AUTHOR=Zhang Wenlan , Lu Hua , Tang Xiaoliao , Xia Suqin , Zhang Jian , Sun Jiwen , Shen Nanping , Ren Hong 

TITLE=Risk factors analysis and research on the construction of early prediction model of difficult weaning in children with mechanical ventilation

JOURNAL=Frontiers in Pediatrics

VOLUME=Volume 13 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/pediatrics/articles/10.3389/fped.2025.1630580

DOI=10.3389/fped.2025.1630580

ISSN=2296-2360

ABSTRACT=ObjectiveTo identify risk factors for difficult weaning in mechanically ventilated children and develop an early predictive nomogram.MethodsA prospective observational study was cunducted between Aug/2023 and Nov/2024 involving 205 pediatric patients from two PICUs. General demographic and clinical data were collected, along with lung ultrasound (LUS) scores obtained within 48–72 h of initiating mechanical ventilation. Additional respiratory and oxygenation function-related parameters were also synchronously recorded. All pediatric patients were followed up to their weaning outcomes, duration of mechanical ventilation, and ICU stay days.Weaning outcomes were defined as the dependent variable, while the collected clinical indicators were treated as independent variables for univariate analysis. Multivariable logistic regression analysis was performed to identify significant predictors, and a nomogram was developed and validated using ROC and K-S curves.ResultsThis study included 205 mechanically ventilated pediatric patients with complete data, and the incidence of difficult weaning was 47.8%. Two independent risk factors were identified: lung ultrasound (LUS) score (OR = 2.316, 95% CI: 1.668–3.216, P < 0.001) and pediatric critical illness score (PCIS) (OR = 0.748, 95% CI: 0.639–0.875, P = 0.001). The nomogram demonstrated good discriminatory ability, with an AUC of 0.874 in the modeling cohort and 0.854 in the validation cohort.ConclusionLUS scores and PCIS are significant early predictors of difficult weaning in mechanically ventilated pediatric patients. The validated nomogram offers a reliable tool for quantitative risk stratification, which can support the development of personalized ventilation liberation strategies.