RESUMO
OBJECTIVE: Coronavirus disease 2019 (COVID-19) can infect patients in any age group including those with no comorbid conditions. Understanding the demographic, clinical, and laboratory characteristics of these patients is important toward developing successful treatment strategies. Approach and Results: In a retrospective study design, consecutive patients without baseline comorbidities hospitalized with confirmed COVID-19 were included. Patients were subdivided into ≤55 and >55 years of age. Predictors of in-hospital mortality or mechanical ventilation were analyzed in this patient population, as well as subgroups. Stable parameters in overall and subgroup models were used to construct a cluster model for phenotyping of patients. Of 1207 COVID-19-positive patients, 157 met the study criteria (80≤55 and 77>55 years of age). Most reliable predictors of outcomes overall and in subgroups were age, initial and follow-up d-dimer, and LDH (lactate dehydrogenase) levels. Their predictive cutoff values were used to construct a cluster model that produced 3 main clusters. Cluster 1 was a low-risk cluster and was characterized by younger patients who had low thrombotic and inflammatory features. Cluster 2 was intermediate risk that also consisted of younger population that had moderate level of thrombosis, higher inflammatory cells, and inflammatory markers. Cluster 3 was a high-risk cluster that had the most aggressive thrombotic and inflammatory feature. CONCLUSIONS: In healthy patient population, COVID-19 remains significantly associated with morbidity and mortality. While age remains the most important predictor of in-hospital outcomes, thromboinflammatory interactions are also associated with worse clinical outcomes regardless of age in healthy patients.