Age-Adjusted Associations Between Comorbidity and Outcomes of COVID-19: A Review of the Evidence From the Early Stages of the Pandemic

COVID-19 inequalities in England: a mathematical modelling study of transmission risk and clinical vulnerability by socioeconomic status

BACKGROUND

The COVID-19 pandemic resulted in major inequalities in infection and disease burden between areas of varying socioeconomic deprivation in many countries, including England. Areas of higher deprivation tend to have a different population structure-generally younger-which can increase viral transmission due to higher contact rates in school-going children and working-age adults. Higher deprivation is also associated with a higher presence of chronic comorbidities, which were convincingly demonstrated to be risk factors for severe COVID-19 disease. These two major factors need to be combined to better understand and quantify their relative importance in the observed COVID-19 inequalities.

METHODS

We used UK Census data on health status and demography stratified by decile of the Index of Multiple Deprivation (IMD), which is a measure of socioeconomic deprivation. We calculated epidemiological impact using an age-stratified COVID-19 transmission model, which incorporated different contact patterns and clinical health profiles by decile. To separate the contribution of each factor, we considered a scenario where the clinical health profile of all deciles was at the level of the least deprived. We also considered the effectiveness of school closures and vaccination of over 65-year-olds in each decile.

RESULTS

In the modelled epidemics in urban areas, the most deprived decile experienced 9% more infections, 13% more clinical cases, and a 97% larger peak clinical size than the least deprived; we found similar inequalities in rural areas. Twenty-one per cent of clinical cases and 16% of deaths in England observed under the model assumptions would not occur if all deciles experienced the clinical health profile of the least deprived decile. We found that more deaths were prevented in more affluent areas during school closures and vaccination rollouts.

CONCLUSIONS

This study demonstrates that both clinical and demographic factors synergise to generate health inequalities in COVID-19, that improving the clinical health profile of populations would increase health equity, and that some interventions can increase health inequalities.

Modeling mechanisms underlying differential inflammatory responses to COVID-19 in type 2 diabetes using a patient-derived microphysiological organ-on-a-chip system

Background: COVID-19 pandemic has caused more than 6 million deaths worldwide. Co-morbid conditions such as Type 2 Diabetes (T2D) have increased mortality in COVID-19. With limited translatability of in vitro and small animal models to human disease, human organ-on-a-chip models are an attractive platform to model in vivo disease conditions and test potential therapeutics. Methods: T2D or non-diabetic patient-derived macrophages and human liver sinusoidal endothelial cells were seeded, along with normal hepatocytes and stellate cells in the liver-on-a-chip (LAMPS - liver acinus micro physiological system), perfused with media mimicking non-diabetic fasting or T2D (high levels of glucose, fatty acids, insulin, glucagon) states. The macrophages and endothelial cells were transduced to overexpress the SARS-CoV2-S (spike) protein with appropriate controls before their incorporation into LAMPS. Cytokine concentrations in the efflux served as a read-out of the effects of S-protein expression in the different experimental conditions (non-diabetic-LAMPS, T2D-LAMPS), including incubation with tocilizumab, an FDA-approved drug for severe COVID-19. Findings: S-protein expression in the non-diabetic LAMPS led to increased cytokines, but in the T2D-LAMPS, this was significantly amplified both in the number and magnitude of key pro-inflammatory cytokines (IL6, CCL3, IL1β, IL2, TNFα, etc.) involved in cytokine storm syndrome (CSS), mimicking severe COVID-19 infection in T2D patients. Compared to vehicle control, tocilizumab (IL6-receptor antagonist) decreased the pro-inflammatory cytokine secretion in T2D-COVID-19-LAMPS but not in non-diabetic-COVID-19-LAMPS. Interpretation: macrophages and endothelial cells play a synergistic role in the pathophysiology of the hyper-inflammatory response seen with COVID-19 and T2D. The effect of Tocilizumab was consistent with large clinical trials that demonstrated Tocilizumab's efficacy only in critically ill patients with severe disease, providing confirmatory evidence that the T2D-COVID-19-LAMPS is a robust platform to model human in vivo pathophysiology of COVID-19 in T2D and for screening potential therapeutics.

Cross-sectional Characterization of SARS-CoV-2 Antibody Levels and Decay Rates Following Infection of Unvaccinated Elderly Individuals

Background

SARS-CoV-2 infections have disproportionally burdened elderly populations with excessive mortality. While several contributing factors exists, questions remain about the quality and duration of humoral antibody-mediated responses resulting from infections in unvaccinated elderly individuals.

Methods

Residual serum/plasma samples were collected from individuals undergoing routine SARS-CoV-2 polymerase chain reaction testing in a community laboratory in Canada. The samples were collected in 2020, before vaccines became available. IgG, IgA, and IgM antibodies against SARS-CoV-2 nucleocapsid, trimeric spike, and its receptor-binding domain were quantified via a high-throughput chemiluminescent enzyme-linked immunosorbent assay. Neutralization efficiency was also quantified through a surrogate high-throughput protein-based neutralization assay.

Results

This study analyzed SARS-CoV-2 antibody levels in a large cross-sectional cohort (N = 739), enriched for elderly individuals (median age, 82 years; 75% >65 years old), where 72% of samples tested positive for SARS-CoV-2 by polymerase chain reaction. The age group ≥90 years had higher levels of antibodies than that <65 years. Neutralization efficiency showed an age-dependent trend, where older persons had higher levels of neutralizing antibodies. Antibodies targeting the nucleocapsid had the fastest decline. IgG antibodies targeting the receptor-binding domain remained stable over time, potentially explaining the lack of neutralization decay observed in this cohort.

Conclusions

Despite older individuals having the highest levels of antibodies postinfection, they are the cohort in which antibody decay was the fastest. Until a better understanding of correlates of protection is acquired, along with the protective role of nonneutralizing antibodies, booster vaccinations remain important in this demographic.

The Incidence Proportion of SARS-CoV-2 Infections and the Percentage of Deaths among Infected Healthcare Workers in Poland

(1) Background: The incidence proportion of SARS-CoV-2 infection among healthcare workers (HCWs) in Poland is not exactly known. This study aims to present secondary epidemiological data identifying the scale of the spread of novel coronavirus infection and the estimation of vaccination coverage in selected professional groups of HCWs in Poland. (2) Methods: The secondary epidemiological data included both the number of infections and infection fatality rate (IFR) in individual occupational groups, which occurred throughout the observation period (January 2021-July 2022), both in the country and in individual voivodeship (administrative area). (3) Results: The incidence proportion of SARS-CoV-2 infections among HCWs was 16.48%. The highest percentage of infected workers concerned laboratory scientists (21.62%) and paramedics (18%). The highest frequency of infections among HCWs occurred in the province of Zachodnio-Pomorskie (18.9%). Due to COVID-19, 558 healthcare workers died during the analysed period, mostly nurses (n = 236) and doctors (n = 200). The results regarding the vaccination coverage of HCWs against COVID-19 indicate the highest percentage of vaccinated were among doctors (83.63%) and the lowest among physiotherapists (38.2%). (4) Conclusions: In general, the percentage of infections was high in Poland during the pandemic (16.48%). Significant territorial differences were observed in the frequency of infections, deaths, and percentage of vaccinated workers in individual voivodeships.

Blood Biomarkers from the Emergency Department Disclose Severe Omicron COVID-19-Associated Outcomes

Background: Since its outbreak, Coronavirus disease 2019 (COVID-19), a life-threatening respiratory illness, has rapidly become a public health emergency with a devastating social impact. Lately, the Omicron strain is considered the main variant of concern. Routine blood biomarkers are, indeed, essential for stratifying patients at risk of severe outcomes, and a huge amount of data is available in the literature, mainly for the previous variants. However, only a few studies are available on early routine biochemical blood biomarkers for Omicron-afflicted patients. Thus, the aim and novelty of this study were to identify routine blood biomarkers detected at the emergency room for the early prediction of severe morbidity and/or mortality. Methods: 449 COVID-19 patients from Sapienza University Hospital of Rome were divided into four groups: (1) the emergency group (patients with mild forms who were quickly discharged); (2) the hospital ward group (patients that after the admission in the emergency department were hospitalized in a COVID-19 ward); (3) the intensive care unit (ICU) group (patients that after the admission in the emergency department required intensive assistance); (4) the deceased group (patients that after the admission in the emergency department had a fatal outcome). Results: ANOVA and ROC data showed that high-sensitivity troponin-T (TnT), fibrinogen, glycemia, C-reactive protein, lactate dehydrogenase, albumin, D-dimer myoglobin, and ferritin for both men and women may predict lethal outcomes already at the level of the emergency department. Conclusions: Compared to previous Delta COVID-19 parallel emergency patterns of prediction, Omicron-induced changes in TnT may be considered other early predictors of severe outcomes.

Exploration of the psychometric properties of the novel General Medication Adherence Scale (GMAS) for chronic illness patients

OBJECTIVE

Many related scales have been developed and applied to measure patients' medication adherence, but the research on the psychometric characteristics of the scale still requires further studies. This study aims to provide further validation of the GMAS scale by using Rasch analysis and to make targeted recommendations for scale improvement.

METHODS

This is a cross-sectional study using secondary data. 312 Chinese adult patients were recruited from two tertiary hospitals and one community health service center in Tianjin to complete a questionnaire containing the GMAS, from January to June 2020. Participants included to have at least one chronic condition and also have been on medication for more than 3 months, but excluded patients with major life-threatening illnesses (e.g. heart failure, cancer), cognitive impairments preventing clear expression and significant communication difficulties. Rasch analysis was used to explore the psychometric properties of the GMAS scale. Key indicators including unidimensionality, validity and reliability, differential item functioning and degree of fit with Rasch model are validated.

RESULTS

After fitting the Rasch model for the first time, 56 samples poorly fitting the model were deleted. The remaining 256 samples were used for Rasch analysis. The results show that GMAS can fit the Rasch model well, which proves that the scale has favourable psychometric characteristics. But some items had differential item functioning in whether patients have comorbidities.

CONCLUSION

The GMAS was found to be useful as a screening tool for patients' medication adherence problems reported, except some issues to be addressed for further improvement of the scale.

Age and Comorbidity Burden of Patients Critically Ill with COVID-19 Affect Both Access to and Outcome of Ventilation Therapy in Intensive Care Units

During the COVID-19 pandemic, large numbers of elderly, multimorbid people required treatment in intensive care units. This study investigated how the inherent patient factors age and comorbidity burden affected the treatment strategy and the outcome achieved. Retrospective analysis of data from intensive care patients enrolled in the Lean European Open Survey on SARS-CoV2-Infected Patients (LEOSS) cohort found that a patient's age and comorbidity burden in fact influenced their mortality rate and the use of ventilation therapy. Evidence showed that advanced age and multimorbidity were associated with the restrictive use of invasive ventilation therapies, particularly ECMO. Geriatric patients with a high comorbidity burden were clustered in the sub-cohort of non-ventilated ICU patients characterized by a high mortality rate. The risk of death generally increased with older age and accumulating comorbidity burden. Here, the more aggressive an applied procedure, the younger the age in which a majority of patients died. Clearly, geriatric, multimorbid COVID-19 patients benefit less from invasive ventilation therapies. This implies the need for a holistic approach to therapy decisions, taking into account the patient's wishes.

Public health impact of UK COVID-19 booster vaccination programs during Omicron predominance

BACKGROUND

We aimed to estimate the public health impact of booster vaccination against COVID-19 in the UK during an Omicron-predominant period.

RESEARCH DESIGN AND METHODS

A dynamic transmission model was developed to compare public health outcomes for actual and alternative UK booster vaccination programs. Input sources were publicly available data and targeted literature reviews. Base case analyses estimated outcomes from the UK's Autumn-Winter 2021-2022 booster program during January-March 2022, an Omicron-predominant period. Scenario analyses projected outcomes from Spring and in Autumn 2022 booster programs over an extended time horizon from April 2022-April 2023, assuming continued Omicron predominance, and explored hypothetical program alternatives with modified eligibility criteria and/or increased uptake.

RESULTS

Estimates predicted that the Autumn-Winter 2021-2022 booster program averted approximately 12.8 million cases, 1.1 million hospitalizations, and 290,000 deaths. Scenario analyses suggested that Spring and Autumn 2022 programs would avert approximately 6.2 million cases, 716,000 hospitalizations, and 125,000 deaths; alternatives extending eligibility or targeting risk groups would improve these benefits, and increasing uptake would further strengthen impact.

CONCLUSIONS

Boosters were estimated to provide substantial benefit to UK public health during Omicron predominance. Benefits of booster vaccination could be maximized by extending eligibility and increasing uptake.

The natural killer cell-associated rs9916629-C allele is a novel genetic risk factor for fatal COVID-19

The severity of COVID-19 is associated with individual genetic host factors. Among these, genetic polymorphisms affecting natural killer (NK) cell responses, as variations in the HLA-E- (HLA-E*0101/0103), FcγRIIIa- (FcγRIIIa-158-F/V), and NKG2C- (KLRC2^wt/del ) receptor, were associated with severe COVID-19. Recently, the rs9916629-C/T genetic polymorphism was identified that indirectly shape the human NK cell repertoire towards highly pro-inflammatory CD56^bright NK cells. We investigated whether the rs9916629-C/T variants alone and in comparison to the other risk factors are associated with a fatal course of COVID-19. We included 1042 hospitalized surviving and 159 nonsurviving COVID-19 patients as well as 1000 healthy controls. rs9916629-C/T variants were genotyped by TaqMan assays and were compared between the groups. The patients' age, comorbidities, HLA-E*0101/0103, FcγRIIIa-158-F/V, and KLRC2^wt/del variants were also determined. The presence of the rs9916629-C allele was a risk factor for severe and fatal COVID-19 (p < 0.0001), independent of the patients' age or comorbidities. Fatal COVID-19 was more frequent in younger patients (<69.85 years) carrying the FcγRIIIa-158-V/V (p < 0.006) and in older patients expressing the KLRC2^del variant (p < 0.003). Thus, patients with the rs9916629-C allele have a significantly increased risk for fatal COVID-19 and identification of the genetic variants may be used as prognostic marker for hospitalized COVID-19 patients.

The syndromic triad of COVID-19, type 2 diabetes, and malnutrition

The coronavirus disease 2019 (COVID-19) pandemic challenges our collective understanding of transmission, prevention, complications, and clinical management of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Risk factors for severe infection, morbidity, and mortality are associated with age, environment, socioeconomic status, comorbidities, and interventional timing. Clinical investigations report an intriguing association of COVID-19 with diabetes mellitus and malnutrition but incompletely describe the triphasic relationship, its mechanistic pathways, and potential therapeutic approaches to address each malady and their underlying metabolic disorders. This narrative review highlights common chronic disease states that interact epidemiologically and mechanistically with the COVID-19 to create a syndromic phenotype-the COVID-Related Cardiometabolic Syndrome-linking cardiometabolic-based chronic disease drivers with pre-, acute, and chronic/post-COVID-19 disease stages. Since the association of nutritional disorders with COVID-19 and cardiometabolic risk factors is well established, a syndromic triad of COVID-19, type 2 diabetes, and malnutrition is hypothesized that can direct, inform, and optimize care. In this review, each of the three edges of this network is uniquely summarized, nutritional therapies discussed, and a structure for early preventive care proposed. Concerted efforts to identify malnutrition in patients with COVID-19 and elevated metabolic risks are needed and can be followed by improved dietary management while simultaneously addressing dysglycemia-based chronic disease and malnutrition-based chronic disease.

Machine learning and comorbidity network analysis for hospitalized patients with COVID-19 in a city in Southern Brazil

The large amount of data generated during the COVID-19 pandemic requires advanced tools for the long-term prediction of risk factors associated with COVID-19 mortality with higher accuracy. Machine learning (ML) methods directly address this topic and are essential tools to guide public health interventions. Here, we used ML to investigate the importance of demographic and clinical variables on COVID-19 mortality. We also analyzed how comorbidity networks are structured according to age groups. We conducted a retrospective study of COVID-19 mortality with hospitalized patients from Londrina, Parana, Brazil, registered in the database for severe acute respiratory infections (SIVEP-Gripe), from January 2021 to February 2022. We tested four ML models to predict the COVID-19 outcome: Logistic Regression, Support Vector Machine, Random Forest, and XGBoost. We also constructed a comorbidity network to investigate the impact of co-occurring comorbidities on COVID-19 mortality. Our study comprised 8358 hospitalized patients, of whom 2792 (33.40%) died. The XGBoost model achieved excellent performance (ROC-AUC = 0.90). Both permutation method and SHAP values highlighted the importance of age, ventilatory support status, and intensive care unit admission as key features in predicting COVID-19 outcomes. The comorbidity networks for old deceased patients are denser than those for young patients. In addition, the co-occurrence of heart disease and diabetes may be the most important combination to predict COVID-19 mortality, regardless of age and sex. This work presents a valuable combination of machine learning and comorbidity network analysis to predict COVID-19 outcomes. Reliable evidence on this topic is crucial for guiding the post-pandemic response and assisting in COVID-19 care planning and provision.

Cost-Effectiveness Analysis of Molnupiravir Versus Best Supportive Care for the Treatment of Outpatient COVID-19 in Adults in the US

BACKGROUND AND AIMS

Coronavirus disease 2019 (COVID-19) imposes a substantial and ongoing burden on the US healthcare system and society. Molnupiravir is a new oral antiviral for treating COVID-19 in outpatient settings. This study evaluated the cost-effectiveness profile of molnupiravir versus best supportive care in the treatment of adult patients with mild-to-moderate COVID-19 at risk of progression to severe disease, from a US payer's perspective.

METHODS

The model was developed using a decision tree for the short-term acute phase of COVID-19 and a Markov state transition model for the long-term post-acute phase. This model compared molnupiravir with best supportive care as consistent with the MOVe-OUT trial. Costs were reported in 2021 US dollars. Transition probabilities were derived from the phase III MOVe-OUT trial and the TriNetX real-world electronic health records database. Costs were derived from the TriNetX database and utility values from a de novo, vignette-based utility study. Deterministic and probabilistic sensitivity analyses (DSA/PSA) were conducted. Primary outcomes included proportion hospitalized, proportion who died overall and by highest healthcare setting at the end of the acute phase, quality-adjusted life-years (QALYs), and incremental costs per QALY gained over a lifetime (100 years) horizon, discounted at 3% annually and assessed at a willingness-to-pay (WTP) threshold of $100,000 per QALY.

RESULTS

In this model, the use of molnupiravir led to an increase in QALYs (0.210) and decrease in direct total medical costs (-$895) per patient across a lifetime horizon, compared with best supportive care in COVID-19 outpatients. Molnupiravir was the dominant intervention when compared with best supportive care. Patients treated with molnupiravir were less likely to be hospitalized (6.38% vs. 9.20%) and more likely to remain alive (99.88% vs. 98.71%) during the acute phase. Through DSA, molnupiravir treatment effect of hospitalization reduction was identified to be the most influential parameter, and through PSA, molnupiravir remained dominant in 84% of the total simulations and, overall, 100% cost effective.

CONCLUSION

This analysis suggests that molnupiravir is cost effective compared with best supportive care for the treatment of adult outpatients with COVID-19. However, our study was limited by the unavailability of the most recent information on the rapidly evolving pandemic, including new viral variants, patient populations affected, and changes in standards of care. Further research should explore the impact of vaccination on the cost effectiveness of molnupiravir and other therapies, based on real-world data, to account for these changes, including the impact of vaccination and immunity.

Comparison of the First and Second Wave of Infections by SARS-CoV-2: A Retrospective and Longitudinal Study From a Primary Health Care Center in Santiago of Chile

The current COVID-19 pandemic is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Many countries have reported the experience of at least two contagion waves, describing associated mortality rates and population behavior. The analysis of the effect of this pandemic in different localities can provide valuable information on the key factors to consider in the face of future massive infectious diseases. This work describes the first retrospective and comparative study about behavior during the first and second waves of the COVID-19 pandemic in Chile from a primary Healthcare Center. From 19,313 real-time quantitative PCR (RT-qPCR) tests assessed, the selected 1,694 positive diagnostics showed a decrease in mortality rate in the second wave (0.6%) compared with the first (4.6%). In addition, we observed that infections in the second wave were mainly in young patients with reduced comorbidities. The population with a complete vaccination schedule shows a decrease in the duration of symptoms related to the disease, and patients with more comorbidities tend to develop severe illness. This report provides evidence to partially understand the behavior and critical factors in the severity of the COVID-19 pandemic in the population of Santiago of Chile.

High mortality of COVID-19 early after allogeneic stem cell transplantation – a retrospective multicenter analysis on behalf of the German Cooperative Transplant Study Group

Recipients of allogeneic stem cell transplantation (alloSCT) are at high risk for contracting infectious diseases with high morbidity and mortality. Coronavirus disease 2019 (COVID-19) is a viral respiratory disease that can lead to severe pneumonia and acute respiratory distress syndrome, with a potentially fatal outcome. In this retrospective study conducted on behalf of the German Cooperative Transplant Study Group, we aimed to analyze risk factors, disease course, and outcomes of COVID-19 in patients who underwent alloSCT. AlloSCT recipients who became infected with SARS-CoV-2 at German and Austrian transplant centers between February 2020 and July 2021 were included. Classification of COVID-19 severity into mild, moderate-severe, or critical disease and division of the course of the pandemic into 4 phases were done according to the German Robert Koch Institute. The main endpoint was overall mortality at the end of follow-up. We further analyzed the need for treatment in an intensive care unit (ICU) and the severity of disease. Risk factors were evaluated using univariate and multivariate analyses, and survival analysis was performed using Kaplan-Meier method. The study cohort comprised 130 patients from 14 transplant centers, with a median age at diagnosis of COVID-19 of 59 years (range, 20 to 81 years) and a median interval between alloSCT and COVID-19 of 787 days (range, 19 to 8138 days). The most common underlying diseases were acute myeloid leukemia (45.4%) and lymphoma (10.8%). The majority of patients (84.9%) were infected in the later phases of the pandemic; 20.8% had moderate-severe disease, 12.3% had critical disease, and 19.2% were treated in an ICU. After a median follow-up of 127 days, overall mortality was 16.2%, 52.0% among patients treated in an ICU. Risk factors for mortality in multivariate analysis were active disease (odds ratio [OR], 4.46), infection with SARS-CoV-2 ≤365 days after alloSCT (OR, 5.60), age >60 years (OR, 5.39), and ongoing immunosuppression with cyclosporine (OR, 8.55). Risk factors for developing moderate-severe or critical disease were concurrent immunosuppression (OR, 4.06) and age >40 years (OR, 4.08). Patients after alloSCT exhibit a substantially increased mortality risk after COVID-19 infection compared with the normal population, without considerable improvement over the course of the pandemic. Risk factors include age, early infection post-alloSCT, and active immunosuppression. Further studies are needed to improve prevention and treatment in this high-risk patient group.

COVID-19 orphans-Global patterns associated with the hidden pandemic

Whilst the COVID-19 pandemic has caused significant mortality across the globe, many children have been orphaned due to the loss of their parents. Using the framework of an ecological analysis, we used estimates of total maternal/paternal orphans using an online COVID-19 orphanhood calculator to estimate the total orphans per COVID-19 death for 139 countries. Descriptive statistics were used to determine global patterns behind this risk of children being orphaned. Linear regression models were fitted to determine factors associated with this risk, and the association with vaccination coverage was calculated. We found that there is tremendous global variation in the risk that COVID-19 deaths will lead to orphaned children, and that this risk is higher in countries below median GDP per capita (1·56 orphans per deaths) compared to countries above (0·09 orphans per death). Poverty prevalence (B = 2·32, p<0·01), GDP per capita (B = -0·23, p<0·05), and a greater proportion of people with NCDs being reproductive aged (B = 1·46, p<0·0001) were associated with this risk. There was a negative correlation between 2nd dose vaccination coverage and orphans per death (p<0·05). The risk of children being orphaned per COVID-19 death, alongside fertility rate, is due to there being a greater share of COVID-19 deaths among younger persons. This is more likely in poorer countries and those where the age distribution for non-communicable diseases that elevate COVID-19 mortality risk are more uniform. Due to vaccine coverage inequity, more children will suffer the loss of their parents in poorer countries.

Public health impact of booster vaccination against COVID-19 in the UK during Delta variant dominance in autumn 2021

AIM

To evaluate the public health impact of the UK COVID-19 booster vaccination program in autumn 2021, during a period of SARS-CoV-2 Delta variant predominance.

MATERIALS AND METHODS

A compartmental Susceptible-Exposed-Infectious-Recovered model was used to compare age-stratified health outcomes for adult booster vaccination versus no booster vaccination in the UK over a time horizon of September-December 2021, when boosters were introduced in the UK and the SARS-CoV-2 Delta variant was predominant. Model input data were sourced from targeted literature reviews and publicly available data. Outcomes were predicted COVID-19 cases, hospitalizations, post-acute sequelae of COVID-19 (PASC) cases, deaths, and productivity losses averted, and predicted healthcare resources saved. Scenario analyses varied booster coverage, virus infectivity and severity, and time horizon parameters.

RESULTS

Booster vaccination was estimated to have averted approximately 547,000 COVID-19 cases, 36,000 hospitalizations, 147,000 PASC cases, and 4,200 deaths in the UK between September and December 2021. It saved over 316,000 hospital bed-days and prevented the loss of approximately 16.5 million paid and unpaid patient work days. In a scenario of accelerated uptake, the booster rollout would have averted approximately 3,400 additional deaths and 25,500 additional hospitalizations versus the base case. A scenario analysis assuming four-fold greater virus infectivity and lower severity estimated that booster vaccination would have averted over 105,000 deaths and over 41,000 hospitalizations versus the base case. A scenario analysis assuming pediatric primary series vaccination prior to adult booster vaccination estimated that expanding vaccination to children aged ≥5 years would have averted approximately 51,000 additional hospitalizations and 5,400 additional deaths relative to adult booster vaccination only.

LIMITATIONS

The model did not include the wider economic burden of COVID-19, hospital capacity constraints, booster implementation costs, or non-pharmaceutical interventions.

CONCLUSIONS

Booster vaccination during Delta variant predominance reduced the health burden of SARS-CoV-2 in the UK, releasing substantial NHS capacity.

Changes in Inflammatory Markers after Administration of Tocilizumab in COVID-19: A Single-Center Retrospective Study

The COVID-19 pandemic requires the development of effective methods for the treatment of severe cases. We aimed to describe clinical outcomes and changes in inflammatory markers in Polish patients treated with tocilizumab. The medical charts of SARS-CoV-2-positive patients treated in the Department of Infectious Diseases between 4 March and 2 September 2020 were retrospectively analyzed. The patients who received tocilizumab according to the Polish Association of Epidemiologists and Infectiologists guidelines were selected for the study. We identified 29 individuals who received tocilizumab, out of whom 11 (37.9%) died. The individuals who died had significantly higher maximal interleukin-6 (IL-6) and lactate dehydrogenase (LDH) serum levels than survivors. After administration of tocilizumab, further increase in LDH and IL-6 was a prognostic factor for unfavorable outcomes. Among inflammatory markers, 7-day mean of IL-6 serum concentration was the best predictor of death (cut-off: ≥417 pg/mL; area under ROC curve = 0.81 [95% Confidence Interval: 0.63-0.98]). The serum concentrations of inflammatory markers before administration of tocilizumab did not predict the outcome, whereas IL-6 and LDH measurements after administration of tocilizumab seemed to be of predictive value.

Prevention of Cardiovascular Burden in COVID-19 Patients Suffering from Familial Hypercholesterolemia: A Global Challenge

A recent meta-analysis of over 20,000 individuals showed that hospitalized COVID-19 patients with acute myocardial injury had more than fourfold higher mortality than those without such injury. Since the COVID-19 pandemic exacerbates already existing health inequalities, there is an urgent need to create measures to protect the most vulnerable patient groups, including those with a pre-existing increased risk of atherosclerotic cardiovascular disease (ASCVD). A typical example is familial hypercholesterolemia (FH), a common genetic disease affecting over 30 million individuals worldwide. If left untreated or undertreated, FH patients suffer from complications of premature ASCVD, such as acute coronary syndromes, resulting in acute myocardial injury/infarction. A recent population-based analysis provided strong evidence suggesting that COVID-19 poses an even higher risk for myocardial injury in FH patients. From the long-term preventive point of view, it is important to note that, in addition to the acutely elevated risk of myocardial injury, an elevated risk of ASCVD and its complications will persist after COVID-19. The decline in outpatient preventive care during the pandemic is likely to influence ASCVD risk and outcomes, particularly in high-risk patients, such as those with FH. This commentary aims to raise global awareness of the challenges that clinicians treating FH patients continue to face during the COVID-19 pandemic, with two low- to middle-income countries, South Africa and Brazil, serving as examples.

Asymptomatic COVID-19 and ST-elevation myocardial infarction in young adults: lessons learned from two similar cases

We present two cases of acute myocardial infarction in young patients with asymptomatic COVID‐19 infection and ST‐elevation myocardial infarction (STEMI), complicated by severe acute heart failure and ventricular fibrillation, resulting cardiopulmonary resuscitation and mechanical ventilatory support. Urgent primary percutaneous coronary intervention with further complex treatment was effective in both cases with critical cardiovascular state and co‐morbid COVID‐19 infection. This report illustrates the challenges in clinical severity of STEMI with COVID‐19 infection, despite of young age and absence of clinical symptoms and chronic co‐morbidities. STEMI patients with even asymptomatic COVID‐19 infection may be presented with significantly higher rates of severe acute heart failure.

COVID-19 Outcomes and Genomic Characterization of SARS-CoV-2 Isolated From Veterans in New England States: Retrospective Analysis

BACKGROUND

Clinical and virologic characteristics of COVID-19 infections in veterans in New England have not been described. The average US veteran is a male older than the general US population. SARS-CoV-2 infection is known to cause poorer outcomes among men and older adults, making the veteran population an especially vulnerable group for COVID-19.

OBJECTIVE

This study aims to evaluate clinical and virologic factors impacting COVID-19 outcomes.

METHODS

This retrospective chart review included 476 veterans in six New England states with confirmed SARS-CoV-2 infection between April and September 2020. Whole genome sequencing was performed on SARS-CoV-2 RNA isolated from these veterans, and the correlation of genomic data to clinical outcomes was evaluated. Clinical and demographic variables were collected by manual chart review and were correlated to the end points of peak disease severity (based on oxygenation requirements), hospitalization, and mortality using multivariate regression analyses.

RESULTS

Of 476 veterans, 274 had complete and accessible charts. Of the 274 veterans, 92.7% (n=254) were men and 83.2% (n=228) were White, and the mean age was 63 years. In the multivariate regression, significant predictors of hospitalization (C statistic 0.75) were age (odds ratio [OR] 1.05, 95% CI 1.03-1.08) and non-White race (OR 2.39, 95% CI 1.13-5.01). Peak severity (C statistic 0.70) also varied by age (OR 1.07, 95% CI 1.03-1.11) and O2 requirement on admission (OR 45.7, 95% CI 18.79-111). Mortality (C statistic 0.87) was predicted by age (OR 1.06, 95% CI 1.01-1.11), dementia (OR 3.44, 95% CI 1.07-11.1), and O2 requirement on admission (OR 6.74, 95% CI 1.74-26.1). Most (291/299, 97.3%) of our samples were dominated by the spike protein D614G substitution and were from SARS-CoV-2 B.1 lineage or one of 37 different B.1 sublineages, with none representing more than 8.7% (26/299) of the cases.

CONCLUSIONS

In a cohort of veterans from the six New England states with a mean age of 63 years and a high comorbidity burden, age was the largest predictor of hospitalization, peak disease severity, and mortality. Non-White veterans were more likely to be hospitalized, and patients who required oxygen on admission were more likely to have severe disease and higher rates of mortality. Multiple SARS-CoV-2 lineages were distributed in patients in New England early in the COVID-19 era, mostly related to viruses from New York State with D614G mutation.

Modifiable Risk Factors for SARS-CoV-2

As the COVID-19 pandemic has raged on, considerable research has been performed around the world evaluating the environmental, genetic, lifestyle, and nutritional factors that significantly impact the COVID-19 pandemic. Many studies have now shown that key risk factors for SARS-CoV-2 infection, severity, and even death are modifiable. Patients, whether partially vaccinated, fully vaccinated, or not vaccinated, are expecting their clinicians to provide them with evidence-based guidance and to help them prioritize the factors most important for them. In this editorial we review the current state of the research on modifiable risk factors for SARS-CoV-2 infection, disease severity, and death.