Abstract
Aim
Central venous catheters (CVCs) are essential for long-term therapies but carry a high risk of central line-associated bloodstream infections (CLABSIs), which significantly impact patient outcomes and healthcare costs. This study aimed to develop a causal model for CLABSI using expert knowledge to guide future clinical trials and prevention strategies.
Methods
We constructed a directed acyclic graph (DAG) informed by literature and expert knowledge elicitation. A multidisciplinary team of clinicians, including infectious disease and vascular access experts, participated in interviews and workshops to refine the DAG, resulting in a final model with 30 variables representing CLABSI development.
Findings
The expert-elicited DAG identified two main pathways, patient-related and CVC-related, each contributing to CLABSI risk. Variables and relationships in the DAG highlighted key patient characteristics, CVC management practices, and overlapping factors influencing infection. This model serves as a novel framework to understand CLABSI causation and supports trial design by identifying confounding factors, causal pathways, and meaningful endpoints.
Conclusions/implications
Our causal DAG provides a structured representation of CLABSI risk factors, which may support the design of clinical trials examining interventions to reduce CVC-related infections. By clarifying causal mechanisms, the DAG can enhance the specificity of endpoints and improve the rigor of prevention strategies.
License
This is an open access article distributed under the Creative Commons Attribution-NonCommercial 4.0 International License which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.
Citation
@article{Schults2025CVC,
title = {Central venous catheter infections: building a causal model with expert domain knowledge to inform future clinical trials},
author = {Jessica A. Schults and Yue Wu and Thomas Snelling and Gladymar Pérez Chacón and Daner Ball and Karina Charles and Julie Marsh and Charlie McLeod and Hideto Yasuda and Claire M. Rickard},
journal = {Antimicrobial Resistance & Infection Control},
volume = {14},
number = {116},
year = {2025},
doi = {10.1186/s13756-025-01630-6},
url = {https://aricjournal.biomedcentral.com/articles/10.1186/s13756-025-01630-6}
}