Background: Since March 2020, Ireland has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To date, while several cohorts from China have been described, our understanding is limited, with no data describing the epidemiological and clinical characteristics of patients with COVID-19 in Ireland. To improve our understanding of the clinical characteristics of this emerging infection we carried out a retrospective review of patient data to examine the clinical characteristics of patients admitted for COVID-19 hospital treatment. Methods: Demographic, clinical and laboratory data on the rst 100 adult patients admitted to Mater Misericordiae University Hospital (MMUH) for in-patient COVID-19 treatment after onset of the outbreak in March 2020 was extracted from clinical and administrative records. Missing data were excluded from the analysis. Results: Fifty-eight per cent were male, 63% were Irish nationals, 29% were GMS eligible, and median age was 45 years (interquartile range [IQR] =34-64 years). Patients had symptoms for a median of ve days before diagnosis (IQR=2.5-7 days), most commonly cough (72%), fever (65%), dyspnoea (37%), fatigue (28%), myalgia (27%) and headache (24%). Of all cases, 54 had at least one pre-existing chronic illness (most commonly hypertension, diabetes mellitus or asthma). At initial assessment, the most common abnormal ndings were: C-reactive protein >7.0mg/L (74%), ferritin >247μg/L (women) or >275μg/L (men) (62%), D-dimer >0.5μg/dL (62%), chest imaging (59%), NEWS Score (modi ed) of ≥3 (55%) and heart rate >90/min (51%). Twenty-seven required supplemental oxygen, of which 17 were admitted to the intensive care unit-14 requiring ventilation. Forty received antiviral treatment (most commonly hydroxychloroquine or lopinavir/ritonavir). Four died, 17 were admitted to intensive care, and 74 were discharged home, with nine days the median hospital stay (IQR=6-11). Conclusion: Our ndings reinforce the emerging consensus of COVID-19 as an acute life-threatening disease and highlights, the importance of laboratory (ferritin, C-reactive protein, D-dimer) and radiological parameters, in addition to clinical parameters. Further cohort studies involving larger samples followed longitudinally are a priority.

The virus SARS-CoV2, which causes coronavirus disease (COVID-19) has become a pandemic and has spread to every inhabited continent. Given the increasing caseload, there is an urgent need to augment clinical skills in order to identify from among the many mild cases the few that will progress to critical illness. We present a first step towards building an artificial intelligence (AI) framework, with predictive analytics (PA) capabilities applied to real patient data, to provide rapid clinical decision-making support. COVID-19 has presented a pressing need as a) clinicians are still developing clinical acumen to this novel disease and b) resource limitations in a surging pandemic require difficult resource allocation decisions. The objectives of this research are: (1) to algorithmically identify the combinations of clinical characteristics of COVID-19 that predict outcomes, and (2) to develop a tool with AI capabilities that will predict patients at risk for more severe illness on initial presentation. The predictive models learn from historical data to help predict who will develop acute respiratory distress syndrome (ARDS), a severe outcome in COVID-19. Our results, based on data from two hospitals in Wenzhou, Zhejiang, China, identified features on initial presentation with COVID-19 that were most predictive of later development of ARDS. A mildly elevated alanine aminotransferase (ALT) (a liver enzyme), the presence of myalgias (body aches), and an elevated hemoglobin (red blood cells), in this order, are the clinical features, on presentation, that are the most predictive. The predictive models that learned from historical data of patients from these two hospitals achieved 70% to 80% accuracy in predicting severe cases.

IMPORTANCE Severe acute respiratory syndrome coronavirus 2 has caused a global outbreak of coronavirus disease 2019 (COVID-19). Severe acute respiratory syndrome coronavirus 2 binds angiotensin-converting enzyme 2 of the rennin-angiotensin system, resulting in hypokalemia. OBJECTIVE To investigate the prevalence, causes, and clinical implications of hypokalemia, including its possible association with treatment outcomes, among patients with COVID-19.

AbstractsThe clinical features and treatment of pulmonary tuberculosis patients with COVID-19 is unclear and understudied. Here, three pulmonary tuberculosis patients with COVID-19 infection were prospectively followed from hospital admission to discharge. We provide information and experience with treatment of pulmonary tuberculosis cases with confirmed COVID-19 infection.