Cohort Profile: The epidemiology of chronic diseases and multimorbidity. The EpiChron cohort study

Why was the cohort set up? Greater life expectancy in Europe over the past few decades has been translated into an increasing burden of chronic diseases that accumulate as the population ages, whereas acute infectious diseases have been progressively pushed into the background. The incidence of conditions such as hypertension, obesity and asthma has increased dramatically worldwide, and cancer, diabetes and respiratory and cardiovascular diseases are responsible for almost 70% of global deaths. Concurrently, the prevalence of multimorbidity (as of people affected by more than one chronic disorder) is also increasing and appears as the most common chronic condition at present. Multimorbidity affects almost 3 in 4 individuals aged 65 years and older, although it represents a problem not only for the elderly but also for adult and even young populations, at whom prevention strategies should aim. People affected by multimorbidity often experience fragmentation of care, greater and inadequate use of health services and polypharmacy, which in turn may increase the risk of low adherence and adverse drug reactions. All of this leads to individuals’ quality of life deterioration and higher risk of mortality. Besides, handling patients with multimorbidity represents a daily challenge for physicians and health systems..

Identifying multimorbidity profiles associated with COVID-19 severity in chronic patients using network analysis in the PRECOVID Study; 35181720

A major risk factor of COVID-19 severity is the patient''s health status at the time of the infection. Numerous studies focused on specific chronic diseases and identified conditions, mainly cardiovascular ones, associated with poor prognosis. However, chronic diseases tend to cluster into patterns, each with its particular repercussions on the clinical outcome of infected patients. Network analysis in our population revealed that not all cardiovascular patterns have the same risk of COVID-19 hospitalization or mortality and that this risk depends on the pattern of multimorbidity, besides age and sex. We evidenced that negative outcomes were strongly related to patterns in which diabetes and obesity stood out in older women and men, respectively. In younger adults, anxiety was another disease that increased the risk of severity, most notably when combined with menstrual disorders in women or atopic dermatitis in men. These results have relevant implications for organizational, preventive, and clinical actions to help meet the needs of COVID-19 patients. © 2022, The Author(s)

Baseline chronic comorbidity and mortality in laboratory-confirmed COVID-19 cases: Results from the PRECOVID study in Spain

We aimed to analyze baseline socio-demographic and clinical factors associated with an increased likelihood of mortality in men and women with coronavirus disease (COVID-19). We conducted a retrospective cohort study (PRECOVID Study) on all 4412 individuals with laboratory-confirmed COVID-19 in Aragon, Spain, and followed them for at least 30 days from cohort entry. We described the socio-demographic and clinical characteristics of all patients of the cohort. Age-adjusted logistic regressions models were performed to analyze the likelihood of mortality based on demographic and clinical variables. All analyses were stratified by sex. Old age, specific diseases such as diabetes, acute myocardial infarction, or congestive heart failure, and dispensation of drugs like vasodilators, antipsychotics, and potassium-sparing agents were associated with an increased likelihood of mortality. Our findings suggest that specific comorbidities, mainly of cardiovascular nature, and medications at the time of infection could explain around one quarter of the mortality in COVID-19 disease, and that women and men probably share similar but not identical risk factors. Nonetheless, the great part of mortality seems to be explained by other patient-and/or health-system-related factors. More research is needed in this field to provide the necessary evidence for the development of early identification strategies for patients at higher risk of adverse outcomes