Association of patient characteristics with clinical outcomes in a cohort of hospitalised patients with SARS-CoV-2 infection in a Greek referral centre for COVID-19.

Patient-important outcomes related to coronavirus disease 2019 (COVID-19) continue to drive the pandemic response across the globe. Various prognostic factors for COVID-19 severity have emerged and their replication across different clinical settings providing health services is ongoing. We aimed to describe the clinical characteristics and their association with outcomes in patients hospitalised with COVID-19 in the University Hospital of Ioannina. We assessed a cohort of 681 consecutively hospitalised patients with COVID-19 from January 2020 to December 2021. Demographic data, underlying comorbidities, clinical presentation, biochemical markers, radiologic findings, COVID-19 treatment and outcome data were collected at the first day of hospitalisation and up to 90 days. Multivariable Cox regression analyses were performed to investigate the associations between clinical characteristics (hazard ratios (HRs) per standard deviation (s.d.)) with intubation and/or mortality status. The participants' mean age was 62.8 (s.d., 16.9) years and 57% were males. The most common comorbidities were hypertension (45%), cardiovascular disease (19%) and diabetes mellitus (21%). Patients usually presented with fever (81%), cough (50%) and dyspnoea (27%), while lymphopenia and increased inflammatory markers were the most common laboratory abnormalities. Overall, 55 patients (8%) were intubated, and 86 patients (13%) died. There were statistically significant positive associations between intubation or death with age (HR: 2.59; 95% CI 1.52-4.40), lactate dehydrogenase (HR: 1.44; 95% CI 1.04-1.98), pO2/FiO2 ratio < 100 mmHg (HR: 3.52; 95% CI 1.14-10.84), and inverse association with absolute lymphocyte count (HR: 0.54; 95% CI 0.33-0.87). These data might help to identify points for improvement in the management of COVID-19 patients.

Impact of covid-19 on acute myocarditis hospital admissions in the national health service of England, UK (2019-2020)

Introduction: Acute myocarditis has been reported in patients infected with COVID-19 in case series and imaging-based studies. We sought to assess this link by evaluating trends in hospital admissions due to acute myocarditis and COVID-19 on a national level during the pandemic. Methods: Data on all NHS England hospital admissions with a primary or secondary diagnosis of acute myocarditis were acquired and curated from the NHS Digital hospital episode statistics dataset from 2019-2020. COVID-19 data was obtained from the UK government daily statistics. Rolling averages over 28-day periods are presented. Results: Across all ages, there were 1,894 hospital admissions due to myocarditis in 2019 compared with 1,610 in 2020 (15% reduction). During the first national lockdown (23rdMar-19thJun 2020), myocarditis admissions were 32% lower than the same period in 2019. During the second lockdown (5thNov-2ndDec), myocarditis admissions were 9% greater than in 2019, although this increase was not sustained throughout December despite the subsequent surge in COVID-19 admissions. In general, patients admitted in 2020, compared to 2019, were older (median age 46 years, interquartile range 28-61 vs 41 years, IQR 26-58;p<0.001), but sex (66% men), ethnicity (39% non-Caucasian, 9% unknown) and duration of hospital admission (median 2 days;IQR 1-4) were similar for both years. Discussion: As COVID-19 admissions peaked in early 2020, there was a sharp decline in myocarditis admissions, probably attributed to profound disruptions in healthcare provision, but possibly due to reduced transmission of other viruses during lockdown. Whilst myocarditis admissions increased during the second lockdown, there was no clear association between COVID19 and myocarditis admission numbers. Further research may identify delayed presentations or sequelae of myocarditis, particularly following the larger COVID-19 peak in January 2021, as well as the impact of the vaccination programme.

Cardiovascular disease, hypertension, diabetes and cystatin c jointly predict covid-19 mortality alongside age, male sex and black ethnicity

Introduction: Studies of risk factors for severe/fatal COVID-19 to date may not have identified the optimal set of informative predictors. Hypothesis: Use of penalized regression with stability analysis may identify new, sparse sets of risk factors jointly associated with COVID-19 mortality. Methods: We investigated demographic, social, lifestyle, biological (lipids, cystatin C, vitamin D), medical (comorbidities, medications) and air pollution data from UK Biobank (N=473,574) in relation to linked COVID-19 mortality, and compared with non-COVID-19 mortality. We used penalized regression models (LASSO) with stability analysis (80% selection threshold from 1,000 models with 80% subsampling) to identify a sparse set of variables associated with COVID-19 mortality. Results: Among 43 variables considered by LASSO stability selection, cardiovascular disease, hypertension, diabetes, cystatin C, age, male sex and Black ethnicity were jointly predictive of COVID-19 mortality risk at 80% selection threshold (Figure). Of these, Black ethnicity and hypertension contributed to COVID-19 but not non-COVID-19 mortality. Conclusions: Use of LASSO stability selection identified a sparse set of predictors for COVID-19mortality including cardiovascular disease, hypertension, diabetes and cystatin C, a marker of renalfunction that has also been implicated in atherogenesis and inflammation. These results indicate theimportance of cardiometabolic comorbidities as predisposing factors for COVID-19 mortality.Hypertension was differentially highly selected for risk of COVID-19 mortality, suggesting the need for continued vigilance with good blood pressure control during the pandemic.