Monitoring human adenovirus loads in bronchoalveolar lavage fluid in non-immunocompromised children with human adenovirus pneumonia.

Abstract

Background: Human adenoviruses (HAdVs) are prevalent pathogens responsible for respiratory infections. In this study, we examined the relationship between adenovirus viral loads in bronchoalveolar lavage fluid (BALF) and the severity of adenovirus pneumonia in children.

Methods: The medical records of patients admitted to Guangzhou Women and Children's Medical Center with confirmed adenovirus pneumonia were analyzed in a prospective manner. We evaluated the potential link between the severity of the disease and the viral load, which was measured using real-time polymerase chain reaction (PCR) on the BALF of pediatric patients. Furthermore, the study investigated the connection between viral loads in BALF and the progression of the illness.

Results: In hospitalized pediatric patients with adenovirus pneumonia, the viral loads found in BALF were positively associated with the severity of the disease during the acute phase (P<0.05). In addition, lactate dehydrogenase (LDH) and C-reactive protein (CRP) levels were positively associated with viral loads in BALF, whereas albumin (ALB) levels showed a negative relationship (P<0.05). In addition, In addition, The receiver operating characteristic (ROC) analysis indicated that viral loads in BALF displayed great potential for predicting severe adenovirus pneumonia, with a cut-off value of >187,500 copies/mL, which achieved a sensitivity of approximately 77.27% and a specificity of 80.65%.Moreover, viral loads in BALF from patients at the acute stage of the disease were positively correlated with fever duration and length of stay (LOS) at the hospital, and viral loads declined quickly during the recovery stage (P<0.05).

Conclusions: Our findings indicated a significant correlation between viral loads in BALF from patients with adenovirus pneumonia and the severity of the disease. We suggested that viral loads can serve as potential biomarkers for identifying severe cases and predicting the progression of illness.