ANALYZING EARLY CLINICAL AND CHEST CT PREDICTORS OF COVID-19 PROGNOSIS IN ATHLETES AND YOUNG ADULTS UNDER 55

Abstract

Purpose: This study aims to explore the prognosis of COVID-19 in athletes and physically active young adults under 55 years, utilizing initial patient characteristics, laboratory tests, imaging examinations, and treatment methods. Our goal is to establish a basis for predicting disease severity and facilitating targeted interventions for this low-risk population. Materials and Methods: We conducted a retrospective analysis of 137 COVID-19 confirmed patients aged ≤55 years, without underlying diseases, who visited the Sixth People's Hospital affiliated with Shanghai Jiao Tong University School of Medicine between December 16, 2022, and January 4, 2023. Patients were categorized based on disease progression into non-absorption and absorption groups. We compared the basic demographics, clinical symptoms, initial blood test results, chest CT findings, and treatment approaches between the two groups. Results: Of the participants, approximately 30.8% were active individuals, with a median age significantly younger in the non-absorption group. The non-absorption group sought medical help later and exhibited more severe symptoms like palpitations and shortness of breath, which are critical for athletic performance. Laboratory findings and chest CT scans showed distinct patterns; the non-absorption group exhibited more severe markers such as ground-glass opacities and pleural thickening, which could indicate prolonged recovery times affecting athletic training and performance. Conclusion: Early clinical signs, laboratory results, and chest CT imaging, particularly the presence of crazy-paving patterns, pleural thickening, and the distribution of lesions, are vital for predicting COVID-19 prognosis in athletes and young adults. These findings can help in developing targeted strategies to ensure faster recovery and minimal impact on athletic performance, thus aiding in better management of physically active populations during the pandemic.