Chest
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Survivors of ICU hospitalizations often experience severe and debilitating symptoms long after critical illness has resolved. Many patients experience notable psychiatric sequelae such as depression, anxiety, and posttraumatic stress disorder (PTSD) that may persist for months to years after discharge. The COVID-19 pandemic has produced large numbers of critical illness survivors, warranting deeper understanding of psychological morbidity after COVID-19 critical illness. ⋯ Existing and novel interventions focused on minimizing psychiatric morbidity need to be further investigated to improve critical care survivorship after COVID-19 illness. This review proposes a framework to conceptualize three domains of risk factors (pathophysiologic, iatrogenic, and situational) associated with psychological morbidity caused by COVID-19 critical illness: (1) direct and indirect effects of the COVID-19 virus in the brain; (2) iatrogenic complications of ICU care that may disproportionately affect patients with COVID-19; and (3) social isolation that may worsen psychological morbidity. In addition, we review current interventions to minimize psychological complications after critical illness.
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Artificial intelligence tools and techniques such as machine learning (ML) are increasingly seen as a suitable manner in which to increase the prediction capacity of currently available clinical tools, including prognostic scores. However, studies evaluating the efficacy of ML methods in enhancing the predictive capacity of existing scores for community-acquired pneumonia (CAP) are limited. We aimed to apply and validate a causal probabilistic network (CPN) model to predict mortality in patients with CAP. ⋯ SeF-ML shows potential for improving mortality prediction among patients with CAP, using structured health data. Additional external validation studies should be conducted to support generalizability.
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The sex differences in use, safety outcomes, and health-care resource use of patients with pulmonary embolism (PE) undergoing percutaneous pulmonary artery thrombectomy are not well characterized. ⋯ In this large nationwide cohort, women with PE who underwent percutaneous thrombectomy showed higher morbidity and in-hospital mortality compared with men.
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Lung ultrasound (LUS) scanning is useful to diagnose and assess the severity of pulmonary lesions during COVID-19-related ARDS (CoARDS). A conventional LUS score is proposed to measure the loss of aeration during CoARDS. However, this score was validated during the pre-COVID-19 era in patients with ARDS in the ICU and does not consider the differences with CoARDS. An alternative LUS method is based on grading the percentage of extension of the typical signs of COVID-19 pneumonia on the lung surface (LUSext). ⋯ LUSext is a valid measure of the severity of the lesions when compared with the CT scan. Not only are LUSext and CTvol correlated, but they also have similar inverse correlation with the severity of respiratory failure. LUSext is a practical and simple bedside measure of the severity of pneumonia in CoARDS, whose clinical and prognostic impact need to be investigated further.
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Overdiagnosis of lung cancer by low-dose CT (LDCT) screening has raised concerns globally. LDCT screening has been used widely in employee health examinations in China since 2011. ⋯ The results provide evidence at a population level for lung cancer overdiagnosis in Chinese women resulting from increasing LDCT screening in the low-risk populations. Criteria for LDCT screening and management of screening-detected nodules need to be addressed fully for expanded application of LDCT screening in China.