Articles: mechanical-ventilation.
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This article examines successful management of an anesthesia machine failure with the Draeger (or Dräger) Apollo (Draeger Inc) anesthesia workstation. Approximately 45 minutes into the case, while the patient was under general anesthesia and mechanical ventilation, the anesthesia machine failed to achieve positive pressurization following a high-pressure alarm. Despite multiple maneuvers, the issue did not resolve until the machine was manually powered off and on at the main power switch. This case report emphasizes the importance of always having a backup means of patient ventilation and anesthesia administration.
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Clinical alarms, including those for mechanical ventilation, have been one of the leading causes of health technology hazards. It has been reported that < 15% of alarms studied rose to the level of being clinically relevant or actionable. Most alarms in health care, whether by default or intention, are set to a hypothetical average patient, which is essentially a one size fits most approach. ⋯ Observations of human response to stimuli suggest that response to alarms is closely matched to the perceived reliability and value of the alarm system. This paper provides a review examining vulnerabilities in the current management of mechanical ventilation alarms and summarizes best practices identified to help prevent patient injury. This review examines the factors that affect alarm utility and provides recommendations for applying research findings to improve safety for patients, clinician efficiency, and clinician well-being.
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Mechanical ventilation is an indispensable form of life support for patients undergoing general anesthesia or experiencing respiratory failure in the setting of critical illness. These patients are at risk for a number of complications related to both their underlying disease states and the mechanical ventilation itself. Intensive monitoring is required to identify early signs of clinical worsening and to minimize the risk of iatrogenic harm. ⋯ Assessments of driving pressure, transpulmonary pressure, and the pressure-volume loop are performed to ensure that adequate PEEP is applied and excess distending pressure is minimized. Finally, monitoring and frequent adjustment of airway cuff pressures is performed to minimize the risk of airway injury and ventilator-associated pneumonia. We will discuss monitoring during mechanical ventilation with a focus on the accuracy, ease of use, and effectiveness in preventing harm for each of these monitoring modalities.
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Machine learning (ML) is a discipline of computer science in which statistical methods are applied to data in order to classify, predict, or optimize, based on previously observed data. Pulmonary and critical care medicine have seen a surge in the application of this methodology, potentially delivering improvements in our ability to diagnose, treat, and better understand a multitude of disease states. Here we review the literature and provide a detailed overview of the recent advances in ML as applied to these areas of medicine. In addition, we discuss both the significant benefits of this work as well as the challenges in the implementation and acceptance of this non-traditional methodology for clinical purposes.
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Pediatric pulmonology · Jun 2020
Observational StudyAssessment of sidestream end-tidal capnography in ventilated infants on the neonatal unit.
Continuous monitoring of carbon dioxide (CO2 ) levels can be achieved by capnography. Our aims were to compare the performance of a sidestream capnograph with a low dead space and sampling rate to a mainstream device and evaluate whether its results correlated with arterial/capillary CO2 levels in infants with different respiratory disease severities. ⋯ The sidestream capnography performed similarly to the mainstream capnography. The poorer correlation of EtCO2 to PCO2 levels in infants with severe respiratory disease should highlight to clinicians increased ventilation-perfusion mismatch.