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ORIGINAL RESEARCH article

Front. Pediatr.

Sec. Neonatology

Development and Validation of a Nomogram for Predicting Unplanned PICC Removal in Preterm Infants with gestational age < 32 Weeks

Provisionally accepted
Yuedi  HuYuedi HuYu  LangYu LangLeilei  ShenLeilei Shen*Ling  YanLing Yan
  • The Southwest Hospital of AMU, Chongqing, China

The final, formatted version of the article will be published soon.

Objective: 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. Methods: 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). Results: 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. Conclusions: 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.

Keywords: peripherally inserted central catheters, Prediction nomogram, preterm infants, risk prediction, unplanned removal

Received: 15 Oct 2025; Accepted: 28 Jan 2026.

Copyright: © 2026 Hu, Lang, Shen and Yan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Leilei Shen

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