https://www.selleckchem.com/products/vbit-4.html Exploratory outcomes of health-related quality-of-life patient-reported outcomes will be collected. Hospitalised patients with laboratory-confirmed COVID-19 will be recruited. This study was approved by the University of Utah Institutional Review Board (IRB_0013292), approved by the US FDA under Investigational New Drug (No 23369) and is registered on ClinicalTrials.gov. Results will be disseminated via peer-reviewed publications and conference presentations. NCT04497389; Pre-results. NCT04497389; Pre-results. Most patients are unaware they have liver cirrhosis until they present with a decompensating event. We therefore aimed to develop and validate an algorithm to predict advanced liver disease (AdvLD) using data widely available in primary care. Logistic regression was performed on routinely collected blood result data from the University Hospital Southampton (UHS) information systems for 16 967 individuals who underwent an upper gastrointestinal endoscopy (2005-2016). Data were used to create a model aimed at detecting AdvLD 'CIRRhosis Using Standard tests' (CIRRUS). Prediction of a first serious liver event (SLE) was then validated in two cohorts of 394 253 (UHS primary and secondary care) and 183 045 individuals (Care and Health Information Exchange (CHIE) primary care). Model creation dataset cirrhosis or portal hypertension. Validation datasets SLE (gastro-oesophageal varices, liver-related ascites or cirrhosis). In the model creation dataset, 931 SLEs were recorded (5.5%). CIRRUS detected cirrhosisry care using routinely available data may provide an opportunity for earlier intervention and prevention of liver-related morbidity and mortality. The overarching objective of the scoping review was to examine peer reviewed and grey literature for best practices that have been developed, implemented and/or evaluated for delayed discharge involving a hospital setting. Two specific objectives were to review what the