Author:
Tran Dien. M.,Pham Dem. V.,Cao Tung. V.,Hoang Canh. N.,Nguyen Ha. T. T.,Nguyen Giang. D.,Le Cuong. N.,Thieu Quan. Q.,Ta Tuan. A.,Dau Hung. V.,Le Chi. Q.,Le Quang. H.,Luong Nghiem. T.,Tran Mai. T.,Nguyen Phu. H.,Nguyen Nhung. T.,Phan Phuc. H.
Abstract
AbstractMultisystemic 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 $$\ge $$
≥
50 (mg/L) (OR 2.52, 95% CI 1.39–4.56, p = 0.002), albumin $$\le $$
≤
30 (g/L) (OR 3.18, 95% CI 1.63–6.02, p = 0.001), absolute lymphocyte count $$\le $$
≤
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 $$\le $$
≤
2 (× 109/L) (OR 2.48, 95% CI 1.10–5.61, p = 0.029), albumin $$\le $$
≤
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.
Funder
Vietnam National University, Hanoi
Publisher
Springer Science and Business Media LLC