Plos One
-
The goal of this study is to construct a mortality prediction model using the XGBoot (eXtreme Gradient Boosting) decision tree model for AKI (acute kidney injury) patients in the ICU (intensive care unit), and to compare its performance with that of three other machine learning models. ⋯ XGBoot model had obvious advantages of performance compared to the other machine learning models. This will be helpful for risk identification and early intervention for AKI patients at risk of death.
-
Research surrounding COVID-19 (coronavirus disease 2019) is rapidly increasing, including the study of biomarkers for predicting outcomes. There is little data examining the correlation between serum albumin levels and COVID-19 disease severity. The purpose of this study is to evaluate whether admission albumin levels reliably predict outcomes in COVID-19 patients. ⋯ Admission serum albumin levels appear to be a predictive biomarker for outcomes in COVID-19 patients. We found that higher albumin levels on admission were associated with significantly fewer adverse outcomes, including less VTE events, ARDS development, ICU admissions, and readmissions within 90 days. Screening patients may lead to early identification of patients at risk for developing in-hospital complications and improve optimization and preventative efforts in this cohort.
-
Comparative Study
Combination of (interferon beta-1b, lopinavir/ritonavir and ribavirin) versus favipiravir in hospitalized patients with non-critical COVID-19: A cohort study.
Our study aims at comparing the efficacy and safety of IFN-based therapy (lopinavir/ritonavir, ribavirin, and interferon β-1b) vs. favipiravir (FPV) in a cohort of hospitalized patients with non-critical COVID-19. ⋯ Early IFN-based triple therapy was associated with lower 28-days mortality as compared to FPV.
-
The COVID-19 pandemic and government imposed social restrictions like lockdown exposed most individuals to an unprecedented stress, increasing mental health disorders worldwide. We explored subjective cognitive functioning and mental health changes and their possible interplay related to COVID-19-lockdown. We also investigated potential risk factors to identify more vulnerable groups. ⋯ Being female, under 45 years, working from home or being underemployed were all identified as relevant risk factors for worsening cognition and mental health. Frequent consumers of COVID-19 mass media information or residents in highly infected communities reported higher depression and anxiety symptoms, particularly hypochondria in the latter. If similar restrictions are reimposed, governments must carefully consider these more vulnerable groups in their decisions, whilst developing effective global and long-term responses to the cognitive and mental health challenges of this type of pandemic; as well as implementing appropriate psychological interventions with specific guidelines: particularly regarding exposure to COVID-19 mass-media reports.
-
To determine the seroprevalence of anti-SARS-CoV-2 IgG and IgM antibodies in symptomatic Japanese COVID-19 patients. ⋯ A serologic anti-SARS-CoV-2 antibody analysis can complement PCR for diagnosing COVID-19 14 days after symptom onset.