Post-COVID Myocarditis and Return-to-Play Recommendations in Young Competitive Athletes: A Prospective Screening Cohort with Six-Month Follow-up across Three Severity Tiers

Dr. Shubhendu Gupta, Mrs. Sudha Gautam, Dr. Supriya Maitiy

COVID-19; Myocarditis; Sports Cardiology; Return-To-Play; Cardiac MRI; Athlete Screening; Troponin.

Early in the COVID-19 pandemic, concern about post-infectious myocarditis prompted broad pre-participation screening of competitive athletes, with cardiac MRI used liberally across many programmes. Subsequent evidence has refined the clinical approach, with most current frameworks reserving advanced imaging for symptomatic or severely-affected athletes. We prospectively followed 215 competitive athletes (mean age 21.4 years; 138 male) after laboratory-confirmed COVID-19 infection, stratifying by symptom severity into mild (n=142), moderate (n=47), and severe (n=26) tiers. Resting ECG abnormalities were uncommon in the mild tier (2.1%) and progressively more frequent with severity (8.5% moderate; 23.1% severe). Cardiac MRI findings consistent with myocarditis were rare in mild illness (0.7%) but reached 14.9% in severely affected athletes. Median time to full return-to-play was 7 days in the mild tier, 16 days in the moderate tier, and 54 days in the severe tier. At six months, 184 athletes (85.6%) had returned to unrestricted training, 18 with modified intensity ramps, 9 remained under surveillance or restriction, and 4 withdrew from competition. A stratified triage approach with cardiac MRI reserved for the moderate-to-severe tiers appears safe and avoids the considerable downstream burden of universal imaging.

[1] Bhatnagar, M., Kumar, N., & Shivam. (2026). Quality improvement frameworks in modern surgical practice: Evidence-based models, implementation science, and outcome-oriented performance evaluation. International Journal of Scientific Research and Engineering Development, 9(2).
[2] Bhatnagar, V., Tyagi, N., & John, L. (2026). Simulation-based competency development in anesthesia training: educational theory, assessment validity, and clinical impact. International Journal of Versatile Research and Analysis, 4(2).
[3] Catherine, S., Gupta, N., Gopi, E., & Swadhi, R. (2025). Enhancing patient engagement and outcomes through digital transformation: Machine learning in medical marketing. In Impact of digital transformation on business growth and performance (pp. 285–312). IGI Global.
[4] Devi, M., Manokaran, D., Sehgal, R. K., Shariff, S. A., & Vettriselvan, R. (2025). Precision medicine, personalized treatment, and network-driven innovations: Transforming healthcare with AI. In AI for large scale communication networks (pp. 303–322). IGI Global.
[5] Gautam, M., Samyal, M., & Chaudhary, S. (2026). Preoperative risk stratification and surgical outcome prediction: Integrating clinical scoring systems, data-driven models, and patient-centered optimization. International Innovations & Scholarly Trends Journal, 2(3).
[6] Jha, S. C., Kumar, P., & Neha. (2026). Artificial intelligence-assisted decision support in internal medicine: Enhancing clinical judgment, precision care, and health system performance. International Journal of Scientific Development and Research, 11(2).
[7] Kumar, P., Gautam, S., & Maitiy, S. (2026). Diagnostic utility of biomarkers in early disease stratification: Clinical applications, predictive value, and emerging innovations. Journal of Emerging Technologies and Innovative Research, 13(2).
[8] Pradeepa, S. V., Gokilavani, R., Deepan, A., Sridevi, J., & Selvi, K. (2026). Predictive maintenance and asset management using motion analytics. In Methodologies and applications of intelligent motion control systems (pp. 75–104). IGI Global.
[9] Rasi, R. A., & Ashifa, K. M. (2019). Role of community-based programmes for active ageing: Elders self-help group in Kerala. Indian Journal of Public Health Research & Development, 10(12).
[10] Sahu, R. L., Sharma, K., & Gupta, S. K. (2026). Biological and mechanical determinants of fracture healing: An integrated mechano-biological, systemic, and translational framework. International Journal of Recent Development in Engineering and Technology, 15(3).
[11] Sehgal, A., Jayapriya, R., & Kumar, A. (2026). Evidence-based rehabilitation in sports-related injuries: Clinical effectiveness, multidisciplinary integration, and technological advancements. International Journal of Recent Development in Engineering and Technology, 15(3).
[12] Selvi, K., Anbarasan, P., Madhumita, G., Janaki, L., & Devi, K. K. (2026). Governance, security, and ethical considerations in AI-driven motion control systems. In Methodologies and applications of intelligent motion control systems (pp. 217–242). IGI Global.
[13] Sharma, S., Sharma, K., & Tyagi, N. (2026). Geriatric psychiatry and cognitive decline: Clinical evaluation, neuropsychological determinants and evidence-based management. International Journal of Management Research and Social Science, 13(2).
[14] Subramani, M., Chillagattu, V., Gayathri, K., Rastogi, V., & Ranganathan, S. (2026). Digital twin integration for predictive and real-time motion control in infrastructure engineering. In Methodologies and applications of intelligent motion control systems (pp. 189–216). IGI Global.
[15] Vettriselvan, R., Ramya, R., Selvalakshmi, V., Jyothi, P., & Velmurugan, P. R. (2026). Empowering patients through knowledge: Educational strategies in rehabilitation. In Holistic approaches to health recovery (pp. 263–290). IGI Global.
[16] Vettriselvan, R., Velmurugan, P. R., Varshney, K. R., EP, J., & Deepika, R. (2025). Health impacts of smartphone and internet addictions across age groups: Physical and mental health across generations. In Impacts of digital technologies across generations (pp. 187–210). IGI Global.
[17] Vijayalakshmi, M., Subramani, A. K., Vettriselvan, R., Velmurugan, P. R., & Hasine, J. (2025). Strategic collaborations in medical innovation and AI-driven globalization: Advancing healthcare startups. In Navigating strategic partnerships for sustainable startup growth (pp. 85–110). IGI Global.
[18] Vinodh, N., & Subramani, A. K. (2026). Augmented and virtual reality for training and operations in motion-control environments. In Intelligent motion control for human-centered systems (pp. 153–178). IGI Global.
[19] Vinodh, N., Subramani, A. K., & Vettriselvan, R. (2026). Transforming the future of management and medical education: AI-driven innovations in curriculum design. In AI education strategies for future-proofing curriculum design (pp. 459–476). IGI Global.
[20] Yatish, Khatoon, N., & Kumar, A. (2026). Advancing preventive strategies for chronic disease management: Clinical, behavioral, and population-level perspectives. International Journal of Novel Trends and Innovation, 4(2).