%0 Journal Article
%T Severity predictors for multisystemic inflammatory syndrome in children after SARS-CoV-2 infection in Vietnam.
%A Tran DM
%A Pham DV
%A Cao TV
%A Hoang CN
%A Nguyen HTT
%A Nguyen GD
%A Le CN
%A Thieu QQ
%A Ta TA
%A Dau HV
%A Le CQ
%A Le QH
%A Luong NT
%A Tran MT
%A Nguyen PH
%A Nguyen NT
%A Phan PH
%J Sci Rep
%V 14
%N 1
%D 2024 07 9
%M 38982132
%F 4.996
%R 10.1038/s41598-024-66891-4
%X Multisystemic inflammatory syndrome in children (MIS-C) might manifest in a broad spectrum of clinical scenarios, ranging from mild features to multi-organ dysfunction and mortality. However, this novel entity has a heterogenicity of data regarding prognostic factors associated with severe outcomes. The present study aimed to identify independent predictors for severity by using multivariate regression models. A total of 391 patients (255 boys and 136 girls) were admitted to Vietnam National Children's Hospital from January 2022 to June 2023. The median age was 85 (range: 2-188) months, and only 12 (3.1%) patients had comorbidities. 161 (41.2%) patients required PICU admission, and the median PICU LOS was 4 (2-7) days. We observed independent factors related to PICU admission, including CRP ≥ 50 (mg/L) (OR 2.52, 95% CI 1.39-4.56, p = 0.002), albumin ≤ 30 (g/L) (OR 3.18, 95% CI 1.63-6.02, p = 0.001), absolute lymphocyte count ≤ 2 (× 109/L) (OR 2.18, 95% CI 1.29-3.71, p = 0.004), ferritin ≥ 300 (ng/mL) (OR 2.35, 95% CI 1.38-4.01), p = 0.002), and LVEF < 60 (%) (OR 2.48, 95% CI 1.28-4.78, p = 0.007). Shock developed in 140 (35.8%) patients, especially for those decreased absolute lymphocyte ≤ 2 (× 109/L) (OR 2.48, 95% CI 1.10-5.61, p = 0.029), albumin ≤ 30 (g/L) (OR 2.53, 95% CI 1.22-5.24, p = 0.013), or LVEF < 60 (%) (OR 2.24, 95% CI 1.12-4.51, p = 0.022). In conclusion, our study emphasized that absolute lymphocyte count, serum albumin, CRP, and LVEF were independent predictors for MIS-C severity. Further well-designed investigations are required to validate their efficacy in predicting MIS-C severe cases, especially compared to other parameters. As MIS-C is a new entity and severe courses may progress aggressively, identifying high-risk patients optimizes clinicians' follow-up and management to improve disease outcomes.