Impact of non-pharmaceutical interventions against COVID-19 in Europe in 2020: a quasi-experimental non-equivalent group and time series design study

IntroductionThe current pandemic of coronavirus disease (COVID-19) is unparalleled in recent history as are the social distancing interventions that have led to a considerable halt on the economic and social life of so many countries.AimWe aimed to generate empirical evidence about which social distancing measures had the most impact in reducing case counts and mortality.MethodsWe report a quasi-experimental (observational) study of the impact of various interventions for control of the outbreak through 24 April 2020. Chronological data on case numbers and deaths were taken from the daily published figures by the European Centre for Disease Prevention and Control and dates of initiation of various control strategies from the Institute of Health Metrics and Evaluation website and published sources. Our complementary analyses were modelled in R using Bayesian generalised additive mixed models and in STATA using multilevel mixed-effects regression models.ResultsFrom both sets of modelling, we found that closure of education facilities, prohibiting mass gatherings and closure of some non-essential businesses were associated with reduced incidence whereas stay-at-home orders and closure of additional non-essential businesses was not associated with any independent additional impact.ConclusionsOur findings are that schools and some non-essential businesses operating ‘as normal’ as well as allowing mass gatherings were incompatible with suppressing disease spread. Closure of all businesses and stay at home orders are less likely to be required to keep disease incidence low. Our results help identify what were the most effective non-pharmaceutical interventions in this period.     

Policy Interventions,Social Distancing,and SARS-CoV-2 Transmission in the United States: A Retrospective State-level Analysis

BackgroundVarious non-pharmaceutical interventions (NPIs) such as stay-at-home orders and school closures have been employed to limit the spread of Coronavirus disease (COVID-19). This study measures the impact of social distancing policies on COVID-19 transmission in US states during the early outbreak phase to assess which policies were most effective.MethodsTo measure transmissibility, we analyze the average effective reproductive number (R_t) in each state the week following its 500th case and doubling time from 500 to 1000 cases. Linear and logistic regressions were performed to assess the impact of various NPIs while controlling for population density, GDP, and certain health metrics. This analysis was repeated for deaths with doubling time to 100 deaths with several healthcare infrastructure control variables.ResultsStates with stay-at-home orders in place at the time of their 500th case were associated with lower average R_t the following week compared to states without them (p<0.001) and significantly less likely to have an R_t>1 (OR 0.07, 95% CI 0.01–0.37, p = 0.004). These states also experienced longer doubling time from 500 to 1000 cases (HR 0.35, 95% CI 0.17–0.72, p = 0.004). States in the highest quartile of average time spent at home were also slower to reach 1000 cases than those in the lowest quartile (HR 0.18, 95% CI 0.06–0.53, p = 0.002).ConclusionsStay-at-home orders had the largest effect of any policy analyzed. Multivariate analyses with cellphone tracking data suggest social distancing adherence drives these effects. States that plan to scale back such measures should carefully monitor transmission metrics.     

Reverse quarantine and COVID-19

BackgroundCOVID-19 is a pandemic, resulting in large number of deaths all over the world. Lack of effective antiviral agents and vaccines pose a major challenge to control this pandemic.MethodsReview the role of reverse quarantine in the control of COVID-19.ResultsPublic health measures like social distancing, wearing face mask and hand hygiene along with quarantine measures form important steps to control the disease. Reverses quarantine is a useful strategy to reduce morbidity and mortality associated with COVID-19.ConclusionsReverse quarantine is a promising public health measure to reduce the morbidity and mortality associated with COVID-19.     

Different patterns of excess all-cause mortality by age and sex in Hungary during the 2nd and 3rd waves of the COVID-19 pandemic

It is well accepted that COVID-19-related mortality shows a strong age dependency. However, temporal changes in the age distribution of excess relative mortality between waves of the pandemic are less frequently investigated. We aimed to assess excess absolute mortality and the age-distribution of all-cause mortality during the second and third waves of the COVID-19 pandemic in Hungary compared to the same periods of non-pandemic years. Rate ratios for excess all-cause mortality with 95% confidence intervals and the number of excess deaths for the second (week 41 of 2020 through week 4 of 2021) and third waves (weeks 7–21 of 2021) of the COVID pandemic for the whole of Hungary compared to the same periods of the pre-pandemic years were estimated for 10-year age strata using Poisson regression. Altogether, 9771 (95% CI: 9554–9988) excess deaths were recorded during the second wave of the pandemic, while it was lower, 8143 (95% CI: 7953–8333) during the third wave. During the second wave, relative mortality peaked for ages 65–74 and 75–84 (RR 1.37, 95%CI 1.33–1.41, RR 1.38, 95%CI 1.34–1.42). Conversely, during the third wave, relative mortality peaked for ages 35–44 (RR 1.43, 95%CI 1.33–1.55), while those ≥65 had substantially lower relative risks compared to the second wave. The reduced relative mortality among the elderly during the third wave is likely a consequence of the rapidly increasing vaccination coverage of the elderly coinciding with the third wave. The hugely increased relative mortality of those 35–44 could point to non-biological causes, such as less stringent adherence to non-pharmaceutical measures in this population.

     

Influenza and Other Respiratory Viruses: Impact of nonpharmaceutical interventions on laboratory detections of influenza A and B in Canada

BackgroundThe first coronavirus disease 2019 (COVID-19) case was reported in Canada on January 25, 2020. In response to the imminent outbreak, many provincial and territorial health authorities implemented nonpharmaceutical public health measures to curb the spread of disease. “Social distancing” measures included restrictions on group gatherings; cancellation of sports, cultural and religious events and gatherings; recommended physical distancing between people; school and daycare closures; reductions in non-essential services; and closures of businesses.ObjectivesTo evaluate the impact of the combined nonpharmaceutical interventions imposed in March 2020 on influenza A and B epidemiology by comparing national laboratory surveillance data from the intervention period with 9-year historical influenza season control data.MethodsWe obtained epidemiologic data on laboratory influenza A and B detections and test volumes from the Canadian national influenza surveillance system for the epidemiologic period December 29, 2019 (epidemiologic week 1) through May 2, 2020 (epidemiologic week 18). COVID-19-related social distancing measures were implemented in Canada from epidemiologic week 10 of this period. We compared influenza A and B laboratory detections and test volumes and trends in detection during the 2019–20 influenza season with those of the previous nine influenza seasons for evidence of changes in epidemiologic trends.ResultsWhile influenza detections the week prior to the implementation of social distancing measures did not differ statistically from the previous nine seasons, a steep decline in positivity occurred between epidemiologic weeks 10 and 14 (March 8–April 4, 2020). Both the percent positive on week 14 (p≤0.001) and rate of decline between weeks 10 and 14 (p=0.003) were significantly different from mean historical data.ConclusionThe data show a dramatic decrease in influenza A and B laboratory detections concurrent with social distancing measures and nonpharmaceutical interventions in Canada. The impact of these measures on influenza transmission may be generalizable to other respiratory viral illnesses during the study period, including COVID-19.     

Worrisome trends of ST-elevation myocardial infarction during the Covid-19 pandemic: Data from Portuguese centers

IntroductionDuring the Covid-19 pandemic there has been a general belief that hospital admissions for non-infectious causes, especially cardiovascular diseases, have fallen.ObjectivesTo assess the impact of the pandemic on admissions for ST-elevation myocardial infarction (STEMI) during the first pandemic wave.MethodsWe performed a multicenter retrospective analysis of consecutive patients presenting with STEMI in two Portuguese hospital centers in two sequential periods – P1 (March 1 to April 30) and P2 (May 1 to June 30). Patient's clinical data and hospital outcomes were compared between the years 2017 to 2019 and 2020 for both periods.ResultsDuring P1 in 2020, a reduction in the number of STEMI patients was observed in comparison with previous years (26.0±4.2 vs. 16.5±4.9 cases per month; p=0.033), as well as an increase in the number of mechanical complications (0.0% vs. 3.0%; p=0.029). Percutaneous coronary interventions in the setting of failed thrombolysis were more frequent (1.9% vs. 9.1%; p=0.033). An overall trend for longer delays in key timings of STEMI care bundles was noted. Mortality was higher during P1 compared to previous years (1.9% vs. 12.1%; p=0.005).ConclusionsDuring the first Covid-19 wave fewer patients presented with STEMI at the catheterization laboratory for percutaneous coronary intervention. These patients presented more mechanical complications and higher mortality.     

Risk of Covid-19-Related Hospitalization and More Severe Outcomes in Medicare Beneficiaries Treated with Renin-Angiotensin-Aldosterone System Inhibitors for Hypertension

BackgroundThere are theoretical concerns that angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) could increase the risk of severe Covid-19.ObjectiveTo determine if ACEIs and ARBs are associated with an increased risk of Covid-19 hospitalization overall, or hospitalization involving intensive care unit (ICU) admission, invasive mechanical ventilation, or death.DesignObservational case-control study.ParticipantsMedicare beneficiaries aged ≥ 66 years with hypertension, treated with ACEIs, ARBs, calcium channel blockers (CCBs), or thiazide diuretics.Main MeasuresAdjusted odds ratios (OR) and 95% confidence intervals (CI) for the outcomes of Covid-19 hospitalization, or hospitalization involving ICU admission, invasive mechanical ventilation, or death.ResultsA total of 35,300 cases of hospitalized Covid-19 were matched to 228,228 controls on calendar date and neighborhood of residence. The median age of cases was 79 years, 57.4% were female, and the median duration of hospitalization was 8 days (interquartile range 5–12). ACEIs and ARBs were associated with a slight reduction in Covid-19 hospitalization risk compared with treatment with other first-line antihypertensives (OR for ACEIs 0.95, 95% CI 0.92–0.98; OR for ARBs 0.94, 95% CI 0.90–0.97). Similar results were obtained for hospitalizations involving ICU admission, invasive mechanical ventilation, or death. There were no meaningful differences in risk for ACEIs compared with ARBs. In an analysis restricted to monotherapy with a first-line agent, CCBs were associated with a small increased risk of Covid-19 hospitalization compared with ACEIs (OR 1.09, 95% CI 1.04–1.14), ARBs (OR 1.10, 95% CI 1.05–1.15), or thiazide diuretics (OR 1.11, 95% CI 1.03–1.19).ConclusionsACEIs and ARBs were not associated with an increased risk of Covid-19 hospitalization or with hospitalization involving ICU admission, invasive mechanical ventilation, or death. The finding of a small increased risk of Covid-19 hospitalization with CCBs was unexpected and could be due to residual confounding.Supplementary InformationThe online version contains supplementary material available at 10.1007/s11606-021-07155-z.Key Words: angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, Covid-19, intensive care, mechanical ventilation     

The Global Effect of the COVID-19 Pandemic on STEMI Care: A Systematic Review and Meta-analysis

BackgroundThe COVID-19 pandemic has affected patients with ST-segment elevation myocardial infarction (STEMI) requiring primary percutaneous coronary intervention (PCI) worldwide. In this review we examine the global effect of the COVID-19 pandemic on incidence of STEMI admissions, and relationship between the pandemic and door to balloon time (D2B), all-cause mortality, and other secondary STEMI outcomes.MethodsWe performed a systematic review and meta-analysis to primarily compare D2B time and in-hospital mortality of STEMI patients who underwent primary PCI during and before the pandemic. Subgroup analyses were performed to investigate the influence of geographical region and income status of a country on STEMI care. An online database search included studies that compared the aforementioned outcomes of STEMI patients during and before the pandemic.ResultsIn total, 32 articles were analyzed. Overall, 19,140 and 68,662 STEMI patients underwent primary PCI during and before the pandemic, respectively. Significant delay in D2B was observed during the pandemic (weighted mean difference, 8.10 minutes; 95% confidence interval [CI], 3.90-12.30 minutes; P = 0.0002; I² = 90%). In-hospital mortality was higher during the pandemic (odds ratio [OR], 1.27; 95% CI, 1.09-1.49; P = 0.002; I² = 36%), however this varied with factors such as geographical location and income status of a country. Subgroup analysis showed that low–middle-income countries observed a higher rate of mortality during the pandemic (OR, 1.52; 95% CI, 1.13-2.05; P = 0.006), with a similar but insignificant trend seen among the high income countries (OR, 1.17; 95% CI, 0.95-1.44; P = 0.13).ConclusionsThe COVID-19 pandemic is associated with worse STEMI performance metrics and clinical outcome, particularly in the Eastern low–middle-income status countries. Better strategies are needed to address these global trends in STEMI care during the pandemic.     

COVID-19: A Year Later: Simple mathematical modelling approaches to assessing the transmission risk of SARS-CoV-2 at gatherings

BackgroundGatherings may contribute significantly to the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). For this reason, public health interventions have sought to constrain unrepeated or recurrent gatherings to curb the coronavirus disease 2019 (COVID-19) pandemic. Unfortunately, the range of different types of gatherings hinders specific guidance from setting limiting parameters (e.g. total size, number of cohorts, the extent of physical distancing).MethodsWe used a generic modelling framework, based on fundamental probability principles, to derive simple formulas to assess introduction and transmission risks associated with gatherings, as well as the potential efficiency of some testing strategies to mitigate these risks.ResultsIntroduction risk can be broadly assessed with the population prevalence and the size of the gathering, while transmission risk at a gathering is mainly driven by the gathering size. For recurrent gatherings, the cohort structure does not have a significant impact on transmission between cohorts. Testing strategies can mitigate risk, but frequency of testing and test performance are factors in finding a balance between detection and false positives.ConclusionThe generality of the modelling framework used here helps to disentangle the various factors affecting transmission risk at gatherings and may be useful for public health decision-making.     

Data mining and analysis of scientific research data records on Covid-19 mortality,immunity, and vaccine development - In the first wave of the Covid-19 pandemic

Background and aimsCovid-19 is a global pandemic that requires a global and integrated response of all national medical and healthcare systems. Covid-19 exposed the need for timely response and data sharing on fast spreading global pandemics. In this study, we investigate the scientific research response from the early stages of the pandemic, and we review key findings on how the early warning systems developed in previous epidemics responded to contain the virus.MethodsWe conducted data mining of scientific literature records from the Web of Science Core Collection, using the topics Covid-19, mortality, immunity, and vaccine. The individual records are analysed in isolation, and the analysis is compared with records on all Covid-19 research topics combined. The data records are analysed with commutable statistical methods, including R Studio’s Bibliometrix package, and the Web of Science data mining tool.ResultsFrom historical analysis of scientific data records on viruses, pandemics and mortality, we identified that Chinese universities have not been leading on these topics historically. However, during the early stages of the Covid-19 pandemic, the Chinese universities are strongly dominating the research on these topics. Despite the current political and trade disputes, we found strong collaboration in Covid-19 research between the US and China. From the analysis on Covid-19 and immunity, we wanted to identify the relationship between different risk factors discussed in the news media. We identified a few clusters, containing references to exercise, inflammation, smoking, obesity and many additional factors. From the analysis on Covid-19 and vaccine, we discovered that although the USA is leading in volume of scientific research on Covid-19 vaccine, the leading 3 research institutions (Fudan, Melbourne, Oxford) are not based in the USA. Hence, it is difficult to predict which country would be first to produce a Covid-19 vaccine.ConclusionsWe analysed the conceptual structure maps with factorial analysis and multiple correspondence analysis (MCA), and identified multiple relationships between keywords, synonyms and concepts, related to Covid-19 mortality, immunity, and vaccine development. We present integrated and corelated knowledge from 276 records on Covid-19 and mortality, 71 records on Covid-19 and immunity, and 189 records on Covid-19 vaccine.     

Covid-19 in liver transplant recipients: the French SOT COVID registry

BackgroundNotwithstanding the ongoing coronavirus disease-2019 (Covid-19) pandemic, information on its clinical presentation and prognosis in organ transplant recipients remains limited. The aim of this registry-based observational study was to report the characteristics and clinical outcomes of liver transplant (LT) recipients included in the French nationwide Registry of Solid Organ Transplant Recipients with Covid-19.MethodsCOVID-19 was diagnosed in patients who had a positive PCR assay for SARS-CoV-2 or in presence of typical lung lesions on imaging or specific SARS-CoV-2 antibodies. Clinical and laboratory characteristics, management of immunosuppression, treatment for Covid-19, and clinical outcomes (hospitalization, admission to intensive care unit, mechanical ventilation, or death) were recorded.ResultsOf the 104 patients, 67 were admitted to hospital and 37 were managed at home (including all 13 children). Hospitalized patients had a median age of 65.2 years (IQR: 58.1 ? 73.2 years) and two thirds were men. Most common comorbidities included overweight (67.3%), hypertension (61.2%), diabetes (50.7%), cardiovascular disease (20.9%) and respiratory disease (16.4%). SARS-CoV-2 infection was identified after a median of 92.8 months (IQR: 40.1 ? 194.7 months) from LT. During hospitalization, antimetabolites, mTOR inhibitor, and CNIs were withdrawn in 41.9%, 30.0% and 12.5% of patients, respectively. The composite endpoint of severe Covid-19 within 30 days after diagnosis was reached by 33.0% of the adult patients. The 30-day mortality rate was 20.0%, and 28.1% for hospitalized patients. Multivariate analysis identified that age was independently associated with mortality.ConclusionIn our large nationwide study, Covid-19 in LT recipients was associated with a high mortality rate.     

Renal function and attributable risk of death and cardiovascular hospitalization in participants with diabetes from a registry-based cohort

AimsTo estimate the attributable risk of renal function on all-cause mortality and cardiovascular hospitalization in patients with diabetes.MethodsA prospective cohort study in 19,469 adults with diabetes, free of cardiovascular disease, attending primary care in Spain (2008–2011). The estimated glomerular filtration rate (eGFR) and other variables were collected and patients were followed to the first hospitalization for coronary or stroke event, or death, until the end of 2012. The cumulative incidence of the study endpoints by eGFR categories was graphically displayed and adjusted population attributable risks (PARs) for low eGFR was calculated.ResultsMean follow-up was 3.2 years and 506 deaths and 1720 hospitalizations were recorded. The cumulative risk for the individual events increased as eGFR levels decreased. The PAR associated with having an eGFR of 60 mL/min/1.73 m² or less was 11.4% (95% CI 4.8–18.3) for all-cause mortality, 9.2% (95% CI 5.3–13.4) for coronary heart disease, and 2.6% (95% CI ?1.8 to 7.4) for stroke.ConclusionsReduced eGFR levels were associated with a larger proportion of avoidable deaths and cardiovascular hospitalizations in people with diabetes compared to previously reported results in people with other cardiovascular risk factors.     

A Strong Seasonality Pattern for Covid-19 Incidence Rates Modulated by UV Radiation Levels

The Covid-19 pandemic has required nonpharmaceutical interventions, primarily physical distancing, personal hygiene and face mask use, to limit community transmission, irrespective of seasons. In fact, the seasonality attributes of this pandemic remain one of its biggest unknowns. Early studies based on past experience from respiratory diseases focused on temperature or humidity, with disappointing results. Our hypothesis that ultraviolet (UV) radiation levels might be a factor and a more appropriate parameter has emerged as an alternative to assess seasonality and exploit it for public health policies. Using geographical, socioeconomic and epidemiological criteria, we selected twelve North-equatorial-South countries with similar characteristics. We then obtained UV levels, mobility and Covid-19 daily incidence rates for nearly the entire 2020. Using machine learning, we demonstrated that UV radiation strongly associated with incidence rates, more so than mobility did, indicating that UV is a key seasonality indicator for Covid-19, irrespective of the initial conditions of the epidemic. Our findings can inform the implementation of public health emergency measures, partly based on seasons in the Northern and Southern Hemispheres, as the pandemic unfolds into 2021.     

Excess diabetes-related deaths: The role of comorbidities through different phases of the COVID-19 pandemic

Background and aimsDiabetes confers an excess risk of death to COVID-19 patients. Causes of death are now available for different phases of the pandemic, encompassing different viral variants and COVID-19 vaccination. The aims of the present study were to update multiple causes of death data on diabetes-related mortality during the pandemic and to estimate the impact of common diabetic comorbidities on excess mortality.Methods and resultsDiabetes-related deaths in 2020–2021 were compared with the 2018–2019 average; furthermore, age-standardized rates observed during the pandemic were compared with expected figures obtained from the 2008–2019 time series through generalized estimating equation models. Changes in diabetes mortality associated with specific comorbidities were also computed. Excess diabetes-related mortality was +26% in 2020 and +18% in 2021, after the initiation of the vaccination campaign. The presence of diabetes and hypertensive diseases was associated with the highest mortality increase, especially in subjects aged 40–79 years, +41% in 2020 and +30% in 2021.ConclusionThe increase in diabetes-related deaths exceeded that observed for all-cause mortality, and the risk was higher when diabetes was associated with hypertensive diseases. Notably, the excess mortality decreased in 2021, after the implementation of vaccination against COVID-19.     

Cigarette Smoking and Risk Perceptions During the COVID-19 Pandemic Reported by Recently Hospitalized Participants in a Smoking Cessation Trial

BackgroundCigarette smoking is a risk factor for severe COVID-19 disease. Understanding smokers’ responses to the pandemic will help assess its public health impact and inform future public health and provider messages to smokers.ObjectiveTo assess risk perceptions and change in tobacco use among current and former smokers during the COVID-19 pandemic.DesignCross-sectional survey conducted in May–July 2020 (55% response rate)Participants694 current and former daily smokers (mean age 53, 40% male, 78% white) who had been hospitalized pre-COVID-19 and enrolled into a smoking cessation clinical trial at hospitals in Massachusetts, Pennsylvania, and Tennessee.Main MeasuresPerceived risk of COVID-19 due to tobacco use; changes in tobacco consumption and interest in quitting tobacco use; self-reported quitting and relapse since January 2020.Key Results68% (95% CI, 65–72%) of respondents believed that smoking increases the risk of contracting COVID-19 or having a more severe case. In adjusted analyses, perceived risk was higher in Massachusetts where COVID-19 had already surged than in Pennsylvania and Tennessee which were pre-surge during survey administration (AOR 1.56, 95% CI, 1.07–2.28). Higher perceived COVID-19 risk was associated with increased interest in quitting smoking (AOR 1.72, 95% CI 1.01–2.92). During the pandemic, 32% (95% CI, 27–37%) of smokers increased, 37% (95% CI, 33–42%) decreased, and 31% (95% CI, 26–35%) did not change their cigarette consumption. Increased smoking was associated with higher perceived stress (AOR 1.49, 95% CI 1.16–1.91). Overall, 11% (95% CI, 8–14%) of respondents who smoked in January 2020 (pre-COVID-19) had quit smoking at survey (mean, 6 months later) while 28% (95% CI, 22–34%) of former smokers relapsed. Higher perceived COVID-19 risk was associated with higher odds of quitting and lower odds of relapse.ConclusionsMost smokers believed that smoking increased COVID-19 risk. Smokers’ responses to the pandemic varied, with increased smoking related to stress and increased quitting associated with perceived COVID-19 vulnerability.Supplementary InformationThe online version contains supplementary material available at 10.1007/s11606-021-06913-3.KEY WORDS: cigarette smoking, electronic cigarettes, COVID-19, risk perceptions     

Standardizing PaO2 for PaCO2 in P/F ratio predicts in-hospital mortality in acute respiratory failure due to Covid-19: A pilot prospective study

IntroductionUp to fifteen percent of patients with novel pandemic coronavirus disease (Covid-19) have acute respiratory failure (ARF). Ratio between arterial partial pressure of oxygen (PaO2) and fraction of inspired oxygen (FiO2), P/F, is currently used as a marker of ARF severity in Covid-19. P/F does not reflect the respiratory efforts made by patients to maintain arterial blood oxygenation, such as tachypnea and hyperpnea, leading to hypocapnia. Standard PaO2, the value of PaO2 adjusted for arterial partial pressure of carbon dioxide (PaCO2) of the subject, better reflects the pathophysiology of hypoxemic ARF. We hypothesized that the ratio between standard PaO2 over FiO2 (STP/F) better predicts Covid-19 ARF severity compared to P/F.MethodsAim of this pilot prospectic observational study was to observe differences between STP/F and P/F in predicting outcome failure, defined as need of invasive mechanical ventilation and/or deaths in Covid-19 ARF. Accuracy was calculated using Receiver Operating Characteristics (ROC) analysis and areas under the ROC curve (AUROC) were compared.Results349 consecutive subjects admitted to our respiratory wards due to Covid-19 ARF were enrolled. STP/F was accurate to predict mortality and superior to P/F with, respectively, AUROC 0.710 versus 0.688, p = 0.012.Both STP/F and PF were accurate to predict outcome failure (AUROC respectively of 0.747 and 0.742, p = 0.590).DiscussionThis is the first study assessing the role of STP/F in describing severity of ARF in Covid-19. According to results, STP/F is accurate and superior to P/F in predicting in-hospital mortality.     

Left ventricular global longitudinal strain imaging in identifying subclinical myocardial dysfunction among covid-19 survivors

BackgroundCovid-19 is multi-system viral infection caused by SARS-CoV-2 virus. Apart from having acute severe respiratory illness causing high mortality, the disease also has a variety of cardiovascular manifestations contributing to morbidity as well as mortality. Cardiac dysfunction and myocarditis are well established complications of Covid-19 as evident in multiple studies after the Covid-19 pandemic. However it is not sufficiently studied in Indian patients either by Echocardiography or by any other imaging modalities like cardiac magnetic resonance imaging (MRI).MethodologyIn this study, we analysed the severity of Left ventricular(LV) dysfunction in Covid-19 survivors. A total of 100 consecutive patients of Covid-19 after one month of discharge who had no underlying cardiovascular diseases underwent echocardiography and global longitudinal strain (GLS) imaging. This study cohort included patients with mild 42 (42%),moderate 46(46%) and severe 12(12%) Covid-19 disease as defined by computerised tomography (CT) severity score.ResultWe observed that total 36(36%) patients had reduced ejection fraction(EF) which included 11 patients having EF <40% and remaining 25(25%) having EF 40–50% (p<0.002). Also 22 (22%) patients had abnormal global longitudinal strain (GLS) values with normal ejection fraction which is suggestive of subclinical myocarditis. We observed LV dysfunction in 7(19.5%) patients who had severe Covid-19 while mild to moderate LV dysfunction observed in 29(80.5%) non critical patients.ConclusionIn conclusion our study demonstrates that myocardial dysfunction is common in covid-19 regardless of disease severity. 2D-echocardiography with GLS is likely to detect early LV dysfunction among these patients.     

Effectiveness of mRNA COVID-19 vaccines in preventing SARS-CoV-2 infections and COVID-19 hospitalisations and deaths in elderly long-term care facility residents,Spain, weeks 53 2020 to 13 2021

Residents in long-term care facilities (LTCF) experienced a large morbidity and mortality during the COVID-19 pandemic in Spain and were prioritised for early COVID-19 vaccination. We used the screening method and population-based data sources to obtain estimates of mRNA COVID-19 vaccine effectiveness for elderly LTCF residents. The estimates were 71% (95% CI: 56–82%), 88% (95% CI: 75–95%), and 97% (95% CI: 92-99%), against SARS-CoV-2 infections (symptomatic and asymptomatic), and COVID-19 hospitalisations and deaths, respectively.     

Excess mortality impact of two epidemics of pandemic influenza A(H1N1pdm09) virus in Hong Kong

Hong Kong experienced two large epidemics of pandemic influenza A(H1N1pdm09). We used regression methods to estimate the excess mortality associated with each epidemic. The first epidemic of H1N1pdm09 peaked in September 2009 and was associated with 2·13 [95% confidence interval (CI): −8·08, 11·82] excess all-cause deaths per 100 000 population. The second epidemic of H1N1pdm09 in early 2011 was associated with 4·72 [95% CI: −0·70, 10·50] excess deaths per 100 000 population. More than half of the estimated excess all-cause deaths were attributable to respiratory causes in each epidemic. The reasons for substantial impact in the second wave remain to be clarified.     

Low-dose aspirin and cancer mortality: a meta-analysis of randomized trials

ObjectiveLow-dose aspirin is a common strategy for preventing cardiovascular disease and associated mortality. A recent individual patient data meta-analysis of 8 trials of low- and high-dose aspirin, with long-term follow-up, found important reductions in cancer mortality. We aimed to determine whether cancer mortality also is reduced by low-dose aspirin in the shorter term.MethodsWe conducted a comprehensive search of 10 electronic databases up to December 2011. We conducted a meta-analysis using data from all randomized clinical trials evaluating low-dose (75-325 mg) daily aspirin. We extracted data on non-cardiovascular disease mortality and cancer mortality. We pooled studies using a random-effects model and conducted a meta-regression. We supplemented this with a cumulative meta-analysis and trial sequential monitoring analysis.ResultsTwenty-three randomized studies reported on nonvascular death. There were 944 nonvascular deaths of 41,398 (2.28%) patients receiving low-dose aspirin and 1074 nonvascular deaths of 41,470 (2.58%) patients not receiving aspirin therapy. The relative risk of nonvascular death was 0.88 (95% confidence interval [CI], 0.81-0.96, I² = 0%). Eleven trials included data evaluating cancer mortality involving 16,066 patients. There were 162 of 7998 (2.02%) and 210 of 8068 (2.60%) cancer deaths among low-dose aspirin users versus non-aspirin users, respectively, reported over an average follow-up of 2.8 years. The relative risk of cancer mortality was 0.77 (95% CI, 0.63-0.95, I² = 0%). Studies demonstrated a significant treatment effect after approximately 4 years of follow-up. The optimal information size analysis showed that a sufficient number of patients had been randomized to provide convincing evidence of a preventive role of low-dose aspirin in nonvascular deaths.ConclusionNonvascular deaths, including cancer deaths, are reduced with low-dose aspirin.