PubMed COVID-19 Clinical Care

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COVID-19 is responsible for high mortality, but robust machine learning-based predictors of mortality are lacking. To generate a model for predicting mortality in patients hospitalized with COVID-19 using Gradient Boosting Decision Trees (GBDT). The

Viral RNA-host protein interactions are indispensable during RNA virus transcription and replication, but their detailed structural and dynamical features remain largely elusive. Here, we characterize the binding interface for the SARS-CoV-2 stem

CONCLUSIONS: COVID-19 vaccine induced hepatitis is a clinical significant complication, and HBV reactivation may account for a possible mechanism.

CONCLUSION: Our study demonstrates that children and adolescents have experienced a deterioration of mental health due to the pandemic. Family factors played an important role in the mental health of children during the lockdown. When a public crisis

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CONCLUSION: Daily telerounding with neonatologists and APPs in a Level II NICU supported neonatal care. Quality metrics and clinical outcomes are described with no differences seen before and during the COVID-19 pandemic.

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CONCLUSION: The domain of neuroticism personality, and the hygienic conditions in the workplace were the predictors with the most weight in the model. This study could be useful for defining aspects that need to be considered for the well-being of

We aimed to identify intergenerational solidarity (emotional closeness, in-person contact, phone contact, geographic proximity, consensus, and conflict) with digital communication (texting, video call, and social media interaction) with adult