Frontiers in pediatrics · 2026
Development and validation of a nomogram for predicting unplanned PICC removal in preterm infants with gestational age <32 weeks.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Hu Yuedi, Lang Yu, Shen Leilei, Yan Ling
Аннотация
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.
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.