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Development of a risk prediction model for central venous catheter insertion-related thrombosis in critically ill
Xiaolan Zhou1, Yunrong Li1, Shoushan Chen1
1Pediatric Intensive Care Unit, The First People's Hospital of Zunyi (The Third Affiliated Hospital of Zunyi Medical University), Zunyi, Guizhou, China.
Insights
Central venous catheter-related thrombosis (CVC-RT) affects critically ill children. Age, parenteral nutrition, D-dimer, and fibrinogen are key risk factors, informing a new predictive model for CVC-RT.
Area of Science:
- Pediatric critical care medicine
- Vascular access complications
- Thrombosis research
Background:
- Central venous catheter-related thrombosis (CVC-RT) is a significant complication in critically ill children, impacting their prognosis.
- Identifying risk factors is crucial for preventing and managing CVC-RT.
Purpose of the Study:
- To identify independent risk factors for CVC-RT in critically ill children.
- To develop and validate a predictive model for CVC-RT.
Main Methods:
- A cohort of 188 critically ill children with central venous catheters (CVCs) was studied.
- Clinical data were analyzed to determine risk factors for CVC-RT.
- A nomogram prediction model was constructed and validated.
Main Results:
- The incidence of CVC-RT was 16.5% (31 out of 188 children).
- Independent predictors of CVC-RT included age, parenteral nutrition, D-dimer levels, and fibrinogen (FIB) levels.
- The nomogram model showed strong predictive performance (AUC = 0.952).
Conclusions:
- Age, parenteral nutrition, D-dimer, and FIB levels are significant risk factors for CVC-RT in critically ill children.
- The developed nomogram model offers a valuable tool for predicting CVC-RT risk.
Introduction:
Central venous catheter-related thrombosis (CVC-RT) is a serious complication associated with CVC insertion that significantly adversely affects the prognosis of critically ill children. This study aimed to identify risk factors for CVC-RT following CVC placement in critically ill children and to develop a corresponding risk prediction model.
Methods:
A total of 188 critically ill children with CVCs were enrolled and categorized into thrombosis and non-thrombosis groups. Clinical data were collected to analyze risk factors for CVC-RT, and a nomogram prediction model was developed and validated for its predictive performance.
Results:
Among the 188 children, 31 developed CVC-RT, yielding an incidence rate of 16.5%. Significant differences were observed between the two groups in terms of age, catheter type, parenteral nutrition status, D-dimer levels, and fibrinogen (FIB) levels. All of these factors, except catheter type, were identified as independent predictors of CVC-RT. The constructed nomogram prediction model demonstrated strong predictive performance and discriminative ability, with an area under the receiver operating characteristic curve of 0.952.
Discussion:
In summary, this study identified age, parenteral nutrition, D-dimer, and FIB levels as independent influencing factors for CVC-RT in critically ill children. The nomogram model incorporating these factors exhibited favorable predictive value.
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