AI Summary & Key Takeaways
AI InsightDetermining risk factors for COVID-19 severity and mortality are critical for classifying critical cases at the time of initial diagnosis, establishing appropriately specific treatment protocols, and ensuring access to early treatment.
📌 3 Key Takeaways
Abstract
Objective: It is increasingly important to identify risk factors for COVID-19-associated mortality to provide access to early treatment. This study aimed to investigate the relationship between COVID-19 severity and laboratory data and demographic characteristics of hospitalized patients and to identify factors predicting mortality in COVID-19. Materials and Methods: The study is a retrospective and single-center study. Data of 1298 COVID-19 patients confirmed by a positive real-time polymerase chain reaction test for COVID-19 and treated at the hospital were retrospectively analyzed. Study patients were divided into three groups based on the clinical severity of disease: the mild-moderate group (n:954) and the severe (n:310) and critical (n:34) groups. Demographic characteristics, underlying diseases, and laboratory findings were compared between groups. Results: Multivariate logistic and ordinal logistic regression analysis revealed that male gender, old age, diabetes mellitus, coronary artery disease, cerebrovascular event, malignancy, chronic obstructive pulmonary disease, chronic renal failure, chronic hepatitis B, and Alzheimer’s disease/dementia/Parkinson’s disease (among neurological diseases) were independently associated with and significantly increased the development of severe disease and mortality. Conclusion: The COVID-19 pandemic continues to be a significant health problem affecting all of humanity. Determining risk factors for COVID-19 severity and mortality are critical for classifying critical cases at the time of initial diagnosis, establishing appropriately specific treatment protocols, and ensuring access to early treatment.