International Journal of Molecular Medical Science, 2025, Vol.15, No.2, 54-68 http://medscipublisher.com/index.php/ijmms 54 Research Report Open Access The Predictive Model For The Risk of Venous Thromboembolism In Children: A Systematic Review of and Meta-Analysis Bochen Wang, Zixuan Liu, Yang Li , Xinqi Shi School of Nursing, Peking Union Medical College, Beijing, 100144, Beijing, China Corresponding author: liyang3413@sina.com International Journal of Molecular Medical Science, 2025, Vol.15, No.2 doi: 10.5376/ijmms.2025.15.0006 Received: 28 Nov., 2024 Accepted: 19 Feb., 2025 Published: 02 Mar., 2025 Copyright © 2025 Wang et al., This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Wang B.C., Liu Z.X., Li Y., and Shi X.Q., 2025, The predictive model for the risk of venous thromboembolism in children: a systematic review of and meta-analysis, International Journal of Molecular Medical Science, 15(2): 54-68 (doi: 10.5376/ijmms.2025.15.0006) Abstract Through systematic review and meta-analysis, this study systematically evaluated the predictive efficacy and heterogeneity of the risk prediction model for venous thromboembolism (VTE) in children, providing evidence-based evidence for the optimization and application of the clinical model. A search of the Chinese and English databases (as of April 16, 2024) included 13 studies. The results showed that the current model was dominated by Logistic regression, central venous catheter (CVC) was the most commonly used predictor (inclusion rate 61.5%), and the combined AUC was 0.84 (95% CI: 0.80-0.88). However, heterogeneity in the included models was significant (I²=96%), especially when the predictors exceeded 5, mainly due to differences in variable selection (e.g., regional differences in medical practice, unadjusted for age stratification effects). Seven studies had a high risk of bias, which was mainly reflected in the opacity of missing data processing and the absence of blind predictors and outcome variables. In this study, a "core + extended" model architecture was proposed for the first time: age-specific thresholds for biomarkers (e.g., D-dimer, CRP) were vertically integrated, and cross-regional core variable sets (≤5 items, e.g., CVC, age, surgery) were constructed horizontally to balance prediction accuracy with clinical universality. In the future, the application value of dynamic biomarkers and machine learning algorithms in children's VTE stratification should be verified by multi-center cohort. Keywords Children; Venous thromboembolism; Prediction model; Systematic evaluation; meta-Analysis 1 Background Venous thromboembolism (VTE) refers to the formation of blood clots, and thrombi or a part of a thrombus detaches and causes embolism in the veins, resulting in partial or complete blockage of the blood vessels. The blockage leads to impaired venous return, which includes deep vein thrombosis and pulmonary embolism (Tan and Zhi, 2023). According to a study conducted by the American Academy of Pediatrics, the hospitalization rate of pediatric VTE has increased by 130% from 2008 to 2019 (from 46 per 10 000 cases to 106 per 10 000 cases) (O’Brien et al., 2022). There are no typical clinical features of VTE on children in the early stage. Delay in diagnosis and treatment poses a great health risk to children, increasing the chance of pulmonary embolism, which could lead to higher mortality rate, increased risk of VTE recurrence and the development of post-thrombotic syndrome (White et al., 2021). Most of the current risk prediction models for venous thromboembolism are used in adults. However, according to the American College of Chest Physicians’ “Antithrombotic Therapy and Prevention of Thrombosis in Neonates and Children Guidelines” published in February 2012, it is known that pediatric patients (defined as ≤21 years old according to the seventh edition of Pediatrics Nursing) differ from adult patients in epidemiology, pharmacokinetics, coagulation system, and comorbidities, resulting in lower applicability of adult VTE risk prediction models to children (Monagle et al., 2012; Cui and Zhang, 2021). At present, risk assessment for adult patients is more mature. The application of adult VTE risk prediction models is also considered to significantly reduce the incidence of VTE in adults (Biss, 2016). However, for children, there is a lack of reliable methods for preventing VTE. Currently, the occurrence of VTE in children largely depends on pediatricians' high suspicion, and there is a lack of practical risk assessment tools in clinical practice (Yang and Hao, 2020; Walker et al., 2023).
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