Chest
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Randomized Controlled Trial Multicenter Study
Smartphone-guided Self-prone Positioning versus Usual Care in Non-Intubated Hospital Ward Patients with COVID-19: A Pragmatic Randomized Clinical Trial.
Safe, effective, and easily implementable treatments that reduce the progression of respiratory failure in COVID-19 are urgently needed. Despite the increased adoption of prone positioning during the pandemic, the effectiveness of this technique on progression of respiratory failure among nonintubated patients is unclear. ⋯ gov.
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Multicenter Study
Predicting Usual Interstitial Pneumonia Histopathology from Chest CT with Deep Learning.
Idiopathic pulmonary fibrosis (IPF) is a progressive, often fatal form of interstitial lung disease (ILD) characterized by the absence of a known cause and usual interstitial pneumonitis (UIP) pattern on chest CT imaging and/or histopathology. Distinguishing UIP/IPF from other ILD subtypes is essential given different treatments and prognosis. Lung biopsy is necessary when noninvasive data are insufficient to render a confident diagnosis. ⋯ Deep learning may be superior to visual assessment in predicting UIP/IPF histopathology from CT imaging and may serve as an alternative to invasive lung biopsy.
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Multicenter Study
Early recognition of low-risk SARS-CoV-2 pneumonia: A model validated with initial data and IDSA/ATS minor criteria.
A shortage of beds in ICUs and conventional wards during the COVID-19 pandemic led to a collapse of health care resources. ⋯ Initial biochemical findings and the application of < 3 IDSA/ATS minor criteria make early identification of low-risk SARS-CoV-2 pneumonia (approximately 80% of hospitalized patients) feasible. This scenario could facilitate and streamline health care resource allocation for patients with COVID-19.