Ndagijimana Frank Aimee Rodrigue, Park Taesung
Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea.
Department of Statistics, Seoul National University, Seoul, Republic of Korea.
Genomics Inform. 2025 Jan 27;23(1):2. doi: 10.1186/s44342-024-00035-y.
Understanding the progression and recovery process of COVID-19 is crucial for guiding public health strategies and developing targeted interventions. This longitudinal cohort study aims to elucidate the dynamics of COVID-19 severity progression and evaluate the impact of underlying health conditions on these transitions, providing critical insights for more effective disease management.
Data from 4549 COVID-19 patients admitted to Seoul National University Boramae Medical Center between February 5th, 2020, and October 30th, 2021, were analyzed using a 5-state continuous-time Markov multistate model. The model estimated instantaneous transition rates between different levels of COVID-19 severity, predicted probabilities of state transitions, and determined hazard ratios associated with underlying comorbidities.
The analysis revealed that most patients stabilized in their initial state, with 72.2% of patients with moderate symptoms remaining moderate. Patients with hypertension had a 67.6% higher risk of progressing from moderate to severe, while those with diabetes had an 89.9% higher risk of deteriorating from severe to critical. Although transition rates to death were low early in hospitalization, these comorbidities significantly increased the likelihood of worsening conditions.
This study highlights the utility of continuous-time Markov multistate models in assessing COVID-19 severity progression among hospitalized patients. The findings indicate that patients are more likely to recover than to experience worsening conditions. However, hypertension and diabetes significantly increase the risk of severe outcomes, underscoring the importance of managing these conditions in COVID-19 patients.
了解新型冠状病毒肺炎（COVID-19）的进展和恢复过程对于指导公共卫生策略和制定针对性干预措施至关重要。这项纵向队列研究旨在阐明COVID-19严重程度进展的动态变化，并评估基础健康状况对这些转变的影响，为更有效的疾病管理提供关键见解。
使用五状态连续时间马尔可夫多状态模型分析了2020年2月5日至2021年10月30日期间入住首尔国立大学博拉梅医疗中心的4549例COVID-19患者的数据。该模型估计了COVID-19不同严重程度水平之间的瞬时转变率，预测了状态转变的概率，并确定了与基础合并症相关的风险比。
分析显示，大多数患者在初始状态稳定下来，72.2%有中度症状的患者保持中度症状。高血压患者从中度进展为重度的风险高67.6%，而糖尿病患者从重度恶化为危重症的风险高89.9%。虽然住院早期死亡的转变率较低，但这些合并症显著增加了病情恶化的可能性。
本研究强调了连续时间马尔可夫多状态模型在评估住院患者COVID-19严重程度进展中的作用。研究结果表明，患者康复的可能性大于病情恶化的可能性。然而，高血压和糖尿病显著增加了严重后果的风险，突出了在COVID-19患者中管理这些疾病的重要性。
