A predictive model for catheter-related bloodstream infection in neonates with peripherally inserted central catheter

The nomogram prediction model constructed based on the screened independent risk factors can effectively predict the risk of CRBSI in neonates with PICC in the NICU, providing a basis for the clinical early identification of high-risk neonates and the formulation of preventive measures.

Authors

Institutions

Publication Details

Journal
Frontiers in Medicine
Published
2025-10-21
DOI
https://doi.org/10.3389/fmed.2025.1665068
Citations
1
Primary Topic
Central Venous Catheters and Hemodialysis
Type
article
Field-Weighted Citation Impact
2.52
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A predictive model for catheter-related bloodstream infection in neonates with peripherally inserted central catheter

Congying Xie, Hang Zhong, Hong-yun Ye, Fan-ying Zeng et al.
1 citations
Frontiers in Medicine
Central Venous Catheters and Hemodialysis
2.52
article

A predictive model for catheter-related bloodstream infection in neonates with peripherally inserted central catheter

Congying Xie, Hang Zhong, Hong-yun Ye, Fan-ying Zeng, Wenyan Li
article en
1 citations

Abstract

The nomogram prediction model constructed based on the screened independent risk factors can effectively predict the risk of CRBSI in neonates with PICC in the NICU, providing a basis for the clinical early identification of high-risk neonates and the formulation of preventive measures.

Frontiers in MedicineVol. 12
Ganzhou People's Hospital (CN)
Openalex Percentile: Top 9%
Central Venous Catheters and Hemodialysis
2.52
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.