Development and validation of a risk prediction model for infiltration/extravasation in peripheral intravenous catheter therapy
10.16016/j.2097-0927.202509021
- VernacularTitle:外周静脉留置针输液渗出/外渗风险预测模型的构建及验证
- Author:
Cui WANG
1
;
Lin TAN
;
Xue ZHANG
;
Xinyan HUANG
;
Lu MAO
;
Jiasi ZHANG
Author Information
1. 陆军军医大学(第三军医大学)第一附属医院神经内科
- Keywords:
intravenous infusions;
effusion;
extravasation;
risk assessment
- From:
Journal of Army Medical University
2025;47(23):3002-3008,封3
- CountryChina
- Language:Chinese
-
Abstract:
Objective To develop and validate a risk prediction model for infiltration/extravasation in peripheral intravenous catheter therapy.Methods This retrospective study analyzed 942 patients who completed the Infiltration/Extravasation Risk Assessment Form between January and June 2023 at the First Affiliated Hospital of Army Medical University(including Departments of Neurology,Endocrinology,Gastroenterology and Hepatobiliary Surgery).Patients were allocated to a derivation cohort(n=628)and validation cohort(n=314)in a 2∶1 ratio based on catheterization chronology.The derivation cohort served for model development and internal validation,while the validation cohort underwent external validation.Logistic scoring method constructed the risk model,with Hosmer-Lemeshow(HL)test assessing goodness-of-fit and ROC curve evaluating predictive performance.Twenty-one potential risk factors were assessed,including age,gender,chronic diseases,clinician experience,treatment compliance,and total infusion volume.Results Infiltration/extravasation occurred in 48 cases(5.10%incidence:31 derivation/17 validation).Among 21 factors,15 showed significant association(P<0.05),with 6 independent predictors:junior high school education or below(OR=5.2),chronic disease history(OR=3.1),poor compliance(OR=2.8),lower extremity venipuncture(OR=4.1),total infusion≥1 000 mL(OR=3.5),and hyperosmotic/corrosive medications(OR=6.7).The final prediction model was:Y=2×(low education)+1×(chronic disease)+1×(poor compliance)+1×(lower extremity puncture)+1×(volume≥1 000 mL)+2×(corrosive agents).For the derivation cohort,AUC was 0.967(95%CI:0.936～0.998),specificity 0.911,sensitivity 0.935,with good calibration(χ2=4.135,P=0.845).Validation cohort showed AUC 0.939(0.853～1.000),specificity 0.919,sensitivity 0.941,and acceptable calibration(χ2=8.998,P=0.085).Conclusion This model demonstrates excellent discriminative ability and calibration,providing an effective tool for identifying high-risk patients and guiding targeted preventive strategies.
