LAUSR

Objective To explore the impact of the COVID-19 on the distribution, type and patterns of diseases in hospitalised children under local antiepidemic measures. Design Retrospective chart review. Setting Electronic medical records of patients hospitalised in the paediatric department of a tertiary hospital in South China from 21 January 2019 to 20 January 2021. Participants Records of 2139 patients. Outcome measures Data were analysed before and during the COVID-19 pandemic. Disease characteristics were analysed based on the 10th revision of the International Statistical Classification of Diseases and Related Health Problems. Features of the length of hospital stay were investigated. Categorical variables involving more than three groups were analysed using an overall χ2 test, followed by pairwise comparisons. Results During the COVID-19 outbreak period, paediatric hospitalisation was reduced by 29.6%, from 1255 to 884. The proportions of infection-related diseases (36.3% (455 cases) vs 20.8% (184 cases)), respiratory system-related diseases (22.5% (283 cases) vs 9.4% (83 cases)); and endocrine, nutritional and metabolic diseases (17.1% (214 cases) vs 9.2% (81 cases)) decreased significantly, whereas that of musculoskeletal and connective tissue diseases increased from 11.0% (138 cases) to 20.1% (178 cases), thereby becoming the most common reason for hospitalisation. The proportions of diseases of the nervous system (12.4% (156 cases) to 18.8% (166 cases)) and mental and behavioural disorders (0.2% (3 cases) to 2.1% (19 cases)) increased significantly. The average length of hospital stay increased after the outbreak (7.57±6.53 vs 8.36±6.87). Conclusion The number of hospitalisation cases decreased during the COVID-19 period. The prominent decreases in hospitalisation associated with infections and respiratory system diseases were likely attributed to the improved epidemic prevention work, enhancement of people’s health awareness and fear of possible exposure to COVID-19. Describing the impact of COVID-19 on disease patterns may provide a reference for resource planning during the pandemic.