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Nomogram for Predicting the Risk of Complications in Hospitalized Children With Peripheral Intravenous Catheters
Xin Zhang1, Shuhui Xu2, Jing Sun2
1From the Chinese Academy of Medical Sciences and Peking Union Medical College.
Insights
This study developed a risk prediction model to identify hospitalized children at risk of peripheral intravenous catheter (PIVC) complications. The nomogram effectively predicts PIVC complication severity, aiding clinical nursing care.
Area of Science:
- Pediatric Nursing
- Medical Device Complications
- Clinical Risk Assessment
Background:
- Peripheral intravenous catheters (PIVCs) are common in hospitalized children.
- PIVC complications can lead to moderate to severe injuries.
- Accurate prediction of PIVC complication risk is crucial for patient safety.
Purpose of the Study:
- To identify hospitalized children at risk of peripheral intravenous catheter (PIVC) complications.
- To develop a severity prediction model for PIVC complications.
- To create a nomogram for easy-to-use visualization of complication risk.
Main Methods:
- Data from 301 hospitalized children with PIVC complications were analyzed.
- Risk factors were collected using a researcher-designed tool.
- Multivariable logistic regression and nomogram construction were employed.
Main Results:
- The nomogram demonstrated good predictive accuracy (AUC = 0.79) and discrimination (C-index = 0.779).
- Independent predictors included vascular condition, limb immobilization, venipuncture technique, infusion parameters, and insertion site.
- Decision curve analysis confirmed the nomogram's clinical utility across a wide probability range.
Conclusions:
- A risk prediction model and nomogram were developed for PIVC complications in children.
- The nomogram offers a user-friendly tool for assessing PIVC complication severity.
- This tool can guide timely and effective nursing care management.
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.
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