Age-adjusted associations between comorbidity and outcomes of COVID-19: a review of the evidence

ABSTRACT Background Current evidence suggests that older people and people with underlying comorbidities are at increased risk of severe disease and death following hospitalisation with COVID-19. As comorbidity increases with age, it is necessary to understand the age-adjusted relationship between comorbidity and COVID-19 outcomes, in order to enhance planning capabilities and our understanding of COVID-19. Methods We conducted a rapid, comprehensive review of the literature up to 10 April 2020, to assess the international empirical evidence on the association between comorbidities and severe or critical care outcomes of COVID-19, after accounting for age, among hospitalised patients with COVID-19. Results After screening 579 studies, we identified seven studies eligible for inclusion and these were synthesised narratively. All were from China. The emerging evidence base mostly indicates that after adjustment for age (and in some cases other potential confounders), obesity, hypertension, diabetes mellitus, chronic obstructive airways disease (COPD), and cancer are all associated with worse outcomes. The largest study, using a large nationwide sample of COVID-19 patients in China, found that those with multiple comorbidities had more than twice the risk of a severe outcome or death compared with patients with no comorbidities, after adjusting for age and smoking (HR=2.59, 95% CI 1.61, 4.17). Conclusions This review summarises for clinicians, policymakers, and academics the most robust evidence to date on this topic, to inform the management of patients and control measures for tackling the pandemic. Given the intersection of comorbidity with ethnicity and social disadvantage, these findings also have important implications for health inequalities. As the pandemic develops, further research should confirm these trends in other settings outside China and explore mechanisms by which various underlying health conditions increase risk of severe COVID-19

Predicting respiratory failure in patients infected by SARS-CoV-2 by admission sex-specific biomarkers

Background: Several biomarkers have been identified to predict the outcome of COVID-19 severity, but few data are available regarding sex differences in their predictive role. Aim of this study was to identify sex-specific biomarkers of severity and progression of acute respiratory distress syndrome (ARDS) in COVID-19. Methods: Plasma levels of sex hormones (testosterone and 17β-estradiol), sex-hormone dependent circulating molecules (ACE2 and Angiotensin1-7) and other known biomarkers for COVID-19 severity were measured in male and female COVID-19 patients at admission to hospital. The association of plasma biomarker levels with ARDS severity at admission and with the occurrence of respiratory deterioration during hospitalization was analysed in aggregated and sex disaggregated form. Results: Our data show that some biomarkers could be predictive both for males and female patients and others only for one sex. Angiotensin1-7 plasma levels and neutrophil count predicted the outcome of ARDS only in females, whereas testosterone plasma levels and lymphocytes counts only in males. Conclusions: Sex is a biological variable affecting the choice of the correct biomarker that might predict worsening of COVID-19 to severe respiratory failure. The definition of sex specific biomarkers can be useful to alert patients to be safely discharged versus those who need respiratory monitoring

Laboratory biomarkers associated to death in the first three COVID-19 waves in Portugal

Funding Information: This study is inserted in the project Predictive Models of COVID-19 Outcomes for Higher Risk Patients Towards a Precision Medicine (PREMO), supported by Fundação para Publisher Copyright: © 2023 IEEE.Besides the pandemic being over, new SARS-CoV-2 lineages, and sub-lineages, still pose risks to global health. Thus, in this preliminary study, to better understand the characteristics of COVID-19 patients and the effect of certain hematologic biomarkers on their outcome, we analyzed data from 337 patients admitted to the ICU of a single-center hospital in Lisbon, Portugal, in the first three waves of the pandemic. Most patients belonged to the second (40.4%) and third (41.2%) waves. The ones from the first wave were significantly older and relied more on respiratory techniques like invasive mechanic ventilation and extracorporeal membrane oxygenation. There were no significant differences between waves regarding mortality in the ICU. In general, non-survivors had worse laboratory results. Biomarkers significantly associated with death changed depending on the waves. Increased high-sensitivity cardiac troponin I results, and lower eosinophil counts were associated to death in all waves. In the second and third waves, the international normalized ratio, lymphocyte counts, and neutrophil counts were also associated to mortality. A higher risk of death was linked to increased myoglobin results in the first two waves, as well as increased creatine kinase results, and lower platelet counts in the third wave.publishersversionpublishe

Ethnic Disparities in Hospitalization for COVID-19: a Community-Based Cohort Study in the UK

Importance: Differentials in COVID-19 incidence, hospitalization and mortality according to ethnicity are being reported but their origin is uncertain. Objective: We aimed to explain any ethnic differentials in COVID-19 hospitalization based on socioeconomic, lifestyle, mental and physical health factors. Design: Prospective cohort study with national registry linkage to hospitalisation for COVID-19. Setting: Community-dwelling. Participants: 340,966 men and women (mean age 56.2 (SD=8.1) years; 54.3% women) residing in England from the UK Biobank study. Exposures: Ethnicity classified as White, Black, Asian, and Others. Main Outcome(s) and Measure(s): Cases of COVID-19 serious enough to warrant a hospital admission in England from 16-March-2020 to 26-April-2020. Results: There were 640 COVID-19 cases (571/324,306 White, 31/4,485 Black, 21/5,732 Asian, 17/5,803 Other). Compared to the White study members and after adjusting for age and sex, Black individuals had over a 4-fold increased risk of being hospitalised (odds ratio; 95% confidence interval: =4.32; 3.00-6.23), and there was a doubling of risk in the Asian group (2.12; 1.37, 3.28) and the Other non-white group (1.84; 1.13, 2.99). After controlling for 15 confounding factors which included neighbourhood deprivation, education, number in household, smoking, markers of body size, inflammation, and glycated haemoglobin, these effect estimates were attenuated by 33% for Blacks, 52% for Asians and 43% for Other, but remained raised for Blacks (2.66; 1.82, 3.91), Asian (1.43; 0.91, 2.26) and other non-white groups (1.41; 0.87, 2.31). Conclusions and Relevance: Our findings show clear ethnic differences in risk of hospitalization for COVID-19 which do not appear to be fully explained by known explanatory factors. If replicated, our results have implications for health policy, including the targeting of prevention advice and vaccination coverage

Immunological Biomarkers of Fatal COVID-19: A Study of 868 Patients

Information on the immunopathobiology of coronavirus disease 2019 (COVID-19) is rapidly increasing; however, there remains a need to identify immune features predictive of fatal outcome. This large-scale study characterized immune responses to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection using multidimensional flow cytometry, with the aim of identifying high-risk immune biomarkers. Holistic and unbiased analyses of 17 immune cell-types were conducted on 1,075 peripheral blood samples obtained from 868 COVID-19 patients and on samples from 24 patients presenting with non-SARS-CoV-2 infections and 36 healthy donors. Immune profiles of COVID-19 patients were significantly different from those of age-matched healthy donors but generally similar to those of patients with non-SARS-CoV-2 infections. Unsupervised clustering analysis revealed three immunotypes during SARS-CoV-2 infection; immunotype 1 (14% of patients) was characterized by significantly lower percentages of all immune cell-types except neutrophils and circulating plasma cells, and was significantly associated with severe disease. Reduced B-cell percentage was most strongly associated with risk of death. On multivariate analysis incorporating age and comorbidities, B-cell and non-classical monocyte percentages were independent prognostic factors for survival in training (n=513) and validation (n=355) cohorts. Therefore, reduced percentages of B-cells and non-classical monocytes are high-risk immune biomarkers for risk-stratification of COVID-19 patients

Lack of Association of the ABO Blood Group with COVID-19 risk and Severity in Hospitalized Patients in Louisville, KY

Background: The potential association of the ABO blood group with the risk of COVID-19 and its severity has attracted a lot of interest since the start of the pandemic. While a number of studies have reported an increased risk associated with blood type A and a reduced risk with type O, other studies have did not found a significant effect. This study aimed to define the prevalence of different ABO blood groups in hospitalized COVID-19 patients in the Louisville, KY area and to investigate whether an association exists between the blood group and disease severity. Methods: This was a retrospective observational study of 380 patients with SARS-CoV-2 infection hospitalized to eight of the adult hospitals in the city of Louisville. Patients were divided into four different groups according to their ABO blood type. Demographic characteristics and clinical variables, including laboratory data as well as clinical outcomes were compared. Results: Type O was the most common blood group among the hospitalized patients (51%) followed by type A (31%), B (14%) and AB (4%). The observed blood group distribution among the patients was not significantly different from the distribution expected when compared to a population of similar racial/ethnic composition. No significant associations were found between the blood group and comorbidities, inflammatory biomarkers as well as with recorded outcomes, including the mortality rate and the length of the hospital stay. Conclusions: The data from hospitalized patients in Louisville is is not consistent with the ABO blood group having a significant effect as a risk or severity factor for COVID-19, but it is representative in COVID-19 or its severityof its prevalence among different racial/ethnic populations

Exposing and Overcoming Limitations of Clinical Laboratory Tests in COVID-19 by Adding Immunological Parameters; A Retrospective Cohort Analysis and Pilot Study

BackgroundTwo years since the onset of the COVID-19 pandemic no predictive algorithm has been generally adopted for clinical management and in most algorithms the contribution of laboratory variables is limited. ObjectivesTo measure the predictive performance of currently used clinical laboratory tests alone or combined with clinical variables and explore the predictive power of immunological tests adequate for clinical laboratories. Methods: Data from 2,600 COVID-19 patients of the first wave of the pandemic in the Barcelona area (exploratory cohort of 1,579, validation cohorts of 598 and 423 patients) including clinical parameters and laboratory tests were retrospectively collected. 28-day survival and maximal severity were the main outcomes considered in the multiparametric classical and machine learning statistical analysis. A pilot study was conducted in two subgroups (n=74 and n=41) measuring 17 cytokines and 27 lymphocyte phenotypes respectively. Findings1) Despite a strong association of clinical and laboratory variables with the outcomes in classical pairwise analysis, the contribution of laboratory tests to the combined prediction power was limited by redundancy. Laboratory variables reflected only two types of processes: inflammation and organ damage but none reflected the immune response, one major determinant of prognosis. 2) Eight of the thirty variables: age, comorbidity index, oxygen saturation to fraction of inspired oxygen ratio, neutrophil-lymphocyte ratio, C-reactive protein, aspartate aminotransferase/alanine aminotransferase ratio, fibrinogen, and glomerular filtration rate captured most of the combined statistical predictive power. 3) The interpretation of clinical and laboratory variables was moderately improved by grouping them in two categories i.e., inflammation related biomarkers and organ damage related biomarkers; Age and organ damage-related biomarker tests were the best predictors of survival, and inflammatory-related ones were the best predictors of severity. 4) The pilot study identified immunological tests (CXCL10, IL-6, IL-1RA and CCL2), that performed better than most currently used laboratory tests. ConclusionsLaboratory tests for clinical management of COVID 19 patients are valuable but limited predictors due to redundancy; this limitation could be overcome by adding immunological tests with independent predictive power. Understanding the limitations of tests in use would improve their interpretation and simplify clinical management but a systematic search for better immunological biomarkers is urgent and feasible

The Interplay between Housing Environmental Attributes and Design Exposures and Psychoneuroimmunology Profile-An Exploratory Review and Analysis Paper in the Cancer Survivors' Mental Health Morbidity Context

Adult cancer survivors have an increased prevalence of mental health comorbidities and other adverse late-effects interdependent with mental illness outcomes compared with the general population. Coronavirus Disease 2019 (COVID-19) heralds an era of renewed call for actions to identify sustainable modalities to facilitate the constructs of cancer survivorship care and health care delivery through physiological supportive domestic spaces. Building on the concept of therapeutic architecture, psychoneuroimmunology (PNI) indicators—with the central role in low-grade systemic inflammation—are associated with major psychiatric disorders and late effects of post-cancer treatment. Immune disturbances might mediate the effects of environmental determinants on behaviour and mental disorders. Whilst attention is paid to the non-objective measurements for examining the home environmental domains and mental health outcomes, little is gathered about the multidimensional effects on physiological responses. This exploratory review presents a first analysis of how addressing the PNI outcomes serves as a catalyst for therapeutic housing research. We argue the crucial component of housing in supporting the sustainable primary care and public health-based cancer survivorship care model, particularly in the psychopathology context. Ultimately, we illustrate a series of interventions aiming at how housing environmental attributes can trigger PNI profile changes and discuss the potential implications in the non-pharmacological treatment of cancer survivors and patients with mental morbidities

Analysis of inflammatory protein profiles in the circulation of COVID-19 patients identifies patients with severe disease phenotypes

Background: The coronavirus disease (COVID-19) caused by the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) can present with a broad range of clinical manifestations, ranging from asymptomatic to severe multiple organ failure. The severity of the disease can vary depending on factors such as age, sex, ethnicity, and pre-existing medical conditions. Despite multiple efforts to identify reliable prognostic factors and biomarkers, the predictive capacity of these markers for clinical outcomes remains poor. Circulating proteins, which reflect the active mechanisms in an individual, can be easily measured in clinical practice and therefore may be useful as biomarkers for COVID-19 disease severity. In this study, we sought to identify protein biomarkers and endotypes for COVID-19 severity and evaluate their reproducibility in an independent cohort.Methods: We investigated a cohort of 153 Greek patients with confirmed SARS-CoV-2 infection in which plasma protein levels were measured using the Olink Explore 1536 panel, which consists of 1472 proteins. We compared the protein profiles from severe and moderate COVID-19 patients to identify proteins associated with disease severity. To evaluate the reproducibility of our findings, we compared the protein profiles of 174 patients with comparable COVID-19 severities in a US COVID-19 cohort to identify proteins consistently correlated with COVID-19 severity in both groups.Results: We identified 218 differentially regulated proteins associated with severity, 20 proteins were also replicated in an external cohort which we used for validation. Moreover, we performed unsupervised clustering of patients based on 97 proteins with the highest log2 fold changes in order to identify COVID-19 endotypes. Clustering of patients based on differentially regulated proteins revealed the presence of three clinical endotypes. While endotypes 2 and 3 were enriched for severe COVID-19 patients, endotypes 3 represented the most severe form of the disease.Conclusions: These results suggest that identified circulating proteins may be useful for identifying COVID-19 patients with worse outcomes, and this potential utility may extend to other populations. Trial registration: NCT04357366.</p