Articles: mechanical-ventilation.
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Journal of critical care · Aug 2024
The value of artificial intelligence for the treatment of mechanically ventilated intensive care unit patients: An early health technology assessment.
The health and economic consequences of artificial intelligence (AI) systems for mechanically ventilated intensive care unit patients often remain unstudied. Early health technology assessments (HTA) can examine the potential impact of AI systems by using available data and simulations. Therefore, we developed a generic health-economic model suitable for early HTA of AI systems for mechanically ventilated patients. ⋯ Using the proposed generic health-economic model, investors and innovators can easily assess whether implementing a certain AI system is likely to be cost-effective before an exact clinical impact is determined. The results of the early HTA can aid investors and innovators in deployment of AI systems by supporting development decisions, informing value-based pricing, clinical trial design, and selection of target patient groups.
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Journal of critical care · Aug 2024
The impact of aggressive and conservative propensity for initiation of neuromuscular blockade in mechanically ventilated patients with hypoxemic respiratory failure.
Neuromuscular blockade (NMB) in ventilated patients may cause benefit or harm. We applied "incremental interventions" to determine the impact of altering NMB initiation aggressiveness. ⋯ Aggressive or conservative initiation of NMB may worsen mortality. In healthier populations, marginally conservative NMB initiation strategies may lead to increased ventilator free days with minimal impact on mortality.
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Endotracheal suctioning causes discomfort, is associated with adverse effects, and is resource-demanding. An artificial secretion removal method, known as an automated cough, has been developed, which applies rapid, automated deflation, and inflation of the endotracheal tube cuff during the inspiratory phase of mechanical ventilation. This method has been evaluated in the hands of researchers but not when used by attending nurses. The aim of this study was to explore the efficacy of the method over the course of patient management as part of routine care. ⋯ This study solely evaluated the efficacy of an automated artificial cough procedure, which illustrated the potential for reducing the need for endotracheal suctioning when applied by attending nurses in routine care.
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Observational Study
Reducing Airway Occlusion Time Without Losing Accuracy to Predict Successful Mechanical Ventilator Liberation During the Measurement of the Timed Inspiratory Effort Index.
In 2013, a new predictor of successful mechanical ventilation liberation named timed inspiratory effort (TIE) index was devised with the normalization of the maximum inspiratory pressure (obtained within 60 s of unidirectional airway occlusion) with the time at which the value was reached. The aim of this study was to verify whether the presence of a sequence of a certain number of inspiratory effort values between 30-60 s > 1.0 cm H2O/s could predict weaning success in a performance comparable to the TIE index. ⋯ The presence of a sequence of ≤ 4 inspiratory efforts > 1.0 cm H2O/s during the TIE index measurement was a reliable predictor of weaning success, which could allow timely interruption of the procedure and entail a substantial reduction in airway occlusion time.
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Practice Guideline
AARC Clinical Practice Guideline: Patient-Ventilator Assessment.
Given the important role of patient-ventilator assessments in ensuring the safety and efficacy of mechanical ventilation, a team of respiratory therapists and a librarian used Grading of Recommendations, Assessment, Development, and Evaluation methodology to make the following recommendations: (1) We recommend assessment of plateau pressure to ensure lung-protective ventilator settings (strong recommendation, high certainty); (2) We recommend an assessment of tidal volume (VT) to ensure lung-protective ventilation (4-8 mL/kg/predicted body weight) (strong recommendation, high certainty); (3) We recommend documenting VT as mL/kg predicted body weight (strong recommendation, high certainty); (4) We recommend an assessment of PEEP and auto-PEEP (strong recommendation, high certainty); (5) We suggest assessing driving pressure to prevent ventilator-induced injury (conditional recommendation, low certainty); (6) We suggest assessing FIO2 to ensure normoxemia (conditional recommendation, very low certainty); (7) We suggest telemonitoring to supplement direct bedside assessment in settings with limited resources (conditional recommendation, low certainty); (8) We suggest direct bedside assessment rather than telemonitoring when resources are adequate (conditional recommendation, low certainty); (9) We suggest assessing adequate humidification for patients receiving noninvasive ventilation (NIV) and invasive mechanical ventilation (conditional recommendation, very low certainty); (10) We suggest assessing the appropriateness of the humidification device during NIV and invasive mechanical ventilation (conditional recommendation, low certainty); (11) We recommend that the skin surrounding artificial airways and NIV interfaces be assessed (strong recommendation, high certainty); (12) We suggest assessing the dressing used for tracheostomy tubes and NIV interfaces (conditional recommendation, low certainty); (13) We recommend assessing the pressure inside the cuff of artificial airways using a manometer (strong recommendation, high certainty); (14) We recommend that continuous cuff pressure assessment should not be implemented to decrease the risk of ventilator-associated pneumonia (strong recommendation, high certainty); and (15) We suggest assessing the proper placement and securement of artificial airways (conditional recommendation, very low certainty).