Nomogram for Predicting the Risk of Complications in Hospitalized Children With Peripheral Intravenous Catheters.

IF 1.7 3区 医学 Q3 HEALTH CARE SCIENCES & SERVICES
Journal of Patient Safety Pub Date : 2024-03-01 Epub Date: 2023-12-21 DOI:10.1097/PTS.0000000000001191
Xin Zhang, Shuhui Xu, Jing Sun, Ying Yang, Meihua Piao, Shih-Yu Lee
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引用次数: 0

Abstract

Objective: The aim of the study is to identify the hospitalized children at risk of peripheral intravenous catheter (PIVC) complications by severity prediction.

Methods: The study included the data of 301 hospitalized children with PIVC complications in 2 tertiary teaching hospitals. A researcher-designed tool was used to collect risk factors associated with PIVC complications. Predictors of PIVC complications at univariate analysis and multivariable logistic regression analysis by backward stepwise. A nomogram was constructed based on the results of the final multivariable model, making it possible to estimate the probability of developing complications.

Results: A total of 182 participants (60.5%) had a moderate injury from PIVC complications. Multivariable logistic regression analysis indicated that the vascular condition, limb immobilization, needle adjustment in venipuncture, infusion length, infusion speed, and insertion site were independent predictors. The nomogram for assessing the severity of PIVC complications indicated good predictive accuracy (area under the curve = 0.79) and good discrimination (concordance index = 0.779). Decision curve analysis demonstrated that the nomogram was a good clinical value with a wide range of threshold probabilities (4%-100%).

Conclusions: The risk prediction model has good predictive performance, and the nomogram provides an easy-to-use visualization to identify the severity of PIVC complications and guide timely nursing care management.

预测使用外周静脉导管的住院儿童并发症风险的提名图。
研究目的该研究旨在通过严重程度预测来识别有外周静脉导管(PIVC)并发症风险的住院患儿:研究纳入了两家三级教学医院 301 名患有外周静脉置管并发症的住院患儿的数据。研究人员设计了一种工具来收集与PIVC并发症相关的风险因素。对PIVC并发症的预测因素进行了单变量分析,并通过逆向逐步法进行了多变量逻辑回归分析。根据最终多变量模型的结果构建了一个提名图,从而可以估算出发生并发症的概率:结果:共有 182 名参与者(60.5%)因 PIVC 并发症而受到中度损伤。多变量逻辑回归分析表明,血管状况、肢体固定、静脉穿刺中的针头调整、输液长度、输液速度和插入部位是独立的预测因素。评估 PIVC 并发症严重程度的提名图显示了良好的预测准确性(曲线下面积 = 0.79)和良好的区分度(一致性指数 = 0.779)。决策曲线分析表明,提名图具有良好的临床价值,阈值概率范围较广(4%-100%):风险预测模型具有良好的预测性能,提名图提供了一种易于使用的可视化方法,可用于识别 PIVC 并发症的严重程度并指导及时的护理管理。
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来源期刊
Journal of Patient Safety
Journal of Patient Safety HEALTH CARE SCIENCES & SERVICES-
CiteScore
4.60
自引率
13.60%
发文量
302
期刊介绍: Journal of Patient Safety (ISSN 1549-8417; online ISSN 1549-8425) is dedicated to presenting research advances and field applications in every area of patient safety. While Journal of Patient Safety has a research emphasis, it also publishes articles describing near-miss opportunities, system modifications that are barriers to error, and the impact of regulatory changes on healthcare delivery. This mix of research and real-world findings makes Journal of Patient Safety a valuable resource across the breadth of health professions and from bench to bedside.
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