The use of electronic health records and COVID-19 registries can bring potential improvements in population health, increasing research efficiency and data quality and management 16, 17, among other benefits. It can also give us valuable information to better understand the etiopathological characteristics of the infection and its complications, and potentially generate hypotheses for a more appropriate clinical management of patients with multiple chronic conditions. Characterization of the clinical profiles of the population at higher risk of hospitalization or mortality may help us effectively design and develop preventive strategies targeting people with specific chronic diseases (for both primary and secondary prevention). The continuously changing landscape of the COVID-19 pandemic with the appearance of new variants of the virus with high transmission rates and unpredictable severity calls scientists to identify vulnerable chronic patients.

In this sense, some studies have already suggested that patterns linked to low-grade systemic inflammation could be decisive in COVID-19 prognosis 11, though only a few have focused on identifying disease patterns with an impact on COVID-19 patients 12, 13, 14, 15.

It is expected that some patterns could affect COVID-19 prognosis in a more significant way than others, depending on the disease composition of each pattern and also on various factors such as sex and age. It is well known that chronic diseases tend to cluster into non-random patterns, usually referred to as multimorbidity patterns 10. However, multimorbidity (i.e., the presence of two or more chronic diseases) is the norm rather than the exception in chronic patients, especially in the elderly 9. To date, most studies on comorbidity and COVID-19 severity have analyzed the impact of some diseases individually. Cardiovascular and metabolic diseases such as obesity, heart failure, chronic renal failure, and diabetes mellitus 1, 7 have been consistently associated with a higher risk of severity, while the role of other conditions such as asthma remains unclear 8. The presence of certain chronic diseases at the time of infection seems to be another determining factor of COVID-19 severity. Nevertheless, we now know that male sex is a risk factor for poor prognosis 2, 3, 4 and that older patients, especially those over the age of 80, are more likely to develop more severe outcomes 5, 6. Severe outcomes and complications can occur at any age, even in previously healthy individuals 1. More than a year and a half later, and even though several factors related to poor prognosis have already been identified, the ongoing COVID-19 pandemic still represents a challenge for clinicians, healthcare systems and society. Immediately after the coronavirus disease (COVID-19) outbreak in December 2019, the clinical and research communities worldwide set their focus on identifying aspects that influence the disparity of symptoms and outcomes in infected individuals. These results have relevant implications for organizational, preventive, and clinical actions to help meet the needs of COVID-19 patients. 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. We evidenced that negative outcomes were strongly related to patterns in which diabetes and obesity stood out in older women and men, respectively. 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.

However, chronic diseases tend to cluster into patterns, each with its particular repercussions on the clinical outcome of infected patients. Numerous studies focused on specific chronic diseases and identified conditions, mainly cardiovascular ones, associated with poor prognosis. A major risk factor of COVID-19 severity is the patient's health status at the time of the infection.

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