2
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Núñez Silveira JM, Gallardo A, García-Valdés P, Ríos F, Rodriguez PO, Felipe Damiani L. Reverse triggering during mechanical ventilation: Diagnosis and clinical implications. Med Intensiva 2023; 47:648-657. [PMID: 37867118 DOI: 10.1016/j.medine.2023.10.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 09/04/2023] [Accepted: 09/04/2023] [Indexed: 10/24/2023]
Abstract
This review addresses the phenomenon of "reverse triggering", an asynchrony that occurs in deeply sedated patients or patients in transition from deep to light sedation. Reverse triggering has been reported to occur in 30-90% of all ventilated patients. The underlying pathophysiological mechanisms remain unclear, but "entrainment" is proposed as one of them. Detecting this asynchrony is crucial, and methods such as visual inspection, esophageal pressure, diaphragmatic ultrasound and automated methods have been used. Reverse triggering may have effects on lung and diaphragm function, probably mediated by the level of breathing effort and eccentric activation of the diaphragm. The optimal management of reverse triggering has not been established, but may include the adjustment of ventilatory parameters as well as of sedation level, and in extreme cases, neuromuscular block. It is important to understand the significance of this condition and its detection, but also to conduct dedicated research to improve its clinical management and potential effects in critically ill patients.
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Affiliation(s)
- Juan M Núñez Silveira
- Servicio de Kinesiología, Hospital Italiano de Buenos Aires, Buenos Aires, Argentina
| | - Adrián Gallardo
- Servicio de Kinesiología, Sanatorio Clínica Modelo de Morón, Morón, Buenos Aires, Argentina
| | - Patricio García-Valdés
- Departamento de Ciencias de la Salud, Carrera de Kinesiología, Facultad de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile; CardioREspirAtory Research Laboratory (CREAR), Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Fernando Ríos
- Casa Hospital San Juan De Dios, Ramos Mejía, Buenos Aires, Argentina
| | - Pablo O Rodriguez
- Unidad de Terapia Intensiva, Centro de Educación Médica e Investigaciones Clínicas (CEMIC), Buenos Aires, Argentina; Instituto Universitario CEMIC (IUC), Buenos Aires, Argentina
| | - L Felipe Damiani
- Departamento de Ciencias de la Salud, Carrera de Kinesiología, Facultad de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile; CardioREspirAtory Research Laboratory (CREAR), Pontificia Universidad Católica de Chile, Santiago, Chile.
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3
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Kolomaznik M, Hanusrichterova J, Mikolka P, Kosutova P, Vatecha M, Zila I, Mokra D, Calkovska A. Efficiency of exogenous surfactant combined with intravenous N-acetylcysteine in two-hit rodent model of ARDS. Respir Physiol Neurobiol 2023; 316:104138. [PMID: 37579929 DOI: 10.1016/j.resp.2023.104138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 08/09/2023] [Accepted: 08/11/2023] [Indexed: 08/16/2023]
Abstract
Accumulation of reactive oxygen species during hyperoxia together with secondary bacteria-induced inflammation leads to lung damage in ventilated critically ill patients. Antioxidant N-acetylcysteine (NAC) in combination with surfactant may improve lung function. We compared the efficacy of NAC combined with surfactant in the double-hit model of lung injury. Bacterial lipopolysaccharide (LPS) instilled intratracheally and hyperoxia were used to induce lung injury in Wistar rats. Animals were mechanically ventilated and treated intravenously with NAC alone or in combination with intratracheal surfactant (poractant alfa; PSUR+NAC). Control received saline. Lung functions, inflammatory markers, oxidative damage, total white blood cell (WBC) count and lung oedema were evaluated during 4 hrs. Administration of NAC increased total antioxidant capacity (TAC) and decreased IL-6. This effect was potentiated by the combined administration of surfactant and NAC. In addition, PSUR+NAC reduced the levels of TNFα, IL-1ß, and TAC compared to NAC only and improved lung injury score. The combination of exogenous surfactant with NAC suppresses lung inflammation and oxidative stress in the experimental double-hit model of lung injury.
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Affiliation(s)
- Maros Kolomaznik
- Biomedical Centre Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Mala hora 4C, 036 01 Martin, Slovakia
| | - Juliana Hanusrichterova
- Biomedical Centre Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Mala hora 4C, 036 01 Martin, Slovakia
| | - Pavol Mikolka
- Department of Physiology, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Mala hora 4C, 036 01 Martin, Slovakia
| | - Petra Kosutova
- Biomedical Centre Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Mala hora 4C, 036 01 Martin, Slovakia
| | - Martin Vatecha
- Department of Physiology, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Mala hora 4C, 036 01 Martin, Slovakia
| | - Ivan Zila
- Department of Physiology, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Mala hora 4C, 036 01 Martin, Slovakia
| | - Daniela Mokra
- Department of Physiology, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Mala hora 4C, 036 01 Martin, Slovakia
| | - Andrea Calkovska
- Department of Physiology, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Mala hora 4C, 036 01 Martin, Slovakia.
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Longhini F, Simonte R, Vaschetto R, Navalesi P, Cammarota G. Reverse Triggered Breath during Pressure Support Ventilation and Neurally Adjusted Ventilatory Assist at Increasing Propofol Infusion. J Clin Med 2023; 12:4857. [PMID: 37510970 PMCID: PMC10381884 DOI: 10.3390/jcm12144857] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 07/18/2023] [Accepted: 07/22/2023] [Indexed: 07/30/2023] Open
Abstract
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.
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Affiliation(s)
- Federico Longhini
- Anesthesia and Intensive Care, Department of Medical and Surgical Sciences, "Magna Graecia" University, 88100 Catanzaro, Italy
| | - Rachele Simonte
- Division of Anesthesia, Analgesia and Intensive Care, Department of Medicine and Surgery, Hospital S. Maria della Misericordia, University of Perugia, 06123 Perugia, Italy
| | - Rosanna Vaschetto
- Anesthesia and Intensive Care, Department of Translational Medicine, Eastern Piedmont University, 28100 Novara, Italy
| | - Paolo Navalesi
- Anesthesia and Intensive Care, Padua Hospital, Department of Medicine-DIMED, University of Padua, 35128 Padova, Italy
| | - Gianmaria Cammarota
- Anesthesia and Intensive Care, Department of Translational Medicine, Eastern Piedmont University, 28100 Novara, Italy
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Jonkman AH, Telias I, Spinelli E, Akoumianaki E, Piquilloud L. The oesophageal balloon for respiratory monitoring in ventilated patients: updated clinical review and practical aspects. Eur Respir Rev 2023; 32:220186. [PMID: 37197768 PMCID: PMC10189643 DOI: 10.1183/16000617.0186-2022] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 02/22/2023] [Indexed: 05/19/2023] Open
Abstract
There is a well-recognised importance for personalising mechanical ventilation settings to protect the lungs and the diaphragm for each individual patient. Measurement of oesophageal pressure (P oes) as an estimate of pleural pressure allows assessment of partitioned respiratory mechanics and quantification of lung stress, which helps our understanding of the patient's respiratory physiology and could guide individualisation of ventilator settings. Oesophageal manometry also allows breathing effort quantification, which could contribute to improving settings during assisted ventilation and mechanical ventilation weaning. In parallel with technological improvements, P oes monitoring is now available for daily clinical practice. This review provides a fundamental understanding of the relevant physiological concepts that can be assessed using P oes measurements, both during spontaneous breathing and mechanical ventilation. We also present a practical approach for implementing oesophageal manometry at the bedside. While more clinical data are awaited to confirm the benefits of P oes-guided mechanical ventilation and to determine optimal targets under different conditions, we discuss potential practical approaches, including positive end-expiratory pressure setting in controlled ventilation and assessment of inspiratory effort during assisted modes.
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Affiliation(s)
- Annemijn H Jonkman
- Department of Intensive Care Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Irene Telias
- Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, ON, Canada
- Division of Respirology, Department of Medicine, University Health Network and Mount Sinai Hospital, Toronto, ON, Canada
- Keenan Research Centre for Biomedical Science, Li Ka Shing Knowledge Institute, St Michael's Hospital-Unity Health Toronto, Toronto, ON, Canada
| | - Elena Spinelli
- Dipartimento di Anestesia, Rianimazione ed Emergenza-Urgenza, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Evangelia Akoumianaki
- Adult Intensive Care Unit, University Hospital of Heraklion, Heraklion, Greece
- Medical School, University of Crete, Heraklion, Greece
| | - Lise Piquilloud
- Adult Intensive Care Unit, Lausanne University Hospital and Lausanne University, Lausanne, Switzerland
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6
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Rodrigues A, Telias I, Damiani LF, Brochard L. Reverse Triggering during Controlled Ventilation: From Physiology to Clinical Management. Am J Respir Crit Care Med 2023; 207:533-543. [PMID: 36470240 DOI: 10.1164/rccm.202208-1477ci] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Reverse triggering dyssynchrony is a frequent phenomenon recently recognized in sedated critically ill patients under controlled ventilation. It occurs in at least 30-55% of these patients and often occurs in the transition from fully passive to assisted mechanical ventilation. During reverse triggering, patient inspiratory efforts start after the passive insufflation by mechanical breaths. The most often referred mechanism is the entrainment of the patient's intrinsic respiratory rhythm from the brainstem respiratory centers to periodic mechanical insufflations from the ventilator. However, reverse triggering might also occur because of local reflexes without involving the respiratory rhythm generator in the brainstem. Reverse triggering is observed during the acute phase of the disease, when patients may be susceptible to potential deleterious consequences of injurious or asynchronous efforts. Diagnosing reverse triggering might be challenging and can easily be missed. Inspection of ventilator waveforms or more sophisticated methods, such as the electrical activity of the diaphragm or esophageal pressure, can be used for diagnosis. The occurrence of reverse triggering might have clinical consequences. On the basis of physiological data, reverse triggering might be beneficial or injurious for the diaphragm and the lung, depending on the magnitude of the inspiratory effort. Reverse triggering can cause breath-stacking and loss of protective lung ventilation when triggering a second cycle. Little is known about how to manage patients with reverse triggering; however, available evidence can guide management on the basis of physiological principles.
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Affiliation(s)
- Antenor Rodrigues
- Keenan Centre for Biomedical Research, Li Ka Shing Knowledge Institute, Unity Health Toronto, Toronto, Ontario, Canada
| | - Irene Telias
- Keenan Centre for Biomedical Research, Li Ka Shing Knowledge Institute, Unity Health Toronto, Toronto, Ontario, Canada.,Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Ontario, Canada.,Division of Respirology, Department of Medicine, University Health Network and Sinai Health System, Toronto, Ontario, Canada; and
| | - L Felipe Damiani
- Departamento Ciencias de la Salud, Carrera de Kinesiología, Facultad de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Laurent Brochard
- Keenan Centre for Biomedical Research, Li Ka Shing Knowledge Institute, Unity Health Toronto, Toronto, Ontario, Canada.,Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Ontario, Canada
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Murray B, Sikora A, Mock JR, Devlin T, Keats K, Powell R, Bice T. Reverse Triggering: An Introduction to Diagnosis, Management, and Pharmacologic Implications. Front Pharmacol 2022; 13:879011. [PMID: 35814233 PMCID: PMC9256988 DOI: 10.3389/fphar.2022.879011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Accepted: 06/02/2022] [Indexed: 11/13/2022] Open
Abstract
Reverse triggering is an underdiagnosed form of patient-ventilator asynchrony in which a passive ventilator-delivered breath triggers a neural response resulting in involuntary patient effort and diaphragmatic contraction. Reverse triggering may significantly impact patient outcomes, and the unique physiology underscores critical potential implications for drug-device-patient interactions. The purpose of this review is to summarize what is known of reverse triggering and its pharmacotherapeutic consequences, with a particular focus on describing reported cases, physiology, historical context, epidemiology, and management. The PubMed database was searched for publications that reported patients presenting with reverse triggering. The current body of evidence suggests that deep sedation may predispose patients to episodes of reverse triggering; as such, providers may consider decreasing sedation or modifying ventilator settings in patients exhibiting ventilator asynchrony as an initial measure. Increased clinician awareness and research focus are necessary to understand appropriate management of reverse triggering and its association with patient outcomes.
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Affiliation(s)
- Brian Murray
- University of North Carolina Hospitals, Chapel Hill, NC, United States
| | - Andrea Sikora
- College of Pharmacy, University of Georgia, Athens, GA, United States
- *Correspondence: Andrea Sikora,
| | - Jason R. Mock
- University of North Carolina Hospitals, Chapel Hill, NC, United States
| | - Thomas Devlin
- University of North Carolina Hospitals, Chapel Hill, NC, United States
| | - Kelli Keats
- Augusta University Medical Center, Augusta, GA, United States
| | - Rebecca Powell
- College of Pharmacy, University of Georgia, Athens, GA, United States
| | - Thomas Bice
- Novant Health, Winston-Salem, NC, United States
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Abstract
This paper provides a review of a selection of papers published in the Journal of Clinical Monitoring and Computing in 2020 and 2021 highlighting what is new within the field of respiratory monitoring. Selected papers cover work in pulse oximetry monitoring, acoustic monitoring, respiratory system mechanics, monitoring during surgery, electrical impedance tomography, respiratory rate monitoring, lung ultrasound and detection of patient-ventilator asynchrony.
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Karageorgos V, Proklou A, Vaporidi K. Lung and diaphragm protective ventilation: a synthesis of recent data. Expert Rev Respir Med 2022; 16:375-390. [PMID: 35354361 DOI: 10.1080/17476348.2022.2060824] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
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.
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Affiliation(s)
- Vlasios Karageorgos
- Department of Intensive Care, University Hospital of Heraklion and University of Crete Medical School, Greece
| | - Athanasia Proklou
- Department of Intensive Care, University Hospital of Heraklion and University of Crete Medical School, Greece
| | - Katerina Vaporidi
- Department of Intensive Care, University Hospital of Heraklion and University of Crete Medical School, Greece
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Zhou C, Chase JG, Sun Q, Knopp J, Tawhai MH, Desaive T, Möller K, Shaw GM, Chiew YS, Benyo B. Reconstructing asynchrony for mechanical ventilation using a hysteresis loop virtual patient model. Biomed Eng Online 2022; 21:16. [PMID: 35255922 PMCID: PMC8900099 DOI: 10.1186/s12938-022-00986-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Accepted: 02/21/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Patient-specific lung mechanics during mechanical ventilation (MV) can be identified from measured waveforms of fully ventilated, sedated patients. However, asynchrony due to spontaneous breathing (SB) effort can be common, altering these waveforms and reducing the accuracy of identified, model-based, and patient-specific lung mechanics. METHODS Changes in patient-specific lung elastance over a pressure-volume (PV) loop, identified using hysteresis loop analysis (HLA), are used to detect the occurrence of asynchrony and identify its type and pattern. The identified HLA parameters are then combined with a nonlinear mechanics hysteresis loop model (HLM) to extract and reconstruct ventilated waveforms unaffected by asynchronous breaths. Asynchrony magnitude can then be quantified using an energy-dissipation metric, Easyn, comparing PV loop area between model-reconstructed and original, altered asynchronous breathing cycles. Performance is evaluated using both test-lung experimental data with a known ground truth and clinical data from four patients with varying levels of asynchrony. RESULTS Root mean square errors for reconstructed PV loops are within 5% for test-lung experimental data, and 10% for over 90% of clinical data. Easyn clearly matches known asynchrony magnitude for experimental data with RMS errors < 4.1%. Clinical data performance shows 57% breaths having Easyn > 50% for Patient 1 and 13% for Patient 2. Patient 3 only presents 20% breaths with Easyn > 10%. Patient 4 has Easyn = 0 for 96% breaths showing accuracy in a case without asynchrony. CONCLUSIONS Experimental test-lung validation demonstrates the method's reconstruction accuracy and generality in controlled scenarios. Clinical validation matches direct observations of asynchrony in incidence and quantifies magnitude, including cases without asynchrony, validating its robustness and potential efficacy as a clinical real-time asynchrony monitoring tool.
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Affiliation(s)
- Cong Zhou
- School of Civil Aviation & Yangtze River Delta Research Institute, Northwestern Polytechnical University, Xian, China
- Dept of Mechanical Engineering, Centre for Bio-Engineering, University of Canterbury, Christchurch, New Zealand
| | - J. Geoffrey Chase
- Dept of Mechanical Engineering, Centre for Bio-Engineering, University of Canterbury, Christchurch, New Zealand
| | - Qianhui Sun
- Dept of Mechanical Engineering, Centre for Bio-Engineering, University of Canterbury, Christchurch, New Zealand
| | - Jennifer Knopp
- Dept of Mechanical Engineering, Centre for Bio-Engineering, University of Canterbury, Christchurch, New Zealand
| | - Merryn H. Tawhai
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
| | - Thomas Desaive
- GIGA-In Silico Medicine, Institute of Physics, University of Liege, Liege, Belgium
| | - Knut Möller
- Institute for Technical Medicine, Furtwangen University, Villingen-Schwenningen, Germany
| | - Geoffrey M. Shaw
- Dept of Intensive Care, Christchurch Hospital, Christchurch, New Zealand
| | | | - Balazs Benyo
- Dept of Control Engineering and Information Technology, Budapest University of Technology and Economics, Budapest, Hungary
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11
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Accuracy of Algorithms and Visual Inspection for Detection of Trigger Asynchrony in Critical Patients : A Systematic Review. Crit Care Res Pract 2021; 2021:6942497. [PMID: 34621546 PMCID: PMC8492248 DOI: 10.1155/2021/6942497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 09/04/2021] [Indexed: 11/29/2022] Open
Abstract
Objective This study aimed to summarize the accuracy of the different methods for detecting trigger asynchrony at the bedside in mechanically ventilated patients. Method A systematic review was conducted from 1990 to 2020 in PubMed, Lilacs, Scopus, and ScienceDirect databases. The reference list of the identified studies, reviews, and meta-analyses was also manually searched for relevant studies. The reference standards were esophageal pressure catheter and/or electrical activity of the diaphragm. Studies were assessed following the QUADAS-2 recommendations, while the review was prepared according to the PRISMA criteria. Results One thousand one hundred and eleven studies were selected, and four were eligible for analysis. Esophageal pressure was the predominant reference standard, while visual inspection and algorithms/software comprised index tests. The trigger asynchrony, ineffective expiratory effort, double triggering, and reverse triggering were analyzed. Sensitivity and specificity ranged from 65.2% to 99% and 80% to 100%, respectively. Positive predictive values reached 80.3 to 100%, while the negative predictive values reached 92 to 100%. Accuracy could not be calculated for most studies. Conclusion Algorithms/software validated directly or indirectly using reference standards present high sensitivity and specificity, with a diagnostic power similar to visual inspection of experts.
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12
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Pham T, Montanya J, Telias I, Piraino T, Magrans R, Coudroy R, Damiani LF, Mellado Artigas R, Madorno M, Blanch L, Brochard L. Automated detection and quantification of reverse triggering effort under mechanical ventilation. Crit Care 2021; 25:60. [PMID: 33588912 PMCID: PMC7883535 DOI: 10.1186/s13054-020-03387-3] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Accepted: 11/12/2020] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Reverse triggering (RT) is a dyssynchrony defined by a respiratory muscle contraction following a passive mechanical insufflation. It is potentially harmful for the lung and the diaphragm, but its detection is challenging. Magnitude of effort generated by RT is currently unknown. Our objective was to validate supervised methods for automatic detection of RT using only airway pressure (Paw) and flow. A secondary objective was to describe the magnitude of the efforts generated during RT. METHODS We developed algorithms for detection of RT using Paw and flow waveforms. Experts having Paw, flow and esophageal pressure (Pes) assessed automatic detection accuracy by comparison against visual assessment. Muscular pressure (Pmus) was measured from Pes during RT, triggered breaths and ineffective efforts. RESULTS Tracings from 20 hypoxemic patients were used (mean age 65 ± 12 years, 65% male, ICU survival 75%). RT was present in 24% of the breaths ranging from 0 (patients paralyzed or in pressure support ventilation) to 93.3%. Automatic detection accuracy was 95.5%: sensitivity 83.1%, specificity 99.4%, positive predictive value 97.6%, negative predictive value 95.0% and kappa index of 0.87. Pmus of RT ranged from 1.3 to 36.8 cmH20, with a median of 8.7 cmH20. RT with breath stacking had the highest levels of Pmus, and RTs with no breath stacking were of similar magnitude than pressure support breaths. CONCLUSION An automated detection tool using airway pressure and flow can diagnose reverse triggering with excellent accuracy. RT generates a median Pmus of 9 cmH2O with important variability between and within patients. TRIAL REGISTRATION BEARDS, NCT03447288.
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Affiliation(s)
- Tài Pham
- Keenan Research Centre for Biomedical Science, Li Ka Shing Knowledge Institute, St. Michael's Hospital, 30 Bond St, Toronto, ON, M5B 1W8, Canada. .,Interdepartmental Division of Critical Care Medicine, University of Toronto, 209 Victoria St, Toronto, ON, M5B 1T8, Canada. .,Université Paris-Saclay, AP-HP, Service de médecine intensive-réanimation, Hôpital de Bicêtre, DMU CORREVE, FHU SEPSIS, Groupe de recherche clinique CARMAS, Le Kremlin-Bicêtre, France.
| | | | - Irene Telias
- grid.415502.7Keenan Research Centre for Biomedical Science, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, 30 Bond St, Toronto, ON M5B 1W8 Canada ,grid.17063.330000 0001 2157 2938Interdepartmental Division of Critical Care Medicine, University of Toronto, 209 Victoria St, Toronto, ON M5B 1T8 Canada ,grid.231844.80000 0004 0474 0428Division of Respirology, Department of Medicine, University Health Network, Toronto, Canada ,grid.492573.e0000 0004 6477 6457Sinai Health System, Toronto, Canada
| | - Thomas Piraino
- grid.415502.7St. Michael’s Hospital, Unity Health Toronto, Toronto, Canada ,grid.25073.330000 0004 1936 8227Division of Critical Care, Department of Anesthesia, McMaster University, Hamilton, Canada
| | | | - Rémi Coudroy
- grid.415502.7Keenan Research Centre for Biomedical Science, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, 30 Bond St, Toronto, ON M5B 1W8 Canada ,grid.17063.330000 0001 2157 2938Interdepartmental Division of Critical Care Medicine, University of Toronto, 209 Victoria St, Toronto, ON M5B 1T8 Canada ,grid.411162.10000 0000 9336 4276Médecine Intensive Réanimation, CHU de Poitiers, Poitiers, France ,grid.11166.310000 0001 2160 6368INSERM CIC 1402, Groupe ALIVE, Université de Poitiers, Poitiers, France
| | - L. Felipe Damiani
- grid.415502.7Keenan Research Centre for Biomedical Science, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, 30 Bond St, Toronto, ON M5B 1W8 Canada ,grid.17063.330000 0001 2157 2938Interdepartmental Division of Critical Care Medicine, University of Toronto, 209 Victoria St, Toronto, ON M5B 1T8 Canada ,grid.7870.80000 0001 2157 0406Departamento Ciencias de la Salud, Carrera de Kinesiología, Faculdad de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Ricard Mellado Artigas
- grid.415502.7Keenan Research Centre for Biomedical Science, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, 30 Bond St, Toronto, ON M5B 1W8 Canada ,grid.17063.330000 0001 2157 2938Interdepartmental Division of Critical Care Medicine, University of Toronto, 209 Victoria St, Toronto, ON M5B 1T8 Canada ,grid.410458.c0000 0000 9635 9413Surgical ICU, Department of Anesthesia, Hospital Clínic, Barcelona, Spain
| | - Matías Madorno
- grid.441574.70000000090137393Instituto Tecnológico de Buenos Aires (ITBA), Buenos Aires, Argentina
| | - Lluis Blanch
- grid.7080.f0000 0001 2296 0625Critical Care Center, Hospital Universitari Parc Taulí, Institut D’Investigació I Innovació Parc Taulí I3PT, Universitat Autònoma de Barcelona, Sabadell, Spain ,grid.413448.e0000 0000 9314 1427Biomedical Research Networking Center in Respiratory Disease (CIBERES), Instituto de Salud Carlos III, Madrid, Spain
| | - Laurent Brochard
- grid.415502.7Keenan Research Centre for Biomedical Science, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, 30 Bond St, Toronto, ON M5B 1W8 Canada ,grid.17063.330000 0001 2157 2938Interdepartmental Division of Critical Care Medicine, University of Toronto, 209 Victoria St, Toronto, ON M5B 1T8 Canada
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Rodriguez PO, Tiribelli N, Fredes S, Gogniat E, Plotnikow G, Fernandez Ceballos I, Pratto R, Raimondi A, Guaymas M, Ilutovich S, San Román E, Madorno M, Maskin P, Brochard L, Setten M. Prevalence of Reverse Triggering in Early ARDS: Results From a Multicenter Observational Study. Chest 2020; 159:186-195. [PMID: 32805238 DOI: 10.1016/j.chest.2020.08.018] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Revised: 07/31/2020] [Accepted: 08/03/2020] [Indexed: 10/23/2022] Open
Abstract
BACKGROUND The prevalence of reverse triggering (RT) in the early phase of ARDS is unknown. RESEARCH QUESTION During early ARDS, what is the proportion of patients affected by RT, what are its potential predictors, and what is its association with clinical outcomes? STUDY DESIGN AND METHODS This was prospective, multicenter, and observational study. Patients who met the Berlin definition of ARDS with less than 72 h of mechanical ventilation and had not been paralyzed with neuromuscular blockers were screened. A 30-min recording of respiratory signals was obtained from the patients as soon as they were enrolled, and the number of breaths with RT were counted. RESULTS One hundred patients were included. ARDS was mild to moderate in 92% of them. The recordings were obtained after a median of 1 day (interquartile range, 1-2 days) of ventilation. Fifty patients had RT, and most of these events (97%) were not associated with breath stacking. Detecting RT was associated with lower tidal volume (Vt) and less opiate infusion. The presence of RT was not associated with time to discontinuation of mechanical ventilation (subdistribution hazard ratio, 1.03; 95% CI, 0.6-1.77), but it possibly was associated with a reduced hospital mortality (hazard ratio, 0.65; 95% CI, 0.57-0.73). INTERPRETATION Fifty percent of patients receiving assist-control ventilation for mild or moderate ARDS, sedated and nonparalyzed, demonstrate RT without breath stacking on the first day of mechanical ventilation. RT may be associated with low VTS and opiate doses. TRIAL REGISTRY ClinicalTrials.gov; No.: NCT02732041; URL: www.clinicaltrials.gov.
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Affiliation(s)
- Pablo O Rodriguez
- Intensive Care Unit, Centro de Educación Médica e Investigaciones Clínicas, Ciudad Autónoma de Buenos Aires, Argentina; Pulmonary Medicine School of Medicine, Centro de Educación Médica e Investigaciones Clínicas, Ciudad Autónoma de Buenos Aires, Argentina; Instituto Universitario, Centro de Educación Médica e Investigaciones Clínicas, Ciudad Autónoma de Buenos Aires, Argentina.
| | - Norberto Tiribelli
- Intensive Care Unit, Complejo Médico Churruca Visca, Ciudad Autónoma de Buenos Aires, Argentina
| | - Sebastián Fredes
- Intensive Care Unit, Complejo Médico Churruca Visca, Ciudad Autónoma de Buenos Aires, Argentina; Intensive Care Unit, Sanatorio de la Trinidad Mitre, Ciudad Autónoma de Buenos Aires, Argentina
| | - Emiliano Gogniat
- Intensive Care Unit, Hospital Italiano de Buenos Aires, Ciudad Autónoma de Buenos Aires, Argentina
| | - Gustavo Plotnikow
- Intensive Care Unit, Sanatorio Anchorena, Ciudad Autónoma de Buenos Aires, Argentina
| | | | - Romina Pratto
- Intensive Care Unit, Sanatorio Anchorena, Ciudad Autónoma de Buenos Aires, Argentina
| | - Alejandro Raimondi
- School of Medicine, University of Buenos Aires, Ciudad Autónoma de Buenos Aires, Argentina
| | - María Guaymas
- Intensive Care Unit, Complejo Médico Churruca Visca, Ciudad Autónoma de Buenos Aires, Argentina
| | - Santiago Ilutovich
- Intensive Care Unit, Sanatorio de la Trinidad Mitre, Ciudad Autónoma de Buenos Aires, Argentina
| | - Eduardo San Román
- Intensive Care Unit, Hospital Italiano de Buenos Aires, Ciudad Autónoma de Buenos Aires, Argentina
| | - Matías Madorno
- MBMed SA, Ciudad Autónoma de Buenos Aires, Argentina; Instituto Tecnológico de Buenos Aires, Ciudad Autónoma de Buenos Aires, Argentina
| | - Patricio Maskin
- Intensive Care Unit, Centro de Educación Médica e Investigaciones Clínicas, Ciudad Autónoma de Buenos Aires, Argentina; Pulmonary Medicine School of Medicine, Centro de Educación Médica e Investigaciones Clínicas, Ciudad Autónoma de Buenos Aires, Argentina; Instituto Universitario, Centro de Educación Médica e Investigaciones Clínicas, Ciudad Autónoma de Buenos Aires, Argentina
| | - Laurent Brochard
- Keenan Centre for Biomedical Research, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, Canada; Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, Canada
| | - Mariano Setten
- Intensive Care Unit, Centro de Educación Médica e Investigaciones Clínicas, Ciudad Autónoma de Buenos Aires, Argentina; Universidad del Salvador Medical School, Ciudad Autónoma de Buenos Aires, Argentina
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14
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Ge H, Duan K, Wang J, Jiang L, Zhang L, Zhou Y, Fang L, Heunks LMA, Pan Q, Zhang Z. Risk Factors for Patient-Ventilator Asynchrony and Its Impact on Clinical Outcomes: Analytics Based on Deep Learning Algorithm. Front Med (Lausanne) 2020; 7:597406. [PMID: 33324663 PMCID: PMC7724969 DOI: 10.3389/fmed.2020.597406] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Accepted: 10/16/2020] [Indexed: 02/05/2023] Open
Abstract
Background and objectives: Patient-ventilator asynchronies (PVAs) are common in mechanically ventilated patients. However, the epidemiology of PVAs and its impact on clinical outcome remains controversial. The current study aims to evaluate the epidemiology and risk factors of PVAs and their impact on clinical outcomes using big data analytics. Methods: The study was conducted in a tertiary care hospital; all patients with mechanical ventilation from June to December 2019 were included for analysis. Negative binomial regression and distributed lag non-linear models (DLNM) were used to explore risk factors for PVAs. PVAs were included as a time-varying covariate into Cox regression models to investigate its influence on the hazard of mortality and ventilator-associated events (VAEs). Results: A total of 146 patients involving 50,124 h and 51,451,138 respiratory cycles were analyzed. The overall mortality rate was 15.6%. Double triggering was less likely to occur during day hours (RR: 0.88; 95% CI: 0.85-0.90; p < 0.001) and occurred most frequently in pressure control ventilation (PCV) mode (median: 3; IQR: 1-9 per hour). Ineffective effort was more likely to occur during day time (RR: 1.09; 95% CI: 1.05-1.13; p < 0.001), and occurred most frequently in PSV mode (median: 8; IQR: 2-29 per hour). The effect of sedatives and analgesics showed temporal patterns in DLNM. PVAs were not associated mortality and VAE in Cox regression models with time-varying covariates. Conclusions: Our study showed that counts of PVAs were significantly influenced by time of the day, ventilation mode, ventilation settings (e.g., tidal volume and plateau pressure), and sedatives and analgesics. However, PVAs were not associated with the hazard of VAE or mortality after adjusting for protective ventilation strategies such as tidal volume, plateau pressure, and positive end expiratory pressure (PEEP).
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Affiliation(s)
- Huiqing Ge
- Department of Respiratory Care, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Regional Medical Center for National Institute of Respiratory Diseases, Bethesda, MD, United States
| | - Kailiang Duan
- Department of Respiratory Care, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Jimei Wang
- Department of Respiratory Care, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Liuqing Jiang
- Department of Respiratory Care, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Lingwei Zhang
- College of Information Engineering, Zhejiang University of Technology, Hangzhou, China
| | - Yuhan Zhou
- College of Information Engineering, Zhejiang University of Technology, Hangzhou, China
| | - Luping Fang
- College of Information Engineering, Zhejiang University of Technology, Hangzhou, China
| | - Leo M. A. Heunks
- Department of Intensive Care Medicine, Amsterdam UMC, Amsterdam, Netherlands
| | - Qing Pan
- College of Information Engineering, Zhejiang University of Technology, Hangzhou, China
- Qing Pan
| | - Zhongheng Zhang
- Department of Emergency Medicine, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
- *Correspondence: Zhongheng Zhang
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