Articles: mechanical-ventilation.
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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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Intensive care medicine · Jun 2020
Review Meta AnalysisDiagnosis of ventilator-associated pneumonia in critically ill adult patients-a systematic review and meta-analysis.
The accuracy of the signs and tests that clinicians use to diagnose ventilator-associated pneumonia (VAP) and initiate antibiotic treatment has not been well characterized. We sought to characterize and compare the accuracy of physical examination, chest radiography, endotracheal aspirate (ETA), bronchoscopic sampling cultures (protected specimen brush [PSB] and bronchoalveolar lavage [BAL]), and CPIS > 6 to diagnose VAP. We searched six databases from inception through September 2019 and selected English-language studies investigating accuracy of any of the above tests for VAP diagnosis. ⋯ CPIS > 6 had a sensitivity of 73.8% (95% CI 50.6-88.5) and specificity of 66.4% (95% CI 43.9-83.3). Classic clinical indicators had poor accuracy for diagnosis of VAP. Reliance upon these indicators in isolation may result in misdiagnosis and potentially unnecessary antimicrobial use.
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Ventilation strategies aiming at prevention of ventilator-induced lung injury (VILI), including low tidal volumes (VT) and use of positive end-expiratory pressures (PEEP) are increasingly used in critically ill patients. It is uncertain whether ventilation practices changed in a similar way in burn patients. Our objective was to describe applied ventilator settings and their relation to development of VILI in burn patients. ⋯ This systematic review shows noticeable trends of ventilatory management in burn patients that mirrors those in critically ill non-burn patients. Variability in available ventilator data precluded us from drawing firm conclusions on the association between ventilator settings and the occurrence of VILI in burn patients.
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Journal of critical care · Jun 2020
Acute respiratory failure in randomized trials of noninvasive respiratory support: A systematic review of definitions, patient characteristics, and criteria for intubation.
To examine the definitions of acute respiratory failure, the characteristics of recruited patients, and the criteria for intubation used in randomized trials. ⋯ We identified deficiencies in the design and reporting of randomized trials, some of which can be remedied by investigators. We also found that patient characteristics differ by the type of respiratory failure. This knowledge can help clinician identify patients at the right moment to benefit from the tested interventions and investigators in developing criteria for enrollment in future trials.
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Lung volume measurement performed during invasive mechanical ventilation can be used to determine functional residual capacity, changes in end-expiratory lung volume with the application of PEEP, and lung strain. However, many bedside measurements provide useful information without the use of specialized equipment. ⋯ This review will describe techniques to measure lung volumes in the ICU and the relationship between lung strain, stress, and other measurements. This review will also discuss monitoring ventilation distribution at the bedside and the clinical assessment of regional compliance that this technology provides.