Journal ArticleDOI
Patient-ventilator asynchrony during assisted mechanical ventilation
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TLDR
One-fourth of patients exhibit a high incidence of asynchrony during assisted ventilation, which is associated with a prolonged duration of mechanical ventilation and with excessive levels of ventilatory support.Abstract:
Objective
The incidence, pathophysiology, and consequences of patient-ventilator asynchrony are poorly known. We assessed the incidence of patient-ventilator asynchrony during assisted mechanical ventilation and we identified associated factors.read more
Citations
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Journal ArticleDOI
A Novel Method to Evaluate Patient-Ventilator Synchrony during Mechanical Ventilation
Liming Hao,Shuai Ren,Yan Shi,Na Wang,Yixuan Wang,Zujin Luo,Fei Xie,Meng Xu,Jian Zhang,Maolin Cai +9 more
TL;DR: A novel synchrony index is established to evaluate the patient-ventilator synchrony which solves the defects of previous evaluation indexes and can be used as the response parameter in the future research of ventilator control algorithms.
Journal ArticleDOI
Intubation rate, duration of noninvasive ventilation and mortality after noninvasive neurally adjusted ventilatory assist (NIV‐NAVA)
Kristina Kock Hansen,Hanne Irene Jensen,Torben Steensgaard Andersen,Christian Fynbo Christiansen +3 more
TL;DR: Neurally adjusted ventilatory assist has shown to improve patient‐ventilator interaction, but it is unknown whether NIV‐NAVA improves outcomes compared to noninvasive pressure support (NIV‐PS).
Journal ArticleDOI
Reconstructing asynchrony for mechanical ventilation using a hysteresis loop virtual patient model
Cong Zhou,J. Geoffrey Chase,Qianhui Sun,Jennifer L. Knopp,Merryn H. Tawhai,Thomas Desaive,Knut Möller,Geoffrey M. Shaw,Yeong Shiong Chiew,Balázs Benyó +9 more
TL;DR: In this paper , patient-specific lung elastance over a pressure-volume (PV) loop, identified using hysteresis loop analysis (HLA), is used to detect the occurrence of asynchrony and identify its type and pattern.
Dissertation
Contributions to Statistical Signal Processing with Applications in Biomedical Engineering
TL;DR: This PhD thesis investigates the detection of AutoPEEP, a common ventilatory abnormality during mechanical ventilation, and proposes an extension of RDT in the sequential decision framework, namely Sequential RDT.
Journal ArticleDOI
Patient–Ventilator Dyssynchrony in Critically Ill Patients
Bruno De Oliveira,Nahla Aljaberi,Ahmed Taha,Baraa Abduljawad,Fadi Hamed,Nadeem Rahman,Jihad Mallat +6 more
TL;DR: In this article, the authors define different types of dyssynchrony and discuss the evidence for their relationship with patient outcomes and address their potential management, including trigger dyssynchronous, ineffective efforts, autotriggering, double triggering, and flow dyssync.
References
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