Conectar
To develop and validate a tool to estimate the risk of central venous catheter-related thrombosis (CRT) in children with congenital heart disease.
Children with congenital heart disease face an elevated risk of CRT, which is closely linked to adverse clinical outcomes. Early detection of CRT may improve prognosis and reduce mortality. However, no specific tools currently exist to effectively assess it.
A cross-sectional study.
From January 2020 to April 2023, we enrolled 503 children with congenital heart disease. Four hundred and three were assigned to the modelling cohort and 100 to the validation cohort. Using binary logistic regression, a predictive model was constructed, followed by the development of a dynamic online nomogram. The model's internal and external verification were performed using ROC analysis, the Hosmer–Lemeshow test, and decision curve analysis, respectively. The study adhered to the TRIPOD guidelines.
The prevalence of CRT in the modelling cohort and validation cohort was 23.57% and 21.00%, respectively. Logistic regression analysis identified duration of catheterization, length of ICU stay, duration of sedation, fibrinogen ≥ 4 g/L and platelet count ≥ 400 × 109/L as independent predictive factors for CRT, all of which were incorporated into the nomogram. The nomogram achieved an AUC of 0.866 in the modelling cohort and 0.761 in the validation cohort, demonstrating strong discriminatory power. In both cohorts, the calibration curve indicated good agreement and decision curve analysis confirmed its significant clinical utility.
We developed a dynamic online nomogram that demonstrated strong predictive accuracy and was practical for identifying CRT in children with congenital heart disease.
This nomogram enables healthcare providers to estimate the risk of CRT in children with congenital heart disease, offering an effective tool for risk stratification and a basis for implementing targeted interventions.
No patient or public contribution.
FreshRSS 