ArticleAntimicrobial resistance and infection control2025
Central venous catheter infections: building a causal model with expert domain knowledge to inform future clinical trials.
Article in Antimicrobial resistance and infection control, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The trial behind it
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Who cites it
2 citing papers in PubMed.
- Difelikefalin Treatment in Chronic Kidney Disease-Associated Pruritus: Modelling Infection-Related Hospitalisation Cost Offsets Using Trial and Real-World Data Across Seven European Countries.Advances in therapy · 2026Article
- Nutrition-modulated, subtype-specific risk factors for catheter-related bloodstream infections in hospitalized patients with intestinal failure.Frontiers in nutrition · 2025Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
aimCentral 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.
methodsWe 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.
findingsThe 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.
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