J. Oman Med. Assoc., Volume 2, Issue 1 (June 2025) – 2 articles

Numerous factors contribute to COVID-19 symptoms, with individuals who have pre-existing health conditions at the highest risk for severe SARS-CoV-2 infection. This study investigated the socio-demographic and comorbidity profiles within a large Turkish population diagnosed with SARS-CoV-2, including 47,875 patients diagnosed between March 2020 and May 2022 across six hospitals in different Turkish cities. Patients with SARS-CoV-2 confirmed via laboratory tests and presenting symptoms were included. The data collected covered socio-demographic details, infection onset dates, COVID-19 symptoms, pre-existing health conditions, radiological findings, treatments, disease progression, and relevant variables. A total of 47,875 files were included in the analysis. The median age was 43.7 years, with 84.5% testing positive for PCR SARS-CoV-2, often correlating with severe symptoms. Notably, 11.8% of the participants exhibited mild symptoms, and approximately 12.8% had comorbidities, increasing to 17.6% among severe cases. Females with PCR-positive COVID-19 had a comorbidity rate of 13.8%, compared to 12.5% in males. Among the patients with comorbidities, those aged 70 and above had the highest rates, at 22.1% (n = 1103). The most prevalent comorbidity was hypertension, followed by diabetes and cardiovascular diseases. Severe cases had a significantly higher prevalence of comorbidities (58.4%) compared to non-severe cases (27.6%). We hope that the evaluation of our findings will contribute to the research and treatment processes of the COVID-19 outpatients. Full article

This research aims to investigate the associations between comorbidities and clinical outcomes, specifically their impacts on mortality rates among COVID-19 inpatients, while also assessing the varying significance of different comorbidities. We conducted this study to understand the interplay between SARS-CoV-2 infection, socio-demographic factors, disease severity, and co-morbid conditions in a sample of 26,835 hospitalized COVID-19 cases. Our analysis extended to examining the frequency of infection symptoms, pre-existing health issues, treatment strategies, intensive care unit (ICU) and hospital stays, clinical symptoms, and radiological findings. Among the 26,883 cases analyzed, comprising 53.7% males and 53.3% females with an average age of 48.5 years, we observed mean clinical values for temperature, heart rate, respiratory rate, and blood pressure. Leveraging logistic regression modeling helped untangle the complex relationships and confounding variables influencing COVID-19 mortality. Notably, our findings underscored the significance of total length of stay, prolonged ICU stays exceeding ten days, and the presence of significant symptoms in affecting mortality rates among COVID-19 patients. These insights unveil potential trends crucial for informing future management strategies tailored to the needs of COVID-19 patients, emphasizing the importance of addressing comorbidities and optimizing care approaches for better outcomes. Full article