文章摘要
付红平,王小乔,杨英英,姜翠,田苗,吴燕.极低出生体重儿PICC继发性异位风险预测模型的构建[J]同济医院杂志社,2026,41(5):57-60
极低出生体重儿PICC继发性异位风险预测模型的构建
Development of a risk prediction model for secondary malposition of peripherally inserted central catheters in very low birth weight infants
投稿时间:2025-09-08  修订日期:2025-09-08
DOI:10.3870/j.issn.1001-4152.2026.05.057
中文关键词: 极低出生体重儿;经外周静脉置入中心静脉导管;继发性异位;静脉炎;风险预测;预测模型;列线图;儿科护理
英文关键词: very low birth weight infants;peripherally inserted central venous catheters;secondary malposition;phlebitis;risk prediction;prediction model;nomogram;pediatric care
基金项目:
付红平,王小乔,杨英英,姜翠,田苗,吴燕
武汉大学中南医院儿科(湖北 武汉,430071)
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中文摘要:
      目的 构建极低出生体重儿PICC继发性异位风险预测模型,为识别危险因素并实施早期针对性干预提供参考。 方法 选取新生儿重症监护室置入PICC的312例极低出生体重儿为研究对象,回顾性收集其基线资料及PICC专项资料。采用单因素分析和logistic回归分析确定危险因素,创建并绘制列线图。 结果 极低出生体重儿PICC继发性异位发生率为18.59%。导管异位的独立危险因素包括:无创通气时间(OR=1.022)、日均俯卧位通气时间(OR=1.182)、PICC相关性静脉炎(OR=2.509)及置管部位(OR=4.352);创建的风险预测模型曲线下面积为0.705(95%CI:0.628~0.782)。 结论 极低出生体重儿PICC继发性异位风险较高,构建的风险预测模型有一定的预测价值,可作为医护人员识别极低出生体重儿PICC继发性异位风险的工具。
英文摘要:
      Objective To develop a risk prediction model for secondary malposition of peripherally inserted central catheters (PICC) in very low birth weight (VLBW) infants, and to provide a reference for identifying risk factors and implementing early targeted interventions. Methods A total of 312 VLBW infants who had a PICC in the neonatal intensive care unit were recruited.Baseline data and PICC-specific data were retrospectively collected.Univariate and logistic regression analysis were performed to identify risk factors, then a nomogram was generated. Results The incidence of secondary malposition of PICC in VLBW infants was 18.59%.Risk factors for catheter malposition included:duration of non-invasive ventilation (OR=1.022), average daily duration of prone position ventilation (OR=1.182), PICC-related phlebitis (OR=2.509), and insertion site (OR=4.352).The area under the Receiver Operating Characteristic curve of the developed risk prediction model was 0.705 (95%CI:0.628-0.782). Conclusion VLBW infants have a relatively high risk of secondary malposition of PICC.The nomogram risk prediction model demonstrates certain predictive value and can serve as a tool for healthcare professionals to identify infants at high-risk.
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