Circulating plasma concentrations of angiotensin-converting enzyme 2 in men and women with heart failure and effects of renin-angiotensin-aldosterone inhibitors

Abstract: AIMS: The current pandemic coronavirus SARS-CoV-2 infects a wide age group but predominantly elderly individuals, especially men and those with cardiovascular disease. Recent reports suggest an association with use of renin-angiotensin-aldosterone system (RAAS) inhibitors. Angiotensin-converting enzyme 2 (ACE2) is a functional receptor for coronaviruses. Higher ACE2 concentrations might lead to increased vulnerability to SARS-CoV-2 in patients on RAAS inhibitors. METHODS AND RESULTS: We measured ACE2 concentrations in 1485 men and 537 women with heart failure (index cohort). Results were validated in 1123 men and 575 women (validation cohort).The median age was 69 years for men and 75 years for women. The strongest predictor of elevated concentrations of ACE2 in both cohorts was male sex (estimate = 0.26, P < 0.001; and 0.19, P < 0.001, respectively). In the index cohort, use of ACE inhibitors, angiotensin receptor blockers (ARBs), or mineralocorticoid receptor antagonists (MRAs) was not an independent predictor of plasma ACE2. In the validation cohort, ACE inhibitor (estimate = -0.17, P = 0.002) and ARB use (estimate = -0.15, P = 0.03) were independent predictors of lower plasma ACE2, while use of an MRA (estimate = 0.11, P = 0.04) was an independent predictor of higher plasma ACE2 concentrations. CONCLUSION: In two independent cohorts of patients with heart failure, plasma concentrations of ACE2 were higher in men than in women, but use of neither an ACE inhibitor nor an ARB was associated with higher plasma ACE2 concentrations. These data might explain the higher incidence and fatality rate of COVID-19 in men, but do not support previous reports suggesting that ACE inhibitors or ARBs increase the vulnerability for COVID-19 through increased plasma ACE2 concentrations.


Antihypertensive drugs and risk of COVID-19? - Authors' reply


Early dinner or "dinner like a pauper": Evidence, the habitual time of the largest meal of the day - dinner - is predisposing to severe COVID-19 outcome - death.

Abstract: COVID-19 and metabolic syndrome are devastating pandemics. Effective control of metabolic parameters and their dysfunction may help prevent or minimize the acute and devastating effects of SARS-CoV-2 by reducing the local inflammatory response and blocking the entry of the virus into cells. With such consideration in mind, we gathered data from dietary surveys conducted in nine European countries to explore the relationship between actual clock hour of the large dinner meal and also interval in minutes between it and sunset in the respective countries and death rate above the median rate of per one million people as an index of mortality due to COVID-19 infection. Clock time of the dinner meal varied between 16:00 and 21:00 h across the European counties sampled, and the correlation between dinner mealtime and death rate was strongly correlated, R = 0.7991 (two-tailed p = 0.0098), with R 2 explaining 63% of the variation within the data. This strong linear positive correlation indicates that the later the clock time of the dinner meal, the higher is the death rate (and vice versa). The relationship between meal timing in reference to sunset, utilized as a gross surrogate marker of the activity/rest synchronizer of circadian rhythms, and death rate was negative and even slightly stronger, R = -0.8025 (two-tailed p = 0.0092), with R 2 explaining 64% of the variation within the data. This strong linear negative correlation indicates that the shorter the interval between the dinner meal and sunset, i.e., the closer the time of the largest meal of the day to bedtime, the greater is the death rate (and vice versa). Our preliminary approach to nighttime eating, in terms of the day's largest caloric intake, as a risk factor for the predisposing conditions of obesity, metabolic syndrome, type 2 diabetes, and other commonly associated comorbidities of being overweight, and death from COVID-19 infection reveals strong correlation with the time of the dinner meal, both in terms of its actual clock and circadian time.


Excess Mortality Estimation During the COVID-19 Pandemic: Preliminary Data from Portugal.

Abstract: INTRODUCTION Portugal is experiencing the effects of the COVID-19 pandemic since March 2020. All-causes mortality in Portugal increased during March and April 2020 compared to previous years, but this increase is not explained by COVID-19 reported deaths. The aim of this study was to analyze and consider other criteria for estimating excessive all-cause mortality during the early COVID-19 pandemic period. MATERIAL AND METHODS Public data was used to estimate excess mortality by age and region between March 1 and April 22, proposing baselines adjusted for the lockdown period. RESULTS Despite the inherent uncertainty, it is safe to assume an observed excess mortality of 2400 to 4000 deaths. Excess mortality was associated with older age groups (over age 65). DISCUSSION The data suggests a ternary explanation for early excess mortality: COVID-19, non-identified COVID-19 and decrease in access to healthcare. The estimates have implications in terms of communication of non-pharmaceutical actions, for research, and to healthcare professionals. CONCLUSION The excess mortality occurred between March 1 and April 22 was 3 to 5 fold higher than what can be explained by the official COVID-19 deaths.


Morbidity and mortality in homeless individuals, prisoners, sex workers, and individuals with substance use disorders in high-income countries: a systematic review and meta-analysis.

Abstract: BACKGROUND Inclusion health focuses on people in extremely poor health due to poverty, marginalisation, and multimorbidity. We aimed to review morbidity and mortality data on four overlapping populations who experience considerable social exclusion: homeless populations, individuals with substance use disorders, sex workers, and imprisoned individuals. METHODS For this systematic review and meta-analysis, we searched MEDLINE, Embase, and the Cochrane Library for studies published between Jan 1, 2005, and Oct 1, 2015. We included only systematic reviews, meta-analyses, interventional studies, and observational studies that had morbidity and mortality outcomes, were published in English, from high-income countries, and were done in populations with a history of homelessness, imprisonment, sex work, or substance use disorder (excluding cannabis and alcohol use). Studies with only perinatal outcomes and studies of individuals with a specific health condition or those recruited from intensive care or high dependency hospital units were excluded. We screened studies using systematic review software and extracted data from published reports. Primary outcomes were measures of morbidity (prevalence or incidence) and mortality (standardised mortality ratios [SMRs] and mortality rates). Summary estimates were calculated using a random effects model. FINDINGS Our search identified 7946 articles, of which 337 studies were included for analysis. All-cause standardised mortality ratios were significantly increased in 91 (99%) of 92 extracted datapoints and were 11·86 (95% CI 10·42-13·30; I2=94·1%) in female individuals and 7·88 (7·03-8·74; I2=99·1%) in men. Summary SMR estimates for the International Classification of Diseases disease categories with two or more included datapoints were highest for deaths due to injury, poisoning, and other external causes, in both men (7·89; 95% CI 6·40-9·37; I2=98·1%) and women (18·72; 13·73-23·71; I2=91·5%). Disease prevalence was consistently raised across the following categories: infections (eg, highest reported was 90% for hepatitis C, 67 [65%] of 103 individuals for hepatitis B, and 133 [51%] of 263 individuals for latent tuberculosis infection), mental health (eg, highest reported was 9 [4%] of 227 individuals for schizophrenia), cardiovascular conditions (eg, highest reported was 32 [13%] of 247 individuals for coronary heart disease), and respiratory conditions (eg, highest reported was 9 [26%] of 35 individuals for asthma). INTERPRETATION Our study shows that homeless populations, individuals with substance use disorders, sex workers, and imprisoned individuals experience extreme health inequities across a wide range of health conditions, with the relative effect of exclusion being greater in female individuals than male individuals. The high heterogeneity between studies should be explored further using improved data collection in population subgroups. The extreme health inequity identified demands intensive cross-sectoral policy and service action to prevent exclusion and improve health outcomes in individuals who are already marginalised. FUNDING Wellcome Trust, National Institute for Health Research, NHS England, NHS Research Scotland Scottish Senior Clinical Fellowship, Medical Research Council, Chief Scientist Office, and the Central and North West London NHS Trust.


SARS-CoV-2 in Italy: Population Density correlates with Morbidity and Mortality.

Abstract: Since the beginning of the SARS-CoV-2/COVID-19 epidemic in China, elderly and multimorbid subjects showed a higher mortality rate. However, other factors could influence the mortality and the spread of contagion such as the population density. An archival research based on the Italian data stratified by region was performed in order to quantify the association between the population density, ageing index, number of positive cases, number of deaths, case-fatality rate, and medical equipment (gloves, masks, and ventilators). Results showed a significant positive linear relationship between the population density and cases, deaths, and case-fatality rate. No correlation with the ageing index was shown. Furthermore, we found a significant positive correlation between the number of medical supplies and population density, cases, and deaths. However, the medical supplies did not show any correlation with the case-fatality rate. Taken together, these findings suggest that the population density and the lack of medical equipment are key factors explaining morbidity and mortality of COVID-19 in Italy.


Rate of Intensive Care Unit admission and outcomes among patients with coronavirus: A systematic review and Meta-analysis.

Abstract: BACKGROUND The rate of ICU admission among patients with coronavirus varied from 3% to 100% and the mortality was as high as 86% of admitted patients. The objective of the systematic review was to investigate the rate of ICU admission, mortality, morbidity, and complications among patients with coronavirus. METHODS A comprehensive strategy was conducted in PubMed/Medline; Science direct and LILACS from December 2002 to May 2020 without language restriction. The Heterogeneity among the included studies was checked with forest plot, χ2 test, I2 test, and the p-values. All observational studies reporting rate of ICU admission, the prevalence of mortality and its determinants among ICU admitted patients with coronavirus were included and the rest were excluded. RESULT A total of 646 articles were identified from different databases and 50 articles were selected for evaluation. Thirty-seven Articles with 24983 participants were included. The rate of ICU admission was 32% (95% CI: 26 to 38, 37 studies and 32, 741 participants). The Meta-Analysis revealed that the pooled prevalence of mortality in patients with coronavirus disease in ICU was 39% (95% CI: 34 to 43, 37 studies and 24, 983 participants). CONCLUSION The Meta-Analysis revealed that approximately one-third of patients admitted to ICU with severe Coronavirus disease and more than thirty percent of patients admitted to ICU with a severe form of COVID-19 for better care died which warns the health care stakeholders to give attention to intensive care patients. REGISTRATION This Systematic review and Meta-Analysis was registered in Prospero international prospective register of systemic reviews (CRD42020177095) on April 9/2020.


Global, regional, and national under-5 mortality, adult mortality, age-specific mortality, and life expectancy, 1970-2016: a systematic analysis for the Global Burden of Disease Study 2016.

Abstract: BACKGROUND Detailed assessments of mortality patterns, particularly age-specific mortality, represent a crucial input that enables health systems to target interventions to specific populations. Understanding how all-cause mortality has changed with respect to development status can identify exemplars for best practice. To accomplish this, the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) estimated age-specific and sex-specific all-cause mortality between 1970 and 2016 for 195 countries and territories and at the subnational level for the five countries with a population greater than 200 million in 2016. METHODS We have evaluated how well civil registration systems captured deaths using a set of demographic methods called death distribution methods for adults and from consideration of survey and census data for children younger than 5 years. We generated an overall assessment of completeness of registration of deaths by dividing registered deaths in each location-year by our estimate of all-age deaths generated from our overall estimation process. For 163 locations, including subnational units in countries with a population greater than 200 million with complete vital registration (VR) systems, our estimates were largely driven by the observed data, with corrections for small fluctuations in numbers and estimation for recent years where there were lags in data reporting (lags were variable by location, generally between 1 year and 6 years). For other locations, we took advantage of different data sources available to measure under-5 mortality rates (U5MR) using complete birth histories, summary birth histories, and incomplete VR with adjustments; we measured adult mortality rate (the probability of death in individuals aged 15-60 years) using adjusted incomplete VR, sibling histories, and household death recall. We used the U5MR and adult mortality rate, together with crude death rate due to HIV in the GBD model life table system, to estimate age-specific and sex-specific death rates for each location-year. Using various international databases, we identified fatal discontinuities, which we defined as increases in the death rate of more than one death per million, resulting from conflict and terrorism, natural disasters, major transport or technological accidents, and a subset of epidemic infectious diseases; these were added to estimates in the relevant years. In 47 countries with an identified peak adult prevalence for HIV/AIDS of more than 0·5% and where VR systems were less than 65% complete, we informed our estimates of age-sex-specific mortality using the Estimation and Projection Package (EPP)-Spectrum model fitted to national HIV/AIDS prevalence surveys and antenatal clinic serosurveillance systems. We estimated stillbirths, early neonatal, late neonatal, and childhood mortality using both survey and VR data in spatiotemporal Gaussian process regression models. We estimated abridged life tables for all location-years using age-specific death rates. We grouped locations into development quintiles based on the Socio-demographic Index (SDI) and analysed mortality trends by quintile. Using spline regression, we estimated the expected mortality rate for each age-sex group as a function of SDI. We identified countries with higher life expectancy than expected by comparing observed life expectancy to anticipated life expectancy on the basis of development status alone. FINDINGS Completeness in the registration of deaths increased from 28% in 1970 to a peak of 45% in 2013; completeness was lower after 2013 because of lags in reporting. Total deaths in children younger than 5 years decreased from 1970 to 2016, and slower decreases occurred at ages 5-24 years. By contrast, numbers of adult deaths increased in each 5-year age bracket above the age of 25 years. The distribution of annualised rates of change in age-specific mortality rate differed over the period 2000 to 2016 compared with earlier decades: increasing annualised rates of change were less frequent, although rising annualised rates of change still occurred in some locations, particularly for adolescent and younger adult age groups. Rates of stillbirths and under-5 mortality both decreased globally from 1970. Evidence for global convergence of death rates was mixed; although the absolute difference between age-standardised death rates narrowed between countries at the lowest and highest levels of SDI, the ratio of these death rates-a measure of relative inequality-increased slightly. There was a strong shift between 1970 and 2016 toward higher life expectancy, most noticeably at higher levels of SDI. Among countries with populations greater than 1 million in 2016, life expectancy at birth was highest for women in Japan, at 86·9 years (95% UI 86·7-87·2), and for men in Singapore, at 81·3 years (78·8-83·7) in 2016. Male life expectancy was generally lower than female life expectancy between 1970 and 2016, and the gap between male and female life expectancy increased with progression to higher levels of SDI. Some countries with exceptional health performance in 1990 in terms of the difference in observed to expected life expectancy at birth had slower progress on the same measure in 2016. INTERPRETATION Globally, mortality rates have decreased across all age groups over the past five decades, with the largest improvements occurring among children younger than 5 years. However, at the national level, considerable heterogeneity remains in terms of both level and rate of changes in age-specific mortality; increases in mortality for certain age groups occurred in some locations. We found evidence that the absolute gap between countries in age-specific death rates has declined, although the relative gap for some age-sex groups increased. Countries that now lead in terms of having higher observed life expectancy than that expected on the basis of development alone, or locations that have either increased this advantage or rapidly decreased the deficit from expected levels, could provide insight into the means to accelerate progress in nations where progress has stalled. FUNDING Bill & Melinda Gates Foundation, and the National Institute on Aging and the National Institute of Mental Health of the National Institutes of Health.


Mortality rate and gender differences in COVID-19 patients dying in Italy: A comparison with other countries.


COVID-19 mortality rates in the European Union, Switzerland, and the UK: effect of timeliness, lockdown rigidity, and population density.

Abstract: BACKGROUND To date the European experience with COVID-19 mortality has been different to the observed in China and Asia. We aimed to forecast mortality trends in the 27 countries of the European Union (EU), plus Switzerland and the United Kingdom (UK), where lockdown dates and confinement interventions have been heterogeneous, and to explore its determinants. METHODS We have adapted our predictive model of COVID-19-related mortality, which rested on the observed mortality within the first weeks of the outbreak and the date of the respective lockdown in each country. It was applied in a training set of three countries (Italy, Germany and Spain), and then applied to the EU plus the UK and Switzerland. In addition, we explored the effects of timeliness and rigidity of the lockdown (on a five-step scale) and population density in our forecasts. We report r2, and percent variation of expected versus observed deaths, all following TRIPOD guidance. RESULTS We identified a homogeneous distribution of deaths, and found a median of 24 days after lockdown adoption to reach the maximum daily deaths. Strikingly, cumulative deaths up to April 25th, 2020 observed in Europe separated countries in three waves, according to the time lockdown measures were adopted following the onset of the outbreak: after a week, within a week, or even prior to the outbreak (r2=0.876). In contrast, no correlation neither with lockdown rigidity nor population density were observed. CONCLUSIONS The European experience confirms that early, effective interventions of 86 lockdown are fundamental to minimizing the COVID-19 death toll.


Mortality Rates of Patients with Proximal Femoral Fracture in a Worldwide Pandemic: Preliminary Results of the Spanish HIP-COVID Observational Study.

Abstract: BACKGROUND The outbreak of coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2), in December 2019 in Wuhan, People's Republic of China, has developed into an unprecedented pandemic with enormous pressure on health-care providers around the world. A higher mortality rate has been described in older infected individuals. Patients with hip fracture are a particularly vulnerable population during this pandemic because older age is associated with a higher mortality rate. Our aim was to describe the early mortality rate and demographic variables in a hip fracture sample population in Spain during the coronavirus pandemic. METHODS This is a multicenter, observational, retrospective, descriptive study. We collected data from 13 major hospitals in Spain from the beginning of the national state of alarm (declared on March 14, 2020, by the Spanish government) until the end of our study period on April 4, 2020. All patients who were ≥65 years of age, presented to the Emergency Department of the participating hospitals during this period with a diagnosis of proximal femoral fracture, and had a minimum follow-up of 10 days were included in the cohort. In addition to mortality, demographic and other potential prognostic variables were also collected. RESULTS In this study, 136 patients with a hip fracture were included. Of these patients, 124 underwent a surgical procedure and 12 were managed nonoperatively. The total mortality rate was 9.6%. Sixty-two patients were tested for COVID-19, with 23 patients being positive. The mortality rate for these 23 patients was 30.4% (7 of 23 patients) at a mean follow-up of 14 days. The mortality rate was 10.3% (4 of 39) for patients who had been tested and had a negative result and 2.7% (2 of 74) for patients who had not been tested. Of the 12 patients who were managed nonoperatively, 8 (67%) died, whereas, of the 124 patients who were surgically treated, 5 (4%) died. Results differed among centers. CONCLUSIONS There is a higher mortality rate in patients with a hip fracture and an associated positive test for COVID-19. LEVEL OF EVIDENCE Prognostic Level IV. See Instructions for Authors for a complete description of levels of evidence.


Assumptions for disparities in case-fatality rates of coronavirus disease (COVID-19) across the globe.

Abstract: In a short span, Coronavirus disease (COVID-19) has become the world pandemic by rapidly spreading almost to all the countries around the globe, irrespective of the continent, population size, economic status and healthcare system. Despite the number of cases increasing exponentially in most of the countries, there exist certain disparities in terms of case-fatality rates. As of April 24, 2020, the case-fatality rate of COVID-19 is about 7.0%, with 193,671 deaths and 2,761,121 confirmed cases around the world. Although the United States of America (USA), Spain, Italy, France, and Germany are the top-most affected counties in terms of confirmed cases; France, Italy and Spain are leading the list in terms of case-fatality rates. Therefore, through this mini-review, authors sought to brief on possible assumptions (five D's) that might contribute to the varying case-fatality rates among different countries across the globe.


Covid-19: Cancer mortality could rise at least 20% because of pandemic, study finds.


COVID-19 death rates by age and sex and the resulting mortality vulnerability of countries and regions in the world

Abstract: The growing number of series on COVID-19 deaths classified by age and sex, released by national health authorities, has allowed us to compute age and sex patterns of its mortality, based on 183,619 deaths from Western Europe and the USA. We highlight the specific age schedule of COVID-19 mortality and its pronounced excess male mortality and we then apply these COVID-19 death rates to world populations, in 2020. Our results underscore that considerable variations exist between world regions, as concerns the potential impact of COVID-19 mortality, because of their demographic structures. When compared to younger countries in Sub-Saharan Africa, the vulnerability to COVID-19 mortality is shown to be 17 times higher in several industrialized countries of East Asia and Europe. There is a high correlation (r2= .44) between demographic vulnerability to COVID-19 mortality and current COVID-19 death rates.


A statistical forecast of LOW mortality and morbidity due to COVID-19, in ARGENTINA and other Southern Hemisphere countries.

Abstract: A set of open source programs in Python is devised to fit a parametric integrated Gaussian equation to cumulative deaths due to COVID-19 in Southern Hemisphere countries. The programs were successfully tested using data from advanced outbreak trajectories (Italy and Spain). The procedure was applied to data reported by Argentina. The projected total death toll will be 182 (277-182) with a peak of deaths (6(+/-2)) the 14 of April. The outbreak begins the 9th of March and end completely the 20th of May. However, already on 1st of May, 2 s (95.45%) of the deaths have occurred. The death toll arises from a number of infected individuals between 36412 and 2275. Then, they were to use to process data from several Southern Hemisphere countries: Argentina, Brazil, Mexico, Peru, Colombia, Ecuador, Cuba, Chile, Panama, Australia, Bolivia, Honduras, New Zealand, Paraguay, Guatemala, Venezuela, Uruguay, El Salvador, Jamaica, Haiti, Costa Rica and Nicaragua. The trend is to show low number of total deaths compared with other disease outbreaks. A total projected number of deaths between 15148 and 9939 deaths for a total population of ca. 664 M inhabitants. The projected death toll is much lower (5-10 times) than those forecasted by the Imperial College Group (ICG) even considering the best scenario of total suppression of virus transmission. Using actual mortality rates it is possible to back calculate which number of infected individuals would produce such mortality. The calculated number of infected individuals (worst case scenario) is below 2.5 million. This is significantly lower than that calculated by ICG (> 45 millions). In most countries the outbreak will end in May or early June. The dynamics of the outbreaks seems to do not saturate the health services (hospital beds) but only Peru, Ecuador and Panama should have not enough ICU beds for grave COVID-19 patients


Estimating the Size of High-risk Populations for COVID-19 Mortality across 442 US Cities

Abstract: A variety of predisposing factors have been associated with serious illness and death from COVID-19. Understanding the distribution of risks associated with these factors by local communities can provide important opportunities for targeting interventions. We characterize the distribution of risk for COVID-19 mortality for populations at large across 442 US cities, by utilizing recently published estimates of risk associated with age, gender, ethnicity, social deprivation and 12 health conditions from a very large UK-based study, combined with the information available on prevalence and co-occurrence of these factors in the US through a variety of population-based public databases. We estimate that across all the cities, an underlying weighted risk-score can identify a total of approximately 12.65 million, 4.09 million and 1.34 million individuals who are at 2-, 5- and 10-fold higher risk, respectively, compared to the average risk for the US population. The percentage of population which exceed the respective risk thresholds varies across the cities in the range (1st-99th percentile), 3.6%-20.1%, 0.7%-8.0% and 0.1%-3.2%, respectively. The percentage of deaths within a city that are expected to occur above these risk-thresholds varies in the range of 20.1%-53.5%, 8.5%-38.2% and 2.9%-25.4%, respectively. Our analysis can provide guidance to national and local policy makers regarding resources needed to protect the most vulnerable populations in these communities, and how much utility such interventions may have in reducing the total population burden of death.


The lower COVID-19 related mortality and incidence rates in Eastern European countries are associated with delayed start of community circulation

Abstract: Background: The purpose of this analysis was to assess the variations in COVID-19 related mortality and incidence rates in relation to the time differences in the commencement of virus circulation and containment measures in different countries of the European Region. Methods: The data for the current analysis (N=50 countries) were retrieved from the John Hopkins University dataset on the 7th of May 2020, with countries as study units. A piecewise regression analysis was conducted with mortality and cumulative incidence rates introduced as dependent variables and time interval (days from the 22nd of January to the date when 100 first cases were reported) as the main predictor. The country average life expectancy at birth was statistically adjusted for in the regression model. Results: Mortality and incidence were strongly and inversely intercorrelated with days from January 22, respectively -0.83 (p<.0001) and -0.73 (p<.0001). Adjusting for average life expectancy, between days 33 to 50 from the 22th of the January, the average mortality rate decreased by 30.4/million per day (95% CI: 23.2, 37.1, p<0.0001). During interval 51 to 73 days, the change in mortality was no longer statistically significant but still showed a decreasing trend. A similar relationship with time interval was found in incidence. Life expectancy was not associated with mortality rate. Conclusion: Countries in Europe which observed the earliest COVID-19 circulation, suffered the worst consequences in terms of health outcomes, specifically mortality. The drastic social isolation measures, undertaken especially in Eastern European countries, where community circulation started after March 11th, may have been timely. This may explain their significantly lower COVID-related mortality compared with the Western European countries.


COVID-19: Spatial Analysis of Hospital Case-Fatality Rate in France

Abstract: When the population risk factors and reporting systems are similar, the assessment of the case-fatality (or lethality) rate (ratio of cases to deaths) represents a perfect tool for analyzing, understanding and improving the overall efficiency of the health system. The objective of this article is to estimate the influence of the hospital care system on lethality in metropolitan France during the inception of the COVID-19 epidemic, by analyzing the spatial variability of the hospital case-fatality rate between French districts. The results show that the higher case-fatality rates observed in certain districts are mostly related to the level of morbidity in the district, therefore to the overwhelming of the healthcare systems during the acute phases of the epidemic. However, the magnitude of this increase of case-fatality rate represents less than 10 per cent of the average case-fatality rate and cannot explain the magnitude of the variations in case-fatality rate reported by country by international organizations or information sites. These differences can only be explained by the systems for reporting cases and deaths, which, indeed, vary greatly from country to country, and not attributed to the care or treatment of patients, even during hospital stress due to epidemic peaks.


Estimating Lower Bounds for COVID-19 Mortality from Northern Italian Towns

Abstract: For COVID-19 the Infection Fatality Rate or IFR - a crucial variable in epidemiological modeling - is difficult to estimate because many cases are asymptomatic and the overall infection rate is generally not known. Circumstances in the Italian provinces of Milano, Bergamo, Brescia, and Lodi allow estimation of lower bounds for age- and sex-specific all-cause excess mortality (a proxy for IFR) since anecdotal reports indicate some towns were close to fully infected. Using data from ISTAT on mortality from January 1 through April 15 for 2020 and the three preceding years, I estimate excess mortality by sex and age categories (0-14, 15-54, 55-64, 65-74, and 75+ years) while controlling for town-specific mortality that proxies for town-specific infection rate. The 99th percentile from the tail of the town distribution gives a lower-bound estimate for COVID-19 mortality. The overall population-weighted mortality at the 99th percentile is 1.09 percent (95% CI 1.06-1.14). The age- and sex-specific rates vary considerably: for men age 65-74 the estimate is 2.10 percent (95% CI 1.94-2.28) which is 3.5-times higher than men 55-64 and 2.7-times higher than women 65-74.


BCG vaccination and socioeconomic variables vs Covid-19 global features: clearing up a controversial issue

Abstract: Background: The Covid-19 pandemic is characterized by extreme variability in the outcome distribution and mortality rates across different countries. Some recent studies suggested an inverse correlation with BCG vaccination at population level, while others denied this hypothesis. In order to address this controversial issue, we performed a strict epidemiological study collecting data available on a global scale, considering additional variables such as cultural-political factors and adherence to other vaccination coverages. Methods: Data on 121 countries, accounting for about 99% of Covid-19 cases and deaths globally, were from John's Hopkins Coronavirus Resource Center, World Bank, International Monetary Fund, United Nations, Human Freedom Report, and BCG Atlas. Statistical models used were Ordinary Least Squares, Tobit and Fractional Probit, implemented on Stata/MP16 software. Results: Based on our results, countries where BCG vaccination is or has been mandated in the last decades have seen a drastic reduction in Covid-19 diffusion (-80% on average) and mortality (-50% on average), even controlling for relative wealth of countries and their governmental health expenditure. A significant contribution to this reduction (respectively -50% and -13% on average) was also associated to the outbreak onset during summer, suggesting a possible influence of seasonality. Other variables turned out to be associated, though to a lesser extent. Conclusions: Relying on a very large dataset and a wide array of control variables, our study confirms a strong and robust association between Covid-19 diffusion and mortality with BCG vaccination and a set socio-economic factors, opening new perspectives for clinical speculations and public health policies.


COVID-19 Pandemic: Marked Global Disparities in Fatalities According to Geographic Location and Universal Health Care

Abstract: Since its outbreak, COVID-19 pandemic has been the biggest global concern with exponentially increasing number of cases and associated deaths across all habitable continents Various countries around the world with their diverse health care systems, have responded to the pandemic in very distinctive ways In this paper, we: compared COVID-19 mortality rates across global geographic regions;and assessed differences in COVID-19-related case fatality rate (CFR) based on presence or absence of Universal Health Coverage (UHC) We found that as of May 6, 2020, Europe had experienced the highest CFR globally of 9 6%, followed by 5 9% in North America Although the pandemic originated in Asia, the continent ranked second to the last in terms of CFR (3 5%) Countries with UHC had lower number of cases of 37 6%, but the CFR of countries with UHC was twice that of countries without UHC (10 5% versus 4 9%) In conclusion, UHC does not appear to protect against mortality in a pandemic environment such as with COVID-19


The COVID-19 mortality effects of underlying health conditions in India: a modelling study

Abstract: Objective: To model how known COVID-19 comorbidities will affect mortality rates and the age distribution of mortality in a large lower middle income country (India), as compared with a high income country (England), and to identify which health conditions drive any differences. Design: Modelling study. Setting: England and India. Participants: 1,375,548 respondents aged 18 to 99 to the District Level Household Survey-4 and Annual Health Survey in India. Additional information on health condition prevalence on individuals aged 18 to 99 was obtained from the Health Survey for England and the Global Burden of Diseases, Risk Factors, and Injuries Studies (GBD). Main outcome measures: The primary outcome was the proportional increase in age-specific mortality in each country due to the prevalence of each COVID-19 mortality risk factor (diabetes, hypertension, obesity, chronic heart disease, respiratory illness, kidney disease, liver disease, and cancer, among others). The combined change in overall mortality and the share of deaths under 60 from the combination of risk factors was estimated in each country. Results: Relative to England, Indians have higher rates of diabetes (10.6% vs. 8.5%), chronic respiratory disease (4.8% vs. 2.5%), and kidney disease (9.7% vs. 5.6%), and lower rates of obesity (4.4% vs. 27.9%), chronic heart disease (4.4% vs. 5.9%), and cancer (0.3% vs. 2.8%). Population COVID-19 mortality in India relative to England is most increased by diabetes (+5.4%) and chronic respiratory disease (+2.3%), and most reduced by obesity (-9.7%), cancer (-3.2%), and chronic heart disease (-1.9%). Overall, comorbidities lower mortality in India relative to England by 9.7%. Accounting for demographics and population health explains a third of the difference in share of deaths under age 60 between the two countries. Conclusions: Known COVID-19 health risk factors are not expected to have a large effect on aggregate mortality or its age distribution in India relative to England. The high share of COVID-19 deaths from people under 60 in low- and middle-income countries (LMICs) remains unexplained. Understanding mortality risk associated with health conditions prevalent in LMICs, such as malnutrition and HIV/AIDS, is essential for understanding differential mortality. Keywords: COVID-19, India, low- and middle-income countries, comorbidity


Estimating the real-time case fatality rate of COVID-19 using Poisson mixtures model

Abstract: Importance: The case fatality rate (CFR) estimation during the early stage of a disease outbreak is important, but the current estimation methods are heavily biased. Objective: We proposed using a Poisson mixtures model that utilized requires data of deaths, recoveries, and total confirmed cases recorded in each day since the outbreak of a population. Design: We collected data of deaths, recoveries, and total confirmed cases of COVID-19 in Hubei Province, China, and other parts of China up to 10th April 2020. Main Outcome(s) and Measure(s): The CFR of COVID-19 was estimated by minimizing the chi-square goodness-of-fit statistic. Results: Our proposed CRF estimates for Hubei Province became stable on 5th February in the range of 4.5% to 7.0% at which the simple CFR estimators overestimated the actual CFR by more than five folds, and that for the other parts of China (1.5% to 1.6%) were all very close to the actual CFR on the first day of CFR estimation (25th January) at which the simple CFRs were in the range between 15% and 35%. Conclusions and Relevance: Our CFR estimates for Hubei Province and other parts of China were superior to the simple CFR estimators.


Patterns of COVID-19 related excess mortality in the municipalities of Northern Italy

Abstract: The Coronavirus Disease 2019 (COVID-19) spatial distribution in Italy is inhomogeneous, because of its ways of spreading from the initial hotspots. The impact of COVID-19 on mortality has been described at the regional level, while less is known about mortality in demographic subgroups within municipalities. We aimed to describe the excess mortality (EM) due to COVID-19 in the three most affected Italian regions, by estimating EM in subgroups defined by gender and age classes within each municipality from February 23 to March 31, 2020. EM varied widely among municipalities even within the same region; it was similar between genders for the [≥]75 age group, while in the other age groups it was higher in males. Thus, nearby municipalities may show a different mortality burden despite being under common regional health policies, possibly as a result of policies adopted both at the regional and at the municipality level.


COVID-19 FATALITY RISK: WHY IS AUSTRALIA LOWER THAN SOUTH KOREA?

Abstract: Background: As the Covid-19 virus epidemic spreads, it is important to establish reliable estimates of fatality hazard rates. Australia and South Korea are ideal candidates for detailed consideration. Both have completed the first wave of the epidemic, they have extensive Covid-19 testing and tracking programs so that confirmed case load data are reliable, and neither country has had any significant case load stress in their hospital systems. Methods: For each country, mortality hazard models were estimated using a parameterized distributed lag model where the number of daily deaths was dependent on the number of confirmed cases in each of the preceding six weeks. Age cohort CFRs were also examined. Findings: We observed major difference in the mortality rates when comparing South Korea to Australia in both the simple age adjusted fatality rates and in the disease hazard curve. On a like-for-like basis, the CFR for South Korea appears to be close to double the Australian rate (aggregate; 2.4% vs 1.4%). Interpretation: Neither differences in the time pattern of the peaking of the case load of confirmed cases, nor differences in the size of age cohorts of confirmed cases explain the difference in mortality observed. We discuss possible explanations that point the way for further investigation. Funding: nil.


Evaluating the determinants of COVID-19 mortality: A cross-country study

Abstract: As the COVID-19 pandemic has spread to the entire world, a race to understand the virus and to find an effective and safe vaccine or treatment has triggered interest in the factors contributing to mortality. For instance, some studies have suggested that the BCG vaccine could protect from COVID-19 and nicotine patches could be therapeutic against the virus. This study makes use of data for about 140 countries to evaluate the determinants of COVID-19 mortality. It finds that a country's share of spending on health care (as a measure of a country's effectiveness in tracking, recording, and reporting COVID-19 deaths) is positively associated with COVID-19 deaths. It also finds that the share of people above 65 years of age, obesity, and urbanization are all positively associated with COVID-19 mortality. There is no evidence that BCG vaccination, smoking prevalence, and PM25 pollution have any link to COVID-19 mortality. These estimation results are robust to alternative specifications and after controlling for confounding factors and excluding outliers. Policymakers should allocate resources towards the protection of the elderly and those suffering from underlying conditions such as obesity. They should also exercise caution about administering nicotine patches or the BCG vaccine to fight COVID-19 without the backing of concrete scientific evidence.


Associations of Global Country Profiles and Modifiable Risk Factors with COVID-19 Cases and Deaths

Abstract: Modifiable risk factors affect SARS-CoV-2 infection and mortality raising the possibility that lifestyle modification could play a role. This has not been studied at a global level. We analysed publicly available data from countries reporting COVID-19 cases and deaths. Associations of modifiable risk factors with total cases and excess deaths were determined with and without adjustment for confounders. 4,670,832 cases and 311,384 deaths were reported by 181 countries by 18th May 2020. Wealthier countries had the greatest caseload. Obesity was the primary modifiable risk factor for infection and greater age, male sex, physical inactivity and low salt consumption were associated with excess deaths. Obesity was less influential on mortality than physical inactivity. Globally, obesity confers vulnerability to SARS-CoV-2 infection and physical inactivity likely explains the greater mortality in the obese. High salt consumption may induce reductions in tissue ACE2 expression and subsequently reduce mortality rates.


Covid-19 and Population Age Structure

Abstract: Epidemiological studies suggest that age distribution of a population has a non-trivial effect on how morbidity rates, mortality rates and case fatality rates (CFR) vary when there is an epidemic or pandemic. We look at the empirical evidence from a large cohort of countries to see the sensitivity of Covid-19 data to their respective median ages. The insights that emerge could be used to control for age structure effects while investigating other factors like cross-protection, co-morbidities, etc.


Why Do COVID-19 Fatality Rates Differ Across Countries? An Explorative Cross-country Study Based on Select Indicators

Abstract: In this article, we analyse the factors that determine the fatality rates across 29 economies spread across both the developing and developed world. Recent emerging literature and expert opinions in popular media have indicated various factors that may explain cross-country difference in fatality rates. These factors range from access to public health infrastructure, BCG vaccination policies, demographic structure, restrictive policy interventions and the weather. In addition, articles are examining different kinds of fatality rates that can be explained. Progressing beyond fragmented databases and anecdotal evidence, we have developed a database for such factors, have explored various econometric models to test the explanatory power of these factors in explaining several kinds of fatality rates. Based on available data, our study reveals that factors such as public health system, population age structure, poverty level and BCG vaccination are powerful contributory factors in determining fatality rates. Interactions between factors such as poverty level and BCG vaccination provide interesting insights into the complex interplay of factors. Our analysis suggests that poor citizens’ access to the public healthcare system are worse in many countries irrespective of whether they are developed or developing countries.


Scaling COVID-19 against inequalities: should the policy response consistently match the mortality challenge?

Abstract: Background The mortality impact of COVID-19 has thus far been described in terms of crude death counts. We aimed to calibrate the scale of the modelled mortality impact of COVID-19 using age-standardised mortality rates and life expectancy contribution against other, socially-determined, causes of death in order to inform governments and the public. Methods We compared mortality attributable to suicide, drug poisoning and socioeconomic inequality with estimates of mortality from an infectious disease model of COVID-19. We calculated age-standardised mortality rates and life expectancy contributions for the UK and its constituent nations. Results Mortality from a fully unmitigated COVID-19 pandemic is estimated to be responsible for a negative life expectancy contribution of -5.96 years for the UK. This is reduced to -0.33 years in the fully mitigated scenario. The equivalent annual life expectancy contributions of suicide, drug poisoning and socioeconomic inequality-related deaths are -0.25, -0.20 and -3.51 years respectively. The negative impact of fully unmitigated COVID-19 on life expectancy is therefore equivalent to 24 years of suicide deaths, 30 years of drug poisoning deaths, and 1.7 years of inequality-related deaths for the UK. Conclusion Fully mitigating COVID-19 is estimated to prevent a loss of 5.63 years of life expectancy for the UK. Over 10 years there is a greater negative life expectancy contribution from inequality than around six unmitigated COVID-19 pandemics. To achieve long-term population health improvements it is therefore important to take this opportunity to introduce post-pandemic economic policies to build back better.


A County-Level Susceptibility Index and Coronavirus Disease 2019 Mortality in the United States: A Socioecological Study

Abstract: As of June 2020, the United States (US) has experienced the highest number of deaths related to coronavirus disease 2019 (Covid-19) in the world, but significant geographic heterogeneity exists at the county-level. Therefore, we sought to classify counties in the United States across multiple domains utilizing a socioecological framework and examine the association between these county-level groups and Covid-19 mortality. We harmonized and linked county-level sociodemographic, health, and environmental metrics associated with increased susceptibility for Covid-19 mortality. Latent class analysis defined a county-level susceptibility index (CSI) based on these metrics (n=2701 counties). Next, we used linear regression models to estimate the associations of the CSI and Covid-19 deaths per capita and initial mortality doubling time (as of 6/2/20), adjusted for days since first Covid-19 case. We identified 4 groups classified by the CSI with distinct sociodemographic, health, and environmental profiles and widespread geographic dispersion. Covid-19 deaths per capita were significantly higher in the group consisting of rural, vulnerable counties (55.8 [95% CI 50.3-61.2] deaths per 100,000) compared with the group with diverse, urban counties (32.2 [27.3-37.0]) at similar points in the outbreak (76 days since first case). Our findings can inform equitable resource allocation for Covid-19 to allow targeted public health preparedness and response in vulnerable counties.


Municipality- level predictors of COVID-19 mortality in Mexico: a cautionary tale

Abstract: Background. Inequalities and burden of comorbidities of the Coronavirus disease 2019 (COVID-19) vary importantly inside the countries. We aimed to analyze the Municipality-level factors associated with a high COVID-19 mortality rate of in Mexico. Methods. We retrieved information from 142,643 cumulative confirmed symptomatic cases and 18,886 deaths of COVID-19 as of June 20th, 2020 from the publicly available database of the Ministry of Health of Mexico. Public official data of the most recent census and surveys of the country were used to adjust a negative binomial regression model with the quintiles (Q) of the distribution of sociodemographic and health outcomes among 2,457 Municipality-level. Expected Mortality Rates (EMR), Incidence Rate Ratios (IRR) and 95% Confidence Intervals are reported. Results. Factors associated with high MR of COVID-19, relative to Quintile 1 (Q1), were; diabetes prevalence (Q4, IRR=2.60), obesity prevalence (Q5, IRR=1.93), diabetes mortality rate (Q5, IRR=1.58), proportion of indigenous population (Q2, IRR=1.68), proportion of economically active population (Q5, IRR=1.50), density of economic units that operate essential activities (Q4, IRR=1.54) and population density (Q5, IRR=2.12). We identified 1,351 Municipality-level without confirmed COVID-19 deaths, of which, 202 had nevertheless high (Q4, Mean EMR= 8.0 deaths per 100,000) and 82 very high expected COVID-19 mortality (Q5, Mean EMR= 13.8 deaths per 100,000). Conclusion. This study identified 1,351 Municipality-level of Mexico that, in spite of not having confirmed COVID-19 deaths yet, share characteristics that could eventually lead to a high mortality scenario later in the epidemic and warn against premature easing of mobility restrictions. Local information should be used to reinforce strategies of prevention and control of outbreaks in communities vulnerable to COVID-19. Keywords: COVID-19; risk factors; social determinants; health determinants; Municipality-level; counties.


Risk factors associated with mortality of COVID-19 in 2692 counties of the United States

Abstract: Background: The number of cumulative confirmed cases of COVID-19 in the United States has risen sharply since March. A county health ranking and roadmaps program has been established to identify factors associated with disparity in mobility and mortality of COVID-19 in all counties in the United States. Objective: To find out the risk factors associated with mortality of COVID-19 with various levels of prevalence. Design: A negative binomial design was applied to the county-level mortality counts of COVID-19 on April 15, 2020 in the United States. In this design, the infected counties were categorized into three levels of infections using clustering analysis based on time-variant cumulative confirmed cases from March 1 to April 15, 2020. Setting: United States Participants: COVID-19 patients in various counties of the United States from March 1 to April 15, 2020. Measurements: The county-level cumulative confirmed cases and mortality of COVID-19. Results. 2692 infected counties were assigned into three classes where the mild, moderate, and severe prevalence of infections were identified, respectively. Several risk factors are significantly associated with the mortality of COVID-19, where Hispanic (0.024, P=0.002), female (0.253, P=0.027), elder (0.218, P=0.017) and Native Hawaiian or other Pacific islander (2.032, P=0.027) individuals are more vulnerable to the mortality of COVID-19. More locations open to exercise (0.030, P=0.004), higher levels of air pollution (0.184, P=0.044), and segregation between non-White and White increased the mortality rate. Limitation: The study relied on mortality data on April 15, 2020. Conclusion. The mortality of COVID-19 depends on sex, ethnicity, and outdoor environment. The increasing awareness of these significant factors may lead to the reduction in the mortality rate of COVID-19.


Correlation Analysis Between Disease Severity and Inflammation-related Parameters in Patients with COVID-19 Pneumonia

Abstract: Aim: The new coronavirus pneumonia (COVID-19) outbreaking at the end of 2019 is highly contagious. Crude mortality rate reached 49% in critical patients. Inflammation matters on disease progression. This study analyzed blood inflammation indicators among mild, severe and critical patients, helping to identify severe or critical patients early. Methods: In this cross-sectional study, 100 patients were included and divided to mild, severe or critical groups. Correlation of peripheral blood inflammation-related indicators with disease criticality was analyzed. Cut-off values for critically ill patients were speculated through the ROC curve. Results：Significantly, disease severity were associated with age (R=-0.564, P<0.001), interleukin-2 receptor (IL2R) (R=-0.534, P<0.001), interleukin-6 (IL-6) (R=-0.535, P<0.001), interleukin-8 (IL-8) (R=-0.308, P<0.001), interleukin-10 (IL-10) (R=-0.422, P<0.001), tumor necrosis factor α (TNFα) (R=-0.322, P<0.001), C-reactive protein (CRP) (R=-0.604, P<0.001), ferroprotein (R=-0.508, P<0.001), procalcitonin (R=-0.650, P<0.001), white cell counts (WBC) (R=-0.54, P<0.001), lymphocyte counts (LC) (R=-0.56, P<0.001), neutrophil count (NC) (R=-0.585, P<0.001) and eosinophil counts (EC) (R=-0.299, P=0.01). Conclusion：With following parameters such as age >67.5 years, IL2R >793.5U/mL, CRP >30.7ng/mL, ferroprotein >2252μg/L, WBC>9.5*10^9/L or NC >7.305*10^9/L, the progress of COVID-19 to critical stage should be closely observed and possibly prevented. Inflammation is closely related to severity of COVID-19, and IL-6, TNFα and IL-8 might be promising therapeutic targets.


Ethnicity and risk of death in patients hospitalised for COVID-19 infection: an observational cohort study in an urban catchment area

Abstract: Objectives. To determine if specific ethnic groups are at higher risk of mortality from COVID19 infection. Design. Retrospective cohort study Setting. University Hospitals Birmingham NHS Foundation Trust (UHB) in Birmingham, UK Participants. Patients with confirmed SARS CoV 2 infection requiring admission to UHB between 10th March 2020 and 17th April 2020 Exposure. Ethnicity Main outcome measures. Standardised Admission Ratio (SAR) and Standardised Mortality Ratio (SMR) for each ethnicity was calculated using observed sex specific age distributions of COVID19 admissions/deaths and 2011 census data for Birmingham/Solihull. Hazard Ratio (aHR) for mortality was estimated for each ethnic group with white population as reference group, using Cox proportional hazards model adjusting for age, sex, social deprivation and co-morbidities, and propensity score matching. Results. 2217 patients admitted to UHB with a proven diagnosis of COVID19 were included. 58.2% were male, 69.5% White and the majority (80.2%) had co morbidities. 18.5% were of South Asian ethnicity, and these patients were more likely to be younger (median age 61 years vs.77 years), have no co morbidities (27.8% vs. 16.6%) but a higher prevalence of diabetes mellitus (48.0% vs 28.2%) than White patients. SAR and SMR suggested more admissions and deaths in South Asian patients than would be predicted. South Asian patients were also more likely to present with severe disease despite no delay in presentation since symptom onset. South Asian ethnicity was associated with an increased risk of death; both by Cox regression (Hazard Ratio 1.66 (95%CI 1.32 to 2.10)) after adjusting for age, sex, deprivation and comorbidities and by propensity score matching, (Hazard ratio 1.68 (1.33 to 2.13), using the same factors but categorising ethnicity into South Asian or not. Conclusions. Current evidence suggests those of South Asian ethnicity may be at risk of worse COVID19 outcomes, further studies need to establish the underlying mechanistic pathways.


Epidemiological Determinants of Acute Respiratory Syndrome Coronavirus-2 Disease Pandemic and The Role of the Bacille-Calmette-Guerin Vaccine in Reducing Morbidity and Mortality

Abstract: This study analyzed the determinants of morbidity, mortality, and case fatality rate (CFR) of the ongoing pandemic of severe acute respiratory syndrome coronavirus-2 disease 2019 (COVID-19) Data for 210 countries and territories available in public domains were analyzed in relation to mandatory vaccination with Bacille-Calmette-Guerin (BCG), population density, median age of the country population, health care expenditure per capita, life expectancy at birth, healthy life expectancy, literacy rate, per capita gross domestic production adjusted to purchasing power (PPP), burden of tuberculosis (TB), acquired immunodeficiency disease caused by human immunodeficiency virus (HI V-AIDS), malaria, cardiovascular disease (CVD), neoplasm, diabetes, deaths due to energy-protein (food) deficiency (EPD), and per capita government spending on safe water and sanitation Mandatory BCG vaccination showed a highly significant (p<0 0001) negative correlation with COVID-19 morbidity (r = -0 62) and mortality (r = -0 58) rates, but no significant correlation with CFR The median age of the nation showed a significant (p<0 0001) positive correlation with COVID-19 morbidity (r= 0 40) and mortality (r = 0 34) rates, but no significant correlation with CFR The pandemic resulted in higher morbidity (r= 0 47, p<0 0001) and mortality (r= 0 25, p = 0 01) rates in countries with a higher PPP than in those with a lower PPP COVID-19 CFR and morbidity and mortality rates showed no significant correlation with population density, the burden of malaria or diabetes, or the level of spending on safe water and sanitation Only the burden of TB showed a positive correlation with CFR (r = 0 17, p = 0 05) However, COVID-19 morbidity showed a significant (p =0 05) negative correlation with the burden of TB, HI V-AIDS, CVD, and EPD Mortality and morbidity in COVID-19 patients showed a positive correlation with per capita health expenditure, life expectancy, the burden of neoplasia, and PPP


Early dinner or "dinner like a pauper": Evidence, the habitual time of the largest meal of the day - dinner - is predisposing to severe COVID-19 outcome - death

Abstract: COVID-19 and metabolic syndrome are devastating pandemics. Effective control of metabolic parameters and their dysfunction may help prevent or minimize the acute and devastating effects of SARS-CoV-2 by reducing the local inflammatory response and blocking the entry of the virus into cells. With such consideration in mind, we gathered data from dietary surveys conducted in nine European countries to explore the relationship between actual clock hour of the large dinner meal and also interval in minutes between it and sunset in the respective countries and death rate above the median rate of per one million people as an index of mortality due to COVID-19 infection. Clock time of the dinner meal varied between 16:00 and 21:00 h across the European counties sampled, and the correlation between dinner mealtime and death rate was strongly correlated, R = 0.7991 (two-tailed p = 0.0098), with R 2 explaining 63% of the variation within the data. This strong linear positive correlation indicates that the later the clock time of the dinner meal, the higher is the death rate (and vice versa). The relationship between meal timing in reference to sunset, utilized as a gross surrogate marker of the activity/rest synchronizer of circadian rhythms, and death rate was negative and even slightly stronger, R = -0.8025 (two-tailed p = 0.0092), with R 2 explaining 64% of the variation within the data. This strong linear negative correlation indicates that the shorter the interval between the dinner meal and sunset, i.e., the closer the time of the largest meal of the day to bedtime, the greater is the death rate (and vice versa). Our preliminary approach to nighttime eating, in terms of the day's largest caloric intake, as a risk factor for the predisposing conditions of obesity, metabolic syndrome, type 2 diabetes, and other commonly associated comorbidities of being overweight, and death from COVID-19 infection reveals strong correlation with the time of the dinner meal, both in terms of its actual clock and circadian time.


COVID: How to explain differences in lethality between different populations?


Clinical outcomes of 402 patients with COVID-2019 from a single center in Wuhan, China

Abstract: The outbreak of SARS-CoV-2 has become a pandemic with significant mortality. Published studies described clinical characteristics of the disease contain small cohorts from individual centers or larger series consisting of mixed series from multiple different hospitals. We report here analyses of mortality and disease severity among 402 patients from a single hospital. The cohort includes 297 patients with confirmed and 105 with clinical diagnosis. The latter group consists of cases with inconclusive nucleic acid test but meeting the criteria for clinical diagnosis. Data are compared between sexes and among different age groups. The overall case fatality is 5.2%. However, age at 70 years or older is associated with a significantly higher mortality (17.8%) and higher rate of severe and critical illness (57.5%). Case fatality is 8% in patients 50 years of age or older, and 1.2% in those younger than 50 years. In addition, case fatality is 7.6% in male patients, as opposed to 2.9% in females, demonstrating a clear sex difference.


Demographic science aids in understanding the spread and fatality rates of COVID-19

Abstract: Governments around the world must rapidly mobilize and make difficult policy decisions to mitigate the coronavirus disease 2019 (COVID-19) pandemic. Because deaths have been concentrated at older ages, we highlight the important role of demography, particularly, how the age structure of a population may help explain differences in fatality rates across countries and how transmission unfolds. We examine the role of age structure in deaths thus far in Italy and South Korea and illustrate how the pandemic could unfold in populations with similar population sizes but different age structures, showing a dramatically higher burden of mortality in countries with older versus younger populations. This powerful interaction of demography and current age-specific mortality for COVID-19 suggests that social distancing and other policies to slow transmission should consider the age composition of local and national contexts as well as intergenerational interactions. We also call for countries to provide case and fatality data disaggregated by age and sex to improve real-time targeted forecasting of hospitalization and critical care needs.


Letalidad del COVID-19: ausencia de patrón epidemiológico./ [Case fatality rate of COVID-19: absence of epidemiological pattern]

Abstract: OBJECTIVE: Analyze a set of indicators to understand the variability of the evolution and impact of the COVID-19 epidemic in a set of selected countries. METHOD: Ecological study of a group of countries with more than 200 reported cases. Demographic variables, health expenditure variables, and variables about characteristics of health services were included as explanatory variables. and incidence, mortality and fatality rates have been analyzed as response variables. In addition, a relative fatality index has been created. Data are from international organizations. Spearman's correlation coefficient was used to estimate the magnitude of the associations. RESULTS: Number of tests and of medical professionals are associated with a higher incidence rate. Mortality and case fatality rate are not associated with demographic, health expenditure, or health services variables. CONCLUSION: Differences suggest a general underestimation of the magnitude of the epidemic. Improvement of case identification and effectiveness of epidemiological surveillance systems is necessary.


Acute Physiology and Chronic Health Evaluation II Score as a Predictor of Hospital Mortality in Patients of Coronavirus Disease 2019

Abstract: OBJECTIVES: Coronavirus disease 2019 has emerged as a major global health threat with a great number of deaths in China. We aimed to assess the association between Acute Physiology and Chronic Health Evaluation II score and hospital mortality in patients with coronavirus disease 2019, and to compare the predictive ability of Acute Physiology and Chronic Health Evaluation II score, with Sequential Organ Failure Assessment score and Confusion, Urea, Respiratory rate, Blood pressure, Age 65 (CURB65) score. DESIGN: Retrospective observational cohort. SETTING: Tongji Hospital in Wuhan, China. SUBJECTS: Confirmed patients with coronavirus disease 2019 hospitalized in the ICU of Tongji hospital from January 10, 2020, to February 10, 2020. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Of 178 potentially eligible patients with symptoms of coronavirus disease 2019, 23 patients (12.92%) were diagnosed as suspected cases, and one patient (0.56%) suffered from cardiac arrest immediately after admission. Ultimately, 154 patients were enrolled in the analysis and 52 patients (33.77%) died. Mean Acute Physiology and Chronic Health Evaluation II score (23.23 ± 6.05) was much higher in deaths compared with the mean Acute Physiology and Chronic Health Evaluation II score of 10.87 ± 4.40 in survivors (p < 0.001). Acute Physiology and Chronic Health Evaluation II score was independently associated with hospital mortality (adjusted hazard ratio, 1.07; 95% CI, 1.01-1.13). In predicting hospital mortality, Acute Physiology and Chronic Health Evaluation II score demonstrated better discriminative ability (area under the curve, 0.966; 95% CI, 0.942-0.990) than Sequential Organ Failure Assessment score (area under the curve, 0.867; 95% CI, 0.808-0.926) and CURB65 score (area under the curve, 0.844; 95% CI, 0.784-0.905). Based on the cut-off value of 17, Acute Physiology and Chronic Health Evaluation II score could predict the death of patients with coronavirus disease 2019 with a sensitivity of 96.15% and a specificity of 86.27%. Kaplan-Meier analysis showed that the survivor probability of patients with coronavirus disease 2019 with Acute Physiology and Chronic Health Evaluation II score less than 17 was notably higher than that of patients with Acute Physiology and Chronic Health Evaluation II score greater than or equal to 17 (p < 0.001). CONCLUSIONS: Acute Physiology and Chronic Health Evaluation II score was an effective clinical tool to predict hospital mortality in patients with coronavirus disease 2019 compared with Sequential Organ Failure Assessment score and CURB65 score. Acute Physiology and Chronic Health Evaluation II score greater than or equal to 17 serves as an early warning indicator of death and may provide guidance to make further clinical decisions.


Factors associated with increased all-cause mortality during the COVID-19 pandemic in Italy

Abstract: BACKGROUND: The number of excess deaths in February-March 2020 in Italy, in comparison to the previous years, was considerably higher than recorded COVID19-related deaths. The present study is aimed at exploring the associations of excess mortality with some indices related to the epidemic and its management. METHODS: Data on all-cause mortality from February 20th to March 31st, in years from 2015 to 2020, and demographic, socioeconomic and healthcare organization data of each Italian region were obtained from Italian Institute of Statistics. Non-COVID19-Imputed Excess Mortality (NCIEM) was calculated as the difference between excess 2020 mortality and reported COVID19 mortality. The association of NCIEM with the rate of COVID-19 cases, COVID-19 mortality, and other potential moderators was assessed using linear regression models. RESULTS: The nationwide number of excess deaths, COVID-19 deaths was 26,701 and 13,710, respectively, with a difference of 12,991. NCIEM in different Regions showed a direct correlation with COVID-19 mortality (r2 = 0.61, p < 0.001) and total cases (r2 = 0.30, p = 0.012), and an inverse correlation with cases/total tests ratio (r2 = 0.49, p = 0.001). Direct correlations were also found with the proportion of institutionalized elderly, whereas inverse correlations were observed with prevalence of diabetes, cardiovascular mortality, and density of general practitioners. CONCLUSIONS: The impact of the COVID19 epidemic on all-cause mortality is considerably greater than that indicated by official counts of victims. Limited testing capacity and causes of death other than COVID19 could contribute to the increase in overall mortality rates.


The Correlation of Comorbidities on the Mortality in Patients with COVID-19: an Observational Study Based on the Korean National Health Insurance Big Data

Abstract: BACKGROUND: Mortality of coronavirus disease 2019 (COVID-19) is a major concern for quarantine departments in all countries. This is because the mortality of infectious diseases determines the basic policy stance of measures to prevent infectious diseases. Early screening of high-risk groups and taking action are the basics of disease management. This study examined the correlation of comorbidities on the mortality of patients with COVID-19. METHODS: We constructed epidemiologic characteristics and medical history database based on the Korean National Health Insurance Service Big Data and linked COVID-19 registry data of Korea Centers for Disease Control & Prevention (KCDC) for this emergent observational cohort study. A total of 9,148 patients with confirmed COVID-19 were included. Mortalities by sex, age, district, income level and all range of comorbidities classified by International Classification of Diseases-10 based 298 categories were estimated. RESULTS: There were 3,556 male confirmed cases, 67 deaths, and crude death rate (CDR) of 1.88%. There were 5,592 females, 63 deaths, and CDR of 1.13%. The most confirmed cases were 1,352 patients between the ages of 20 to 24, followed by 25 to 29. As a result of multivariate logistic regression analysis that adjusted epidemiologic factors to view the risk of death, the odds ratio of death would be hemorrhagic conditions and other diseases of blood and blood-forming organs 3.88-fold (95% confidence interval [CI], 1.52-9.88), heart failure 3.17-fold (95% CI, 1.88-5.34), renal failure 3.07-fold (95% CI, 1.43-6.61), prostate malignant neoplasm 2.88-fold (95% CI, 1.01-8.22), acute myocardial infarction 2.38-fold (95% CI, 1.03-5.49), diabetes was 1.82-fold (95% CI, 1.25-2.67), and other ischemic heart disease 1.71-fold (95% CI, 1.09-2.66). CONCLUSION: We hope that this study could provide information on high risk groups for preemptive interventions. In the future, if a vaccine for COVID-19 is developed, it is expected that this study will be the basic data for recommending immunization by selecting those with chronic disease that had high risk of death, as recommended target diseases for vaccination.


Estimating the infection and case fatality ratio for coronavirus disease (COVID-19) using age-adjusted data from the outbreak on the Diamond Princess cruise ship, February 2020

Abstract: Adjusting for delay from confirmation to death, we estimated case and infection fatality ratios (CFR, IFR) for coronavirus disease (COVID-19) on the Diamond Princess ship as 2.6% (95% confidence interval (CI): 0.89-6.7) and 1.3% (95% CI: 0.38-3.6), respectively. Comparing deaths on board with expected deaths based on naive CFR estimates from China, we estimated CFR and IFR in China to be 1.2% (95% CI: 0.3-2.7) and 0.6% (95% CI: 0.2-1.3), respectively.


Case Fatality Rate of Cancer Patients with COVID-19 in a New York Hospital System

Abstract: Patients with cancer are presumed to be at increased risk from COVID-19 infection-related fatality due to underlying malignancy, treatment-related immunosuppression, or increased comorbidities. A total of 218 COVID-19-positive patients from March 18, 2020, to April 8, 2020, with a malignant diagnosis were identified. A total of 61 (28%) patients with cancer died from COVID-19 with a case fatality rate (CFR) of 37% (20/54) for hematologic malignancies and 25% (41/164) for solid malignancies. Six of 11 (55%) patients with lung cancer died from COVID-19 disease. Increased mortality was significantly associated with older age, multiple comorbidities, need for ICU support, and elevated levels of D-dimer, lactate dehydrogenase, and lactate in multivariate analysis. Age-adjusted CFRs in patients with cancer compared with noncancer patients at our institution and New York City reported a significant increase in case fatality for patients with cancer. These data suggest the need for proactive strategies to reduce likelihood of infection and improve early identification in this vulnerable patient population. SIGNIFICANCE: COVID-19 in patients with cancer is associated with a significantly increased risk of case fatality, suggesting the need for proactive strategies to reduce likelihood of infection and improve early identification in this vulnerable patient population.This article is highlighted in the In This Issue feature, p. 890.


Analyzing COVID-19 pandemic for unequal distribution of tests, identified cases, deaths, and fatality rates in the top 18 countries

Abstract: BACKGROUND AND AIMS: COVID-19 pandemic has affected various countries differently due to variance in demographics, income level, health infrastructure, government response, control and enforcement, and cultural traits of different populations. This study aims to identify significant factors behind the unequal distribution of identified cases and deaths in different countries. Our study's objective is comparative analysis and identification of relations between the spread of COVID-19 pandemic, population characteristics, and government response. METHODS: The top 18 countries worst hit by COVID-19 cases were identified. The data metrics, such as the number of cases, deaths, fatality rates, tests, average life expectancy, and population, were collected and consolidated. RESULTS: Countries with significant percentage of the older population are vulnerable to a high number of deaths due to COVID-19. Developed countries have higher per capita testing, whereas testing is less intensive in developing/underdeveloped countries. There is a consensus among health experts that COVID-19 has higher fatality rates for people above 60, however, with further age, this increases exponentially. Countries with higher life expectancy are also high-income countries, and the best course of action would be to provide specialized support to self-isolate for people of ages 75 and above. CONCLUSION: The behaviour of disease occurring at a large scale and interaction with different populations is studied to understand and differentiate the factors and measures that successfully inhibited the pandemic. The study benchmarks different countries based on their performance and efforts against the pandemic and provides some useful insights on the efficiency of their governance and potential to improve & ramp up their programs. The economic status and existing healthcare infrastructure as they are the key factors in determining the country's ability to contain and minimize the losses from this pandemic.


SARS-CoV-2 in Italy: Population Density correlates with Morbidity and Mortality

Abstract: Since the beginning of the SARS-CoV-2/COVID-19 epidemic in China, elderly and multimorbid subjects showed a higher mortality rate. However, other factors could influence the mortality and the spread of contagion such as the population density. An archival research based on the Italian data stratified by region was performed in order to quantify the association between the population density, ageing index, number of positive cases, number of deaths, case-fatality rate, and medical equipment (gloves, masks, and ventilators). Results showed a significant positive linear relationship between the population density and cases, deaths, and case-fatality rate. No correlation with the ageing index was shown. Furthermore, we found a significant positive correlation between the number of medical supplies and population density, cases, and deaths. However, the medical supplies did not show any correlation with the case-fatality rate. Taken together, these findings suggest that the population density and the lack of medical equipment are key factors explaining morbidity and mortality of COVID-19 in Italy.


Rate of Intensive Care Unit admission and outcomes among patients with coronavirus: A systematic review and Meta-analysis

Abstract: BACKGROUND: The rate of ICU admission among patients with coronavirus varied from 3% to 100% and the mortality was as high as 86% of admitted patients. The objective of the systematic review was to investigate the rate of ICU admission, mortality, morbidity, and complications among patients with coronavirus. METHODS: A comprehensive strategy was conducted in PubMed/Medline; Science direct and LILACS from December 2002 to May 2020 without language restriction. The Heterogeneity among the included studies was checked with forest plot, χ2 test, I2 test, and the p-values. All observational studies reporting rate of ICU admission, the prevalence of mortality and its determinants among ICU admitted patients with coronavirus were included and the rest were excluded. RESULT: A total of 646 articles were identified from different databases and 50 articles were selected for evaluation. Thirty-seven Articles with 24983 participants were included. The rate of ICU admission was 32% (95% CI: 26 to 38, 37 studies and 32, 741 participants). The Meta-Analysis revealed that the pooled prevalence of mortality in patients with coronavirus disease in ICU was 39% (95% CI: 34 to 43, 37 studies and 24, 983 participants). CONCLUSION: The Meta-Analysis revealed that approximately one-third of patients admitted to ICU with severe Coronavirus disease and more than thirty percent of patients admitted to ICU with a severe form of COVID-19 for better care died which warns the health care stakeholders to give attention to intensive care patients. REGISTRATION: This Systematic review and Meta-Analysis was registered in Prospero international prospective register of systemic reviews (CRD42020177095) on April 9/2020.


Prevalence and mortality in ß-thalassaemias due to outbreak of novel coronavirus disease (COVID-19): the nationwide Iranian experience


Mortality rate and gender differences in COVID-19 patients dying in Italy: A comparison with other countries


COVID-19 patients' clinical characteristics, discharge rate, and fatality rate of meta-analysis

Abstract: The aim of this study was to analyze the clinical data, discharge rate, and fatality rate of COVID-19 patients for clinical help. The clinical data of COVID-19 patients from December 2019 to February 2020 were retrieved from four databases. We statistically analyzed the clinical symptoms and laboratory results of COVID-19 patients and explained the discharge rate and fatality rate with a single-arm meta-analysis. The available data of 1994 patients in 10 literatures were included in our study. The main clinical symptoms of COVID-19 patients were fever (88.5%), cough (68.6%), myalgia or fatigue (35.8%), expectoration (28.2%), and dyspnea (21.9%). Minor symptoms include headache or dizziness (12.1%), diarrhea (4.8%), nausea and vomiting (3.9%). The results of the laboratory showed that the lymphocytopenia (64.5%), increase of C-reactive protein (44.3%), increase of lactic dehydrogenase (28.3%), and leukocytopenia (29.4%) were more common. The results of single-arm meta-analysis showed that the male took a larger percentage in the gender distribution of COVID-19 patients 60% (95% CI [0.54, 0.65]), the discharge rate of COVID-19 patients was 52% (95% CI [0.34,0.70]), and the fatality rate was 5% (95% CI [0.01,0.11]).


Coronavirus Disease 2019: Where are we and Where are we Going? Intersections Between Coronavirus Disease 2019 and the Heart

Abstract: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19), which has become a pandemic affecting every country in the world. In the province of Bergamo, Italy, more than 2,200 cases of COVID-19 have been reported, which include more than 300 deaths. Most hospitalisations have been at the Papa Giovanni XXIII Hospital. This has imposed a significant burden on our hospital in terms of healthcare personnel, dedicated spaces (including intensive care areas) and time spent by clinicians, who are committed to assisting COVID-19 patients. In this short expert opinion, the authors will focus on new insights related to COVID-19 and the cardiovascular system, and try to investigate the grey areas and uncertainties in this field.


[Cardiac biomarkers and COVID-19 - Phenotypes and Interpretation].

Abstract: Current pandemic caused by SARS-CoV-2 inducing viral COVID-19 pneumonia, is categorized in 3 stages. Some biomarkers could be assigned to one of these stages, showing a correlation to mortality in COVID-19 patients. Laboratory findings in COVID-19, especially when serially evaluated, may represent individual disease severity and prognosis. These may help planning and controlling therapeutic interventions. Biomarkers for myocardial injury (high sensitive cardiac troponin, hsTn) or hemodynamic stress (NTproBNP) may occur in COVID-19 pneumonia such as in other pneumonias, correlating with severity and prognosis of the underlying disease. In hospitalized COVID-19 patients' mild increases of hsTn or NTproBNP may be explained by cardiovascular comorbidities and direct or indirect cardiac damage or stress caused by or during COVID-19 pneumonia. In case of suspected NSTE-ACS and COVID-19, indications for echocardiography or reperfusion strategy should be carefully considered against the risk of contamination.


Usefulness of echocardiography to detect cardiac involvement in COVID-19 patients.

Abstract: Coronavirus disease 2019 (COVID-19) outbreak is a current global healthcare burden, leading to the life-threatening severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, evidence showed that, even if the prevalence of COVID-19 damage consists in pulmonary lesions and symptoms, it could also affect other organs, such as heart, liver, and spleen. Particularly, some infected patients refer to the emergency department for cardiovascular symptoms, and around 10% of COVID-19 victims had finally developed heart injury. Therefore, the use of echocardiography, according to the safety local protocols and ensuring the use of personal protective equipment, could be useful firstly to discriminate between primary cardiac disease or COVID-19-related myocardial damage, and then for assessing and monitoring COVID-19 cardiovascular complications: acute myocarditis and arrhythmias, acute heart failure, sepsis-induced myocardial impairment, and right ventricular failure derived from treatment with high-pressure mechanical ventilation. The present review aims to enlighten the applications of transthoracic echocardiography for the diagnostic and therapeutic management of myocardial damage in COVID-19 patients.


Coronavirus Disease 2019 (COVID-19) Pandemic Implications in Pediatric and Adult Congenital Heart Disease.

Abstract: The corona virus disease -2019 (COVID-19) is a recently described infectious disease caused by the severe acute respiratory syndrome corona virus 2 with significant cardiovascular implications. Given the increased risk for severe COVID-19 observed in adults with underlying cardiac involvement, there is concern that patients with pediatric and congenital heart disease (CHD) may likewise be at increased risk for severe infection. The cardiac manifestations of COVID-19 include myocarditis, arrhythmia and myocardial infarction. Importantly, the pandemic has stretched health care systems and many care team members are at risk for contracting and possibly transmitting the disease which may further impact the care of patients with cardiovascular disease. In this review, we describe the effects of COVID-19 in the pediatric and young adult population and review the cardiovascular involvement in COVID-19 focusing on implications for patients with congenital heart disease in particular.


SARS-CoV-2 and myocardial injury: Few answers, many questions.

Abstract: Patients with COVID-19 and acute cardiac injury as measured by an elevated high-sensitivity troponin I or troponin T upon admission or during hospitalization have a mortality rate of over 50% in initial reports. The mechanism of SARS-CoV-2 and associated myocardial injury, whether SARS-CoV-2 patients with myocardial injury are a distinct population, and possible treatment options for myocardial injury associated with SARS-CoV-2 are unknown.


Approach to Acute Cardiovascular Complications in COVID-19 Infection.

Abstract: The novel coronavirus disease 2019, otherwise known as COVID-19, is a global pandemic with primary respiratory manifestations in those who are symptomatic. It has spread to more than 187 countries with a rapidly growing number of affected patients. Underlying cardiovascular disease is associated with more severe manifestations of COVID-19 and higher rates of mortality. COVID-19 can have both primary (arrhythmias, myocardial infarction, myocarditis) and secondary (myocardial injury/biomarker elevation, heart failure) cardiac involvement. In severe cases, profound circulatory failure can result. This review discusses the presentation and management of patients with severe cardiac complications of COVID-19 disease, with an emphasis on a "Heart-Lung" team approach in patient management. Furthermore, it focuses on the use of and indications for acute mechanical circulatory support in cardiogenic and/or mixed shock.


Cardiac Troponin for the Diagnosis and Risk-Stratification of Myocardial Injury in COVID-19: JACC Review Topic of the Week.

Abstract: Increases in cardiac troponin (cTn) indicative of myocardial injury are common in patients with COVID-19 and associated with adverse outcomes such as arrhythmias and death. These increases are more likely to occur in those with chronic cardiovascular conditions and in those with severe COVID-19 presentations. The increased inflammatory, prothrombotic, and procoagulant responses following SARS-CoV-2 infection increase the risk for acute nonischemic myocardial injury and acute myocardial infarction, particularly type 2 myocardial infarction because of respiratory failure with hypoxia and hemodynamic instability in critically ill patients. Myocarditis, stress cardiomyopathy, acute heart failure, and direct injury from SARS-CoV-2 are important etiologies, but primary non-cardiac conditions such as pulmonary embolism, critical illness, and sepsis probably cause more of the myocardial injury. The structured use of serial cTn has the potential to facilitate risk stratification, help make decisions about when to use imaging, and inform stage categorization and disease phenotyping among hospitalized COVID-19 patients.


Cardiac manifestations in COVID-19 patients-A systematic review.

Abstract: OBJECTIVES The coronavirus disease-2019 (COVID-19) pandemic has resulted in the worst global pandemic of our generation, affecting 215 countries with nearly 5.5 million cases. The association between COVID-19 and the cardiovascular system has been well described. We sought to systematically review the current published literature on the different cardiac manifestations and the use of cardiac-specific biomarkers in terms of their prognostic value in determining clinical outcomes and correlation to disease severity. METHODS A systematic literature review across PubMed, Cochrane database, Embase, Google Scholar, and Ovid was performed according to PRISMA guidelines to identify relevant articles that discussed risk factors for cardiovascular manifestations, cardiac manifestations in COVID-19 patients, and cardiac-specific biomarkers with their clinical implications on COVID-19. RESULTS Sixty-one relevant articles were identified which described risk factors for cardiovascular manifestations, cardiac manifestations (including heart failure, cardiogenic shock, arrhythmia, and myocarditis among others) and cardiac-specific biomarkers (including CK-MB, CK, myoglobin, troponin, and NT-proBNP). Cardiovascular risk factors can play a crucial role in identifying patients vulnerable to developing cardiovascular manifestations of COVID-19 and thus help to save lives. A wide array of cardiac manifestations is associated with the interaction between COVID-19 and the cardiovascular system. Cardiac-specific biomarkers provide a useful prognostic tool in helping identify patients with the severe disease early and allowing for escalation of treatment in a timely fashion. CONCLUSION COVID-19 is an evolving pandemic with predominate respiratory manifestations, however, due to the interaction with the cardiovascular system; cardiac manifestations/complications feature heavily in this disease, with cardiac biomarkers providing important prognostic information.


Obesity accompanying COVID-19: the role of epicardial fat.

Abstract: With interest we read the study by Simonnet A et al. (1) in which important novel evidence is addressed that obesity is highly frequent among critically ill patients with severe acute respiratory syndrome coronavirus-2 (SARS-Cov-2) infection. Although clinically very relevant, it remains difficult to elucidate the mechanisms by which SARS-Cov-2 severity is increased in the context of obesity. As reported by Katz JN et al. (2), 28% of hospitalised patients with coronavirus disease 2019 (COVID-19) presented cardiac complications including myocarditis, arrhythmias, heart failure (HF) and sudden death. Considering that myocardial response in COVID-19 is closely associated with in-hospital mortality, local biological effects on myocardial tissue from epicardial adipose tissue (EAT) is warrant further discussion.


Takotsubo Syndrome Associated with COVID-19

Abstract: Objective: The availability of public health information for optimised supportive care is critical during the COVID-19 pandemic We describe the first case of COVID-19 complicated by Takotsubo cardiomyopathy Materials and Methods: We report the clinical, laboratory and radiological findings of a patient with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Results: The nasopharyngeal swab was positive for SARS-CoV-2 and x-ray images demonstrated pathognomonic pneumonia The patient developed tachycardia and the echocardiogram confirmed the diagnosis of Takotsubo cardiomyopathy Conclusions: Doctors should be aware of the need to thoroughly study this new infection in order to understand its underlying mechanisms and related complications LEARNING POINTS: We report the first case of Takotsubo cardiomyopathy associated with COVID-19 We discuss a rare presentation in the current pandemic COVID-19 can be associated with cardiac complications, even after the onset of pneumonia, and so strict monitoring of these patients is essential


Cardiac Structural and Functional Characteristics in Patients with Coronavirus Disease 2019: A Serial Echocardiographic Study

Abstract: BACKGROUND: Increasing attention has been paid to cardiac involvement in patients with coronavirus disease 2019 (COVID-19). Yet, scarce information is available regarding the morphological and functional features of cardiac impairments in these patients. METHODS: We conducted a prospective and serial echocardiographic study to investigate the structural and functional cardiac changes among COVID-19 patients admitted to the intensive care unit (ICU). From January 21 to April 8, 2020, a total of 51 ICU patients (31 critically ill and 20 severely ill) with confirmed COVID-19 were monitored by serial transthoracic echocardiography examinations. Outcomes were followed up until April 8, 2020. RESULTS: Of 51 ICU patients, 33 (64.7%) had cardiovascular comorbidities. Elevations of levels of cardiac biomarkers including high-sensitivity cardiac troponin-I (hs-cTnI) and brain natriuretic peptide were observed in 62.7% and 86.3% of patients, respectively. Forty-two (82.3%) had at least one left-heart and/or right-heart echocardiographic abnormality. The overall median left ventricular ejection fraction (LVEF) was 65.0% (IQR 58.0-69.0%), with most (44,86.3%) having preserved LVEF. Sixteen patients (31.4%) had increased pulmonary artery systolic pressure, and 14 (27.5%) had right-ventricle (RV) enlargement. During the study period, 12 (23.5%) patients died. LVEF was comparable between survivors and non-survivors, while non-survivors had more often pulmonary hypertension (58.3% vs. 23.1%; P=0.028) and RV enlargement (58.3% vs. 17.9%, P=0.011). Kaplan-Meier analysis demonstrated similar survival curves between patients with vs. without echocardiographic left-heart abnormalities (P=0.450 by log-rank test), while right-heart abnormalities had adverse impact on mortality (P=0.012 by log-rank test). CONCLUSIONS: Typical cardiac abnormality in ICU patients with COVID-19 was right-heart dysfunction with preserved LVEF. Echocardiographic right-heart dysfunction was associated with disease severity and increased mortality in patients affected by COVID-19.


Cardiovascular complications of severe acute respiratory syndrome.

Abstract: BACKGROUND AND AIMS Severe acute respiratory syndrome (SARS) is a virulent viral infection that affects a number of organs and systems. This study examined if SARS may result in cardiovascular complications. METHODS AND RESULTS 121 patients (37.5 (SD13.2) years, 36% male) diagnosed to have SARS were assessed continuously for blood pressure, pulse, and temperature during their stay in hospital. Hypotension occurred in 61 (50.4%) patients in hospital, and was found in 28.1%, 21.5%, and 14.8% of patients during the first, second, and third week, respectively. Only one patient who had transient echocardiographic evidence of impaired left ventricular systolic function required temporary inotropic support. Tachycardia was present in 87 (71.9%) patients, and was found in 62.8%, 45.4%, and 35.5% of patients from the first to third week. It occurred independent of hypotension, and could not be explained by the presence of fever. Tachycardia was also present in 38.8% of patients at follow up. Bradycardia only occurred in 18 (14.9%) patients as a transient event. Reversible cardiomegaly was reported in 13 (10.7%) patients, but without clinical evidence of heart failure. Transient atrial fibrillation was present in one patient. Corticosteroid therapy was weakly associated with tachycardia during the second (chi(2) = 3.99, p = 0.046) and third week (chi(2) = 6.53, p = 0.01), although it could not explain tachycardia during follow up. CONCLUSIONS In patients with SARS, cardiovascular complications including hypotension and tachycardia were common but usually self limiting. Bradycardia and cardiomegaly were less common, while cardiac arrhythmia was rare. However, only tachycardia persisted even when corticosteroid therapy was withdrawn.