# Development and validation of a nomogram for predicting unplanned PICC removal in preterm infants with gestational age <32 weeks

## TL;DR

This study creates a tool to predict unplanned removal of PICC lines in preterm infants, using factors like blood cell counts and insertion site to improve NICU care.

## Contribution

A novel nomogram is developed and validated for predicting unplanned PICC removal in preterm infants under 32 weeks gestational age.

## Key findings

- Five independent predictors for PICC-UR were identified: insertion site, WBC, PLT, Fib, and HCA.
- The nomogram demonstrated high accuracy with a C-index of 0.827 (95% CI: 0.740–0.915).
- Internal validation confirmed excellent calibration and clinical utility via decision curve analysis.

## Abstract

To develop and validate a risk prediction model for unplanned removal (UR) of peripherally inserted central catheters (PICC) in preterm infants with gestational age (GA) < 32 Weeks.

This retrospective study analyzed preterm infants with PICC admitted to a neonatal intensive care unit (NICU) (January 2018 to December 2024). Clinical and catheter-related variables were assessed. Multivariable logistic regression identified predictors of PICC-UR, with model performance evaluated by C-index, calibration, and decision curve analysis (internal validation via 1000 bootstraps).

We identified five independent predictors for PICC-UR: insertion site (categorical), white blood cell count (WBC), platelet count (PLT), and fibrinogen (Fib) (all modeled as continuous linear terms), along with hypercholanemia (HCA). These predictors were integrated into a nomogram designed to estimate the individual risk of PICC-UR in preterm infants. The predictive model demonstrated a high accuracy with a C-index of 0.827 [95% confidence interval (CI): 0.740–0.915]. Internal validation confirmed excellent calibration and significant clinical utility based on decision curve analysis.

This validated nomogram, incorporating insertion site, WBC, PLT, Fib and HCA, aids early identification of high-risk infants. It offers actionable insights for optimizing PICC fixation and biochemical monitoring, potentially reducing PICC-UR in NICU.