Articles: mechanical-ventilation.
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During the COVID-19 pandemic, a need for innovative, inexpensive, and simple ventilator devices for mass use has emerged. The Oxylator (CPR Medical Devices, Markham, Ontario, Canada) is an FDA-approved, fist-size, portable ventilation device developed for out-of-hospital emergency ventilation. It has not been tested in conditions of severe lung injury or with added PEEP. We aimed to assess the performance and reliability of the device in simulated and experimental conditions of severe lung injury, and to derive monitoring methods to allow the delivery of safe, individualized ventilation during situations of surge. ⋯ The Oxylator is a simple device that delivered stable ventilation with tidal volumes within a clinically acceptable range in bench and porcine lung models with low compliance. External monitoring of respiratory timing is advisable, allowing tidal volume estimation and recognition of changes in respiratory mechanics. The device can be an efficient, low-cost, and practical rescue solution for providing short-term ventilatory support as a temporary bridge, but it requires a caregiver at the bedside.
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High-flow nasal cannula (HFNC) is an option for respiratory support in patients with acute hypoxic respiratory failure. To improve patient outcomes, reduce ICU-associated costs, and ease ICU bed availability, a multi-phased, comprehensive strategy was implemented to make HFNC available outside the ICU under the supervision of pulmonology or trauma providers in cooperation with a dedicated respiratory therapy team. The purpose of this study was to describe the education and implementation process for initiating HFNC therapy outside the ICU and to convey key patient demographics and outcomes from the implementation period. ⋯ A comprehensive implementation process and a robust therapy protocol were integral to initiating and managing HFNC in all hospital locations. Study findings indicate that patients with acute hypoxic respiratory failure can safely receive HFNC therapy outside the ICU with appropriate patient selection and staff education.
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Review Meta Analysis
Reducing the dose of neuromuscular blocking agents with adjuncts: a systematic review and meta-analysis.
Acute global shortages of neuromuscular blocking agents (NMBA) threaten to impact adversely on perioperative and critical care. The use of pharmacological adjuncts may reduce NMBA dose. However, the magnitude of any putative effects remains unclear. ⋯ PROSPERO: CRD42020183969.
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Observational Study
Influence of ventilatory strategies on outcomes and length of hospital stay: assist-control and synchronized intermittent mandatory ventilation modes.
The use of synchronized intermittent mandatory ventilation with pressure support ventilation (SIMV + PSV) mode has been discontinued. This study analyzed the association between medical outcomes related to the use of assist-control (A/C) and SIMV + PSV in an intensive care unit. In this observational and retrospective study, modes of ventilation and medical data were collected from electronic medical records for three consecutive years and were related to medical outcomes (mortality), duration of mechanical ventilation, length of hospital stay and the need for tracheostomy. ⋯ Of the participants, 151/345 (43.77%) were on SIMV + PSV and 194/345 (56.23%) were on A/C. The comparative analysis between the modes of ventilation showed no significant differences in length of hospital stay (p = 0.675), duration of mechanical ventilation (p = 0.952), mortality (p = 0.241), failed extubation (p = 0.411) and the need for tracheostomy (p = 0.301). SIMV + PSV as a mode of ventilation showed similar statistical results to the A/C mode, when compared to analyzed medical outcomes.
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Observational Study
Clinically applicable approach for predicting mechanical ventilation in patients with COVID-19.
Patients with coronavirus disease 2019 (COVID-19) requiring mechanical ventilation have high mortality and resource utilisation. The ability to predict which patients may require mechanical ventilation allows increased acuity of care and targeted interventions to potentially mitigate deterioration. ⋯ Machine learning techniques can be leveraged to improve the ability to predict which patients with COVID-19 are likely to require mechanical ventilation, identifying unrecognised bellwethers and providing insight into the constellation of accompanying signs of respiratory failure in COVID-19.