Article
Medicine, General & Internal
Ling Liu, Yue Yu, Xiaoting Xu, Qin Sun, Haibo Qiu, Davide Chiumello, Yi Yang
Summary: The study found that using an automatic adjustment system in pressure support ventilation significantly reduced patient-ventilator asynchrony, mainly through reducing micro-asynchrony.
FRONTIERS IN MEDICINE
(2021)
Article
Critical Care Medicine
Robert G. T. Blokpoel, Johannes G. M. Burgerhof, Dick G. Markhorst, Martin C. J. Kneyber
Summary: The study found that the level of patient-ventilator asynchrony in mechanically ventilated children increased over time, but was not related to patient discomfort and was inversely related to the duration of mechanical ventilation. The prevalence of asynchronous breaths was highest on the day of extubation.
PEDIATRIC CRITICAL CARE MEDICINE
(2021)
Article
Critical Care Medicine
Anne-Fleur Haudebourg, Tommaso Maraffi, Samuel Tuffet, Francois Perier, Nicolas de Prost, Keyvan Razazi, Armand Mekontso Dessap, Guillaume Carteaux
Summary: The study assessed the impact of proportional assist ventilation with load-adjustable gain factors (PAV+) on refractory ineffective triggering during pressure support ventilation. Among patients with ineffective triggering under PSV, 58% had refractory ineffective triggering, which was not eliminated by PSL adjustment. Switching to PAV+ significantly reduced or eliminated the incidence of asynchrony for these patients.
ANNALS OF INTENSIVE CARE
(2021)
Article
Anesthesiology
Francesco Mojoli, Anita Orlando, Isabella Maria Bianchi, Roberta Puce, Eric Arisi, Giulia Salve, Giuseppe Maggio, Silvia Mongodi, Marco Pozzi
Summary: The study found that automated real-time waveform analysis-guided cycling-off appears to be a reliable solution to improve synchronization in difficult-to-wean patients under pressure support ventilation.
ANAESTHESIA CRITICAL CARE & PAIN MEDICINE
(2022)
Article
Critical Care Medicine
Annemijn H. Jonkman, Minke C. Holleboom, Heder J. de Vries, Marijn Vriends, Pieter R. Tuinman, Leo M. A. Heunks
Summary: This case report describes a previously unrecognized patient-ventilator dyssynchrony called expiratory muscle relaxation-induced ventilator triggering (ERIT). It can be recognized with in-depth respiratory muscle monitoring.
Review
Critical Care Medicine
Michihito Kyo, Tatsutoshi Shimatani, Koji Hosokawa, Shunsuke Taito, Yuki Kataoka, Shinichiro Ohshimo, Nobuaki Shime
Summary: Patient-ventilator asynchrony (PVA) is a common issue in patients undergoing invasive mechanical ventilation (MV) in the intensive care unit (ICU) and may lead to longer MV duration, higher ICU mortality, and higher hospital mortality. Physicians may consider monitoring PVA and adjusting ventilator settings and sedatives to reduce PVA. Further studies are needed to determine the impact of PVA on clinical outcomes.
JOURNAL OF INTENSIVE CARE
(2021)
Article
Engineering, Multidisciplinary
Dingfu Chen, Kangwei Lin, Ziheng Deng, Qingxu Deng
Summary: In this paper, a lightweight network called Mobiformer is proposed for automatic PVA identification, which combines the ability of parameter sharing of convolutional network and the global interaction of self-attention mechanism. The model can dynamically capture the global dependencies and extract local information to accurately detect PVA. Experimental results show that our model can effectively identify PVA and make interpretable decisions.
Article
Computer Science, Interdisciplinary Applications
Tom Bakkes, Anouk van Diepen, Ashley De Bie, Leon Montenij, Francesco Mojoli, Arthur Bouwman, Massimo Mischi, Pierre Woerlee, Simona Turco
Summary: An automatic detection and classification algorithm for patient-ventilator asynchrony (PVA) was developed using a neural network and simulated data. The algorithm achieved over 90% accuracy in detecting and classifying PVAs, providing a tool to optimize mechanical ventilation and monitor ventilation strategies.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2023)
Article
Medicine, General & Internal
Federico Longhini, Rachele Simonte, Rosanna Vaschetto, Paolo Navalesi, Gianmaria Cammarota
Summary: RTB occurs during both pressure support ventilation and neurally adjusted ventilatory assist, and the level of propofol sedation and the mode of ventilation may influence the incidence of RTBs.
JOURNAL OF CLINICAL MEDICINE
(2023)
Article
Critical Care Medicine
Francesco Mojoli, Marco Pozzi, Anita Orlando, Isabella M. Bianchi, Eric Arisi, Giorgio A. Iotti, Antonio Braschi, Laurent Brochard
Summary: This study suggests that respiratory efforts and their timing can be reliably detected during pressure support ventilation using standard ventilator waveforms, providing an opportunity to assess and improve patient-ventilator interaction without the need for special equipment.
Article
Respiratory System
Baozhu Zhang, Zhe Zhang, Haiping Qin, Zhenjie Jiang, Qiuxue Deng, Qingwen Sun, Yingzhi Wang, Jing Zhou, Zhimin Lin, Weiqun He, Dongming Hua, Yuanda Xu
Summary: This study investigates the effects of two different low-level pressure support ventilation protocols on respiratory mechanics in difficult-to-wean patients. The results show that the zero PEEP group is more likely to induce patient-ventilator asynchronies in these patients.
CLINICAL RESPIRATORY JOURNAL
(2023)
Review
Critical Care Medicine
Xueyan Yuan, Xinxing Lu, Yali Chao, Jennifer Beck, Christer Sinderby, Jianfeng Xie, Yi Yang, Haibo Qiu, Ling Liu
Summary: The study suggests that the NAVA mode may improve the rate of weaning success for difficult to wean patients compared with other partial support modes. Additionally, NAVA may reduce the duration of mechanical ventilation, decrease hospital mortality, and prolong ventilator-free days when compared with other modes.
Review
Medicine, General & Internal
Mengfan Wu, Xueyan Yuan, Ling Liu, Yi Yang
Summary: This study conducted a systematic review and meta-analysis to determine the impact of neurally adjusted ventilatory assist (NAVA) compared to conventional mechanical ventilation (CMV) on the outcomes of patients with acute respiratory failure (ARF). The results suggest that NAVA improves patient-ventilator synchronization and important clinical outcomes, including reducing asynchrony index, shortening duration of mechanical ventilation, and decreasing ICU mortality.
FRONTIERS IN MEDICINE
(2022)
Article
Engineering, Biomedical
Dingfu Chen, Kangwei Lin, Ziheng Deng, Dayu Li, Qingxu Deng
Summary: In this study, an attention-based convolutional long short-term memory network was proposed for accurately and automatically detecting patient-ventilator asynchrony (PVA) during mechanical ventilation. Experimental results showed that the algorithm outperformed existing methods in PVA detection, which is beneficial for patient recovery.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2022)
Article
Critical Care Medicine
I. I. Ramirez, R. S. Adasme, D. H. Arellano, A. R. M. Rocha, F. M. D. Andrade, J. Nunez-Silveira, N. A. Montecinos, S. Dias, L. F. Damiani, R. Gutierrez-Arias, B. Lobo-Valbuena, F. Gordo-Vidal
Summary: This study highlights that factors associated with proper recognition and management of patient-ventilator asynchrony (PVA) include specific training programs in mechanical ventilation, completion of courses with more than 100 hours, and the number of ICU beds. The key factor influencing the management of PVA is the correct identification of the number of PVAs.
MEDICINA INTENSIVA
(2021)
Article
Critical Care Medicine
Colin K. Grissom, Eliotte L. Hirshberg, Justin B. Dickerson, Samuel M. Brown, Michael J. Lanspa, Kathleen D. Liu, David Schoenfeld, Mark Tidswell, R. Duncan Hite, Peter Rock, Russell R. Miller, Alan H. Morris
CRITICAL CARE MEDICINE
(2015)
Review
Respiratory System
Jonathan A. Gehlbach, Kyle J. Rehder, Michael A. Gentile, David A. Turner, Daniel J. Grady, Ira M. Cheifetz
EXPERT REVIEW OF RESPIRATORY MEDICINE
(2017)
Letter
Critical Care Medicine
Neil R. MacIntyre, Michael Gentile, John Davies, Stephen Bergin, Craig Rackley, Anne Mathews
INTENSIVE CARE MEDICINE
(2018)
Article
Critical Care Medicine
Andrew G. Miller, Michael A. Gentile, John D. Davies, Neil R. MacIntyre
Letter
Critical Care Medicine
Neil R. MacIntyre, Andrew G. Miller, Michael A. Gentile, John D. Davies
Article
Critical Care Medicine
David A. Turner, David F. Adams, Michael A. Gentile, Lee Williford, George A. Quick, P. Brian Smith, Ira M. Cheifetz
PEDIATRIC CRITICAL CARE MEDICINE
(2012)
Article
Critical Care Medicine
Brian K. Walsh, Michael A. Gentile, Barry M. Grenier
Article
Critical Care Medicine
Michael A. Gentile
Review
Critical Care Medicine
J. Brady Scott, Michael A. Gentile, Stacey N. Bennett, Mary Ann Couture, Neil R. MacIntyre
Article
Critical Care Medicine
Andrew G. Miller, Jhaymie L. Cappiello, Michael A. Gentile, Andrew M. Almond, Janice J. Thalman, Neil R. MacIntyre
Article
Critical Care Medicine
Renee M. Bartle, Andrew G. Miller, Anthony J. Diez, P. Brian Smith, Michael A. Gentile, Mihai Puia-Dumitrescu
Letter
Critical Care Medicine
Roham T. Zamanian, Charles V. Pollack, Michael A. Gentile, Moira Rashid, John Christian Fox, Kenneth W. Mahaffey, Vinicio de Jesus Perez
AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE
(2020)
Article
Critical Care Medicine
Andrew G. Miller, Michael A. Gentile, Joseph P. Coyle
Article
Critical Care Medicine
Carl G. Tams, Neil R. Euliano, A. Daniel Martin, Michael J. Banner, Andrea Gabrielli, Steven Bonnet, Paul J. Stephan, Adam J. Seiver, Michael A. Gentile
JOURNAL OF CRITICAL CARE
(2020)
Editorial Material
Critical Care Medicine
Filip Depta, Marko Zdravkovic, Michael A. Gentile
INTENSIVE CARE MEDICINE EXPERIMENTAL
(2022)