Thrombolysis for acute ischaemic stroke (AIS) patients aged ˜80 years is evidence based, although its use in previously dependent patients is controversial.

Data from 831 thrombolysed AIS patients in our centre from 2009-2017 were used to compare demographic trends and outcomes (haemorrhage, mortality, three-month independence) in patients aged <80 and ˜80 years and with prior dependency. Comparison with UK and world registry data regarding age and pre-stroke dependency was made.

The percentage of treated patients aged ˜80 years increased year-on-year, doubling from 25% to 50% (p <0.01), with increasing average age and pre-stroke dependency in world centres. Patients ˜80 years had higher (p <0.001) stroke severity, symptomatic intracerebral haemorrhage (5% vs. 1.5%), mortality (35% vs. 13%) and lower three month independent survival (24% vs. 60%). Patients with pre-stroke dependency had especially higher three month mortality (57-71%, OR 3.75 [95% CI 1.97-7.15]) in both age groups.

Patients aged ˜80 years and with dependency increasingly receive thrombolysis. Given poorer outcomes thrombolysis trials are needed in pre-stroke dependent patients.

Patients aged ˜80 years and with dependency increasingly receive thrombolysis. Given poorer outcomes thrombolysis trials are needed in pre-stroke dependent patients.

A prospective bed utilisation census of acute London hospitals using an established Day of Care Survey (DoCS), which quantified adult patients not meeting criteria for in-hospital care.

Twenty-three hospitals were surveyed over two weeks in October/November 2017 using supervised trained hospital staff. Pairs of staff visited wards, reviewed all patients and identified those not meeting inpatient care criteria, recording reasons for delay. Patient demographics, length of stay (LOS), ward specialty and delay reasons were collected.

Overall – In total, 8,656 in-patients were studied (overall occupancy 96%, range 82-117%) 800 definite discharges were excluded, leaving 7,856 patients for analysis; seven hospitals had °100% occupancy; 1,919/7,856 patients (24%, range 12-43%) did not meet criteria; 56% of patients were over 70 years; five hospitals had higher number of patients <70yo 56% patients had LOS 0˛7days. Delayed patients – Number of delayed patients increased with age, but three hospitals had more with insufficient discharges. This study suggests policies selecting age and/or LOS alone as cut offs to tackle delays in care may miss a large proportion of patients requiring more timely interventions. Adopting a proactive thematic approach to improvement using the top eight delay reasons provides an obvious opportunity to reduce delays while noting the inter site variation. All metrics analysed emphasized the need for informed local data to help support local change.Factors such as non-uniform definitions of mortality, uncertainty in disease prevalence, and biased sampling complicate the quantification of fatality during an epidemic. Regardless of the employed fatality measure, the infected population and the number of infection-caused deaths need to be consistently estimated for comparing mortality across regions. We combine historical and current mortality data, a statistical testing model, and an SIR epidemic model, to improve estimation of mortality. We find that the average excess death across the entire US is 13% higher than the number of reported COVID-19 deaths. In some areas, such as New York City, the number of weekly deaths is about eight times higher than in previous years. Other countries such as Peru, Ecuador, Mexico, and Spain exhibit excess deaths significantly higher than their reported COVID-19 deaths. Conversely, we find negligible or negative excess deaths for part and all of 2020 for Denmark, Germany, and Norway.

Risk of severe coronavirus disease 2019 (COVID-19) increases with age, is greater in males, and is associated with decreased numbers of blood lymphoid cells. Though the reasons for these robust associations are unclear, effects of age and sex on innate and adaptive lymphoid subsets, including on homeostatic innate lymphoid cells (ILCs) implicated in disease tolerance, may underlie the effects of age and sex on COVID-19 morbidity and mortality.

Flow cytometry was used to quantitate subsets of blood lymphoid cells from people infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), comparing those hospitalized with severe COVID-19 (n=40) and those treated as outpatients for less severe disease (n=51). 86 healthy individuals served as controls. The relationship between abundance of specific blood lymphoid cell types, age, sex, hospitalization, duration of hospitalization, and elevation of blood markers for systemic inflammation, was determined using multiple regression.

After accounting he number of ILCs with age and in males accounts for the increased risk of severe COVID-19 in these demographic groups.The coronavirus disease of 2019 (COVID-19) is a pandemic. To characterize its disease transmissibility, we propose a Bayesian change point detection model using daily actively infectious cases. Our model builds on a Bayesian Poisson segmented regression model that can 1) capture the epidemiological dynamics under the changing conditions caused by external or internal factors; 2) provide uncertainty estimates of both the number and locations of change points; and 3) adjust any explanatory time-varying covariates. Our model can be used to evaluate public health interventions, identify latent events associated with spreading rates, and yield better short-term forecasts.

COVID-19 has impacted millions of patients across the world. Molecular testing occurring now identifies the presence of the virus at the sampling site nasopharynx, nares, or oral cavity. RNA sequencing has the potential to establish both the presence of the virus and define the host’s response in COVID-19.

Single center, prospective study of patients with COVID-19 admitted to the intensive care unit where deep RNA sequencing (>100 million reads) of peripheral blood with computational biology analysis was done. All patients had positive SARS-CoV-2 PCR. Clinical data was prospectively collected.

We enrolled fifteen patients at a single hospital. DMOG Patients were critically ill with a mortality of 47% and 67% were on a ventilator. All the patients had the SARS-CoV-2 RNA identified in the blood in addition to RNA from other viruses, bacteria, and archaea. The expression of many immune modulating genes, including PD-L1 and PD-L2, were significantly different in patients who died from COVID-19. Some proteins were influenced by alternative transcription and splicing events, as seen in HLA-C, HLA-E, NRP1 and NRP2.