Clinical Characteristics and Co-infection Profile of COVID-19 Patients with Different Severity Levels: A tNGS-Based Study in Post-Outbreak China

The 2019 coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has resulted in significant global morbidity and mortality. The World Health Organization declared it a pandemic in March 2020 due to its rapid spread and impact [1]. COVID-19 presents with a diverse spectrum of clinical manifestations, ranging from asymptomatic or pre-symptomatic stages to mild respiratory symptoms, severe pneumonia, acute respiratory distress syndrome, multi-organ dysfunction, and even death.

Early identification of patients at high risk of severe COVID-19 and a thorough understanding of the incidence and characteristics of co-infections in these patients are critical for effective clinical management. These factors are crucial for timely recognition of critical illness, accurate prognosis assessment, and the administration of appropriate and timely treatment.

Established risk factors for severe COVID-19 in adults include advanced age, male sex, certain racial backgrounds, and the presence of underlying comorbidities such as cardiovascular disease and chronic obstructive pulmonary disease (COPD) [2]. Furthermore, since 2020, numerous studies have identified several biomarkers as potential predictors of adverse clinical outcomes in COVID-19 patients [3]. These laboratory indicators include, but are not limited to:

• Lymphocyte and platelet counts* Creatinine* Interleukin-6 (IL-6)* Procalcitonin (PCT)* D-dimer* Ferritin* Lactate dehydrogenase (LDH)* C-reactive protein (CRP)* Aspartate aminotransferase (AST)* Alanine aminotransferase (ALT)* High-sensitivity troponin T (hsTnT)* Albumin* Creatine kinase (CK)

In addition to these factors, the incidence and characteristics of bacterial, fungal, and viral co-infections in COVID-19 patients have emerged as a significant area of research interest [4]. These co-infections can complicate the clinical course of COVID-19 and pose unique challenges in diagnosis and treatment.

However, there remains a paucity of research investigating the clinical characteristics and co-infection profiles of hospitalized COVID-19 patients across different severity levels. This knowledge gap is partly attributable to the limitations of traditional microbial detection methods, such as prolonged turnaround times for results and suboptimal sensitivity, which hinder comprehensive understanding of co-infection patterns in this patient population.

This study aims to address this critical gap in knowledge by investigating the demographic characteristics, laboratory indicator differences, and co-infection profiles of COVID-19 patients with varying severity levels in the post-outbreak period in China. To overcome the limitations of conventional diagnostic approaches, this study will employ targeted next-generation sequencing (tNGS), a cutting-edge technology known for its high sensitivity and broad pathogen detection capabilities. This comprehensive approach will provide valuable insights into the clinical heterogeneity of COVID-19 and contribute to the development of more effective, personalized management strategies for this complex and evolving disease.