Inpatient COVID-19 mortality has reduced over time: Results from an observational cohort.

BACKGROUND: The Covid-19 pandemic in the United Kingdom has seen two waves; the first starting in March 2020 and the second in late October 2020. It is not known whether outcomes for those admitted with severe Covid were different in the first and second waves. METHODS: The study population comprised all patients admitted to a 1,500-bed London Hospital Trust between March 2020 and March 2021, who tested positive for Covid-19 by PCR within 3-days of admissions. Primary outcome was death within 28-days of admission. Socio-demographics (age, sex, ethnicity), hypertension, diabetes, obesity, baseline physiological observations, CRP, neutrophil, chest x-ray abnormality, remdesivir and dexamethasone were incorporated as co-variates. Proportional subhazards models compared mortality risk between wave 1 and wave 2. Cox-proportional hazard model with propensity score adjustment were used to compare mortality in patients prescribed remdesivir and dexamethasone. RESULTS: There were 3,949 COVID-19 admissions, 3,195 hospital discharges and 733 deaths. There were notable differences in age, ethnicity, comorbidities, and admission disease severity between wave 1 and wave 2. Twenty-eight-day mortality was higher during wave 1 (26.1% versus 13.1%). Mortality risk adjusted for co-variates was significantly lower in wave 2 compared to wave 1 [adjSHR 0.49 (0.37, 0.65) p<0.001]. Analysis of treatment impact did not show statistically different effects of remdesivir [HR 0.84 (95%CI 0.65, 1.08), p = 0.17] or dexamethasone [HR 0.97 (95%CI 0.70, 1.35) p = 0.87]. CONCLUSION: There has been substantial improvements in COVID-19 mortality in the second wave, even accounting for demographics, comorbidity, and disease severity. Neither dexamethasone nor remdesivir appeared to be key explanatory factors, although there may be unmeasured confounding present.

SARS-CoV-2 Exacerbates Beta-Amyloid Neurotoxicity, Inflammation and Oxidative Stress in Alzheimer's Disease Patients.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) triggered the pandemic Coronavirus Disease 19 (COVID-19), causing millions of deaths. The elderly and those already living with comorbidity are likely to die after SARS-CoV-2 infection. People suffering from Alzheimer's disease (AD) have a higher risk of becoming infected, because they cannot easily follow health roles. Additionally, those suffering from dementia have a 40% higher risk of dying from COVID-19. Herein, we collected from Gene Expression Omnibus repository the brain samples of AD patients who died of COVID-19 (AD+COVID-19), AD without COVID-19 (AD), COVID-19 without AD (COVID-19) and control individuals. We inspected the transcriptomic and interactomic profiles by comparing the COVID-19 cohort against the control cohort and the AD cohort against the AD+COVID-19 cohort. SARS-CoV-2 in patients without AD mainly activated processes related to immune response and cell cycle. Conversely, 21 key nodes in the interactome are deregulated in AD. Interestingly, some of them are linked to beta-amyloid production and clearance. Thus, we inspected their role, along with their interactors, using the gene ontologies of the biological process that reveals their contribution in brain organization, immune response, oxidative stress and viral replication. We conclude that SARS-CoV-2 worsens the AD condition by increasing neurotoxicity, due to higher levels of beta-amyloid, inflammation and oxidative stress.

Questioning the sex-specific differences in the association of smoking on the survival rate of hospitalized COVID-19 patients.

INTRODUCTION: In the absence of a universally accepted association between smoking and COVID-19 health outcomes, we investigated this relationship in a representative cohort from one of the world's highest tobacco consuming regions. This is the first report from the Middle East and North Africa that tackles specifically the association of smoking and COVID-19 mortality while demonstrating a novel sex-discrepancy in the survival rates among patients. METHODS: Clinical data for 743 hospitalized COVID-19 patients was retrospectively collected from the leading centre for COVID-19 testing and treatment in Lebanon. Logistic regression, Kaplan-Meier survival curves and Cox proportional hazards model adjusted for age and stratified by sex were used to assess the association between the current cigarette smoking status of patients and COVID-19 outcomes. RESULTS: In addition to the high smoking prevalence among our hospitalized COVID-19 patients (42.3%), enrolled smokers tended to have higher reported ICU admissions (28.3% vs 16.6%, p<0.001), longer length of stay in the hospital (12.0 ± 7.8 vs 10.8 days, p<0.001) and higher death incidences as compared to non-smokers (60.5% vs 39.5%, p<0.001). Smokers had an elevated odds ratio for death (OR = 2.3, p<0.001) and for ICU admission (OR = 2.0, p<0.001) which remained significant in a multivariate regression model. Once adjusted for age and stratified by sex, our data revealed that current smoking status reduces survival rate in male patients ([HR] = 1.9 [95% (CI), 1.029-3.616]; p = 0.041) but it does not affect survival outcomes among hospitalized female patients([HR] = 0.79 [95% CI = 0.374-1.689]; p = 0.551). CONCLUSION: A high smoking prevalence was detected in our hospitalized COVID-19 cohort combined with worse prognosis and higher mortality rate in smoking patients. Our study was the first to highlight potential sex-specific consequences for smoking on COVID-19 outcomes that might further explain the higher vulnerability to death from this disease among men.

Temporal trends and forecasting of COVID-19 hospitalisations and deaths in Scotland using a national real-time patient-level data platform: a statistical modelling study.

BACKGROUND: As the COVID-19 pandemic continues, national-level surveillance platforms with real-time individual person-level data are required to monitor and predict the epidemiological and clinical profile of COVID-19 and inform public health policy. We aimed to create a national dataset of patient-level data in Scotland to identify temporal trends and COVID-19 risk factors, and to develop a novel statistical prediction model to forecast COVID-19-related deaths and hospitalisations during the second wave. METHODS: We established a surveillance platform to monitor COVID-19 temporal trends using person-level primary care data (including age, sex, socioeconomic status, urban or rural residence, care home residence, and clinical risk factors) linked to data on SARS-CoV-2 RT-PCR tests, hospitalisations, and deaths for all individuals resident in Scotland who were registered with a general practice on Feb 23, 2020. A Cox proportional hazards model was used to estimate the association between clinical risk groups and time to hospitalisation and death. A survival prediction model derived from data from March 1 to June 23, 2020, was created to forecast hospital admissions and deaths from October to December, 2020. We fitted a generalised additive spline model to daily SARS-CoV-2 cases over the previous 10 weeks and used this to create a 28-day forecast of the number of daily cases. The age and risk group pattern of cases in the previous 3 weeks was then used to select a stratified sample of individuals from our cohort who had not previously tested positive, with future cases in each group sampled from a multinomial distribution. We then used their patient characteristics (including age, sex, comorbidities, and socioeconomic status) to predict their probability of hospitalisation or death. FINDINGS: Our cohort included 5 384 819 people, representing 98·6% of the entire estimated population residing in Scotland during 2020. Hospitalisation and death among those testing positive for SARS-CoV-2 between March 1 and June 23, 2020, were associated with several patient characteristics, including male sex (hospitalisation hazard ratio [HR] 1·47, 95% CI 1·38-1·57; death HR 1·62, 1·49-1·76) and various comorbidities, with the highest hospitalisation HR found for transplantation (4·53, 1·87-10·98) and the highest death HR for myoneural disease (2·33, 1·46-3·71). For those testing positive, there were decreasing temporal trends in hospitalisation and death rates. The proportion of positive tests among older age groups (>40 years) and those with at-risk comorbidities increased during October, 2020. On Nov 10, 2020, the projected number of hospitalisations for Dec 8, 2020 (28 days later) was 90 per day (95% prediction interval 55-125) and the projected number of deaths was 21 per day (12-29). INTERPRETATION: The estimated incidence of SARS-CoV-2 infection based on positive tests recorded in this unique data resource has provided forecasts of hospitalisation and death rates for the whole of Scotland. These findings were used by the Scottish Government to inform their response to reduce COVID-19-related morbidity and mortality. FUNDING: Medical Research Council, National Institute for Health Research Health Technology Assessment Programme, UK Research and Innovation Industrial Strategy Challenge Fund, Health Data Research UK, Scottish Government Director General Health and Social Care.

Vascular comorbidities worsen prognosis of patients with heart failure hospitalised with COVID-19.

BACKGROUND: Prior diagnosis of heart failure (HF) is associated with increased length of hospital stay (LOS) and mortality from COVID-19. Associations between substance use, venous thromboembolism (VTE) or peripheral arterial disease (PAD) and its effects on LOS or mortality in patients with HF hospitalised with COVID-19 remain unknown. OBJECTIVE: This study identified risk factors associated with poor in-hospital outcomes among patients with HF hospitalised with COVID-19. METHODS: Case-control study was conducted of patients with prior diagnosis of HF hospitalised with COVID-19 at an academic tertiary care centre from 1 January 2020 to 28 February 2021. Patients with HF hospitalised with COVID-19 with risk factors were compared with those without risk factors for clinical characteristics, LOS and mortality. Multivariate regression was conducted to identify multiple predictors of increased LOS and in-hospital mortality in patients with HF hospitalised with COVID-19. RESULTS: Total of 211 patients with HF were hospitalised with COVID-19. Women had longer LOS than men (9 days vs 7 days; p<0.001). Compared with patients without PAD or ischaemic stroke, patients with PAD or ischaemic stroke had longer LOS (7 days vs 9 days; p=0.012 and 7 days vs 11 days, p<0.001, respectively). Older patients (aged 65 and above) had increased in-hospital mortality compared with younger patients (adjusted OR: 1.04; 95% CI 1.00 to 1.07; p=0.036). Prior diagnosis of VTE increased mortality more than threefold in patients with HF hospitalised with COVID-19 (adjusted OR: 3.33; 95% CI 1.29 to 8.43; p=0.011). CONCLUSION: Vascular diseases increase LOS and mortality in patients with HF hospitalised with COVID-19.

Clinical Characteristics and Outcomes of COVID-19 in West Virginia.

This study examines the clinical characteristics, outcomes and types of management in SARS-CoV-2 infected patients, in the hospitals affiliated with West Virginia University. We included patients from West Virginia with SARS-CoV-2 infection between 15 April to 30 December 2020. Descriptive analysis was performed to summarize the characteristics of patients. Regression analyses were performed to assess the association between baseline characteristics and outcomes. Of 1742 patients, the mean age was 47.5 years (±22.7) and 54% of patients were female. Only 459 patients (26.3%) reported at least one baseline symptom, of which shortness of breath was most common. More than half had at least one comorbidity, with hypertension being the most common. There were 131 severe cases (7.5%), and 84 patients (4.8%) died despite treatment. The mean overall length of hospital stay was 2.6 days (±6.9). Age, male sex, and comorbidities were independent predictors of outcomes. In this study of patients with SARS-CoV-2 infection from West Virginia, older patients with underlying co-morbidities had poor outcomes, and the in-hospital mortality was similar to the national average.

Variation in COVID-19 Mortality Across 117 US Hospitals in High- and Low-Burden Settings.

Some hospitals have faced a surge of patients with COVID-19, while others have not. We assessed whether COVID-19 burden (number of patients with COVID-19 admitted during April 2020 divided by hospital certified bed count) was associated with mortality in a large sample of US hospitals. Our study population included 14,226 patients with COVID-19 (median age 66 years, 45.2% women) at 117 hospitals, of whom 20.9% had died at 5 weeks of follow-up. At the hospital level, the observed mortality ranged from 0% to 44.4%. After adjustment for age, sex, and comorbidities, the adjusted odds ratio for in-hospital death in the highest quintile of burden was 1.46 (95% CI, 1.07-2.00) compared to all other quintiles. Still, there was large variability in outcomes, even among hospitals with a similar level of COVID-19 burden and after adjusting for age, sex, and comorbidities.

Epidemiology of end-stage kidney disease.

End-stage kidney disease (ESKD) is a common and morbid disease that affects patients' quality and length of life, representing a large portion of health care expenditure in the United States. These patients commonly have associated diabetes and cardiovascular disease, with high rates of cardiovascular-related death. Management of ESKD requires renal replacement therapy via dialysis or transplantation. While transplantation provides the greatest improvement in survival and quality of life, the vast majority of patients are treated initially with hemodialysis. However, outcomes differ significantly among patient populations. Barriers in access to care have particularly affected at-risk populations, such as Black and Hispanic patients. These patients receive less pre-ESKD nephrology care, are less likely to initiate dialysis with a fistula, and wait longer for transplants-even in pediatric populations. Priorities for ESKD care moving into the future include increasing access to nephrology care in underprivileged populations, providing patient-centered care based on each patient's "life plan," and focusing on team-based approaches to ESKD care. This review explores ESKD from the perspective of epidemiology, costs, vascular access, patient-reported outcomes, racial disparities, and the impact of the COVID-19 crisis.

Mortality Rate of Infection With COVID-19 in Korea From the Perspective of Underlying Disease.

On December 31, 2019 the China National Health Commission (NHC) reported that an unknown cause of pneumonia had been detected in Wuhan in Hubei province. On February 12, the disease caused by the novel coronavirus (2019-nCoV) was given a formal name, COVID-19. On January 20, 2020, the first case of COVID-19 was confirmed in Korea. The age-specific death rate was the highest among patients over 70 years of age, with underlying diseases in their circulatory system, such as myocardial infarction, cerebral infraction, arrythmia, and hypertension. Patients with underlying disease who are 70 years of age or older should recognize that there is a high possibility of developing a serious disease in case of viral infection and follow strict precautions.

Charlson comorbidity index and a composite of poor outcomes in COVID-19 patients: A systematic review and meta-analysis.

BACKGROUND AND AIMS: The ongoing COVID-19 pandemic is disproportionately affecting patients with comorbidities. Therefore, thorough comorbidities assessment can help establish risk stratification of patients with COVID-19, upon hospital admission. Charlson Comorbidity Index (CCI) is a validated, simple, and readily applicable method of estimating the risk of death from comorbid disease and has been widely used as a predictor of long-term prognosis and survival. METHODS: We performed a systematic review and meta-analysis of CCI score and a composite of poor outcomes through several databases. RESULTS: Compared to a CCI score of 0, a CCI score of 1-2 and CCI score of ≥3 was prognostically associated with mortality and associated with a composite of poor outcomes. Per point increase of CCI score also increased mortality risk by 16%. Moreover, a higher mean CCI score also significantly associated with mortality and disease severity. CONCLUSION: CCI score should be utilized for risk stratifications of hospitalized COVID-19 patients.

Implications of Telemedicine in Oncology during the COVID-19 Pandemic.

COVID-19 has had a catastrophic effect on healthcare systems compromising the treatment of cancer patients. It has an increased disease burden in the cancer population. As a result, tele-oncology services have become essential to reduce the risk of cancer patients being exposed to the deadly pathogen. Many governmental establishments have endorsed the use of tele-oncology during COVID-19 era. However, telemedicine in oncology still has certain drawbacks that can be improved upon. Nevertheless, tele-oncology has shown great promise to support cancer care not only during this pandemic but also become a part of normal care in the future.