Article(id=1322954280889627236, tenantId=1146029695717560320, journalId=1319373162502258839, issueId=1322954180431847810, articleNumber=null, orderNo=null, doi=10.16016/j.2097-0927.202509021, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1756915200000, receivedDateStr=2025-09-04, revisedDate=1764259200000, revisedDateStr=2025-11-28, acceptedDate=null, acceptedDateStr=null, onlineDate=1793346479866, onlineDateStr=2026-10-30, pubDate=1765728000000, pubDateStr=2025-12-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793346479866, onlineIssueDateStr=2026-10-30, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793346479866, creator=13701087609, updateTime=1793346479866, updator=13701087609, issue=Issue{id=1322954180431847810, tenantId=1146029695717560320, journalId=1319373162502258839, year='2025', volume='47', issue='23', pageStart='2881', pageEnd='3008', issueExtLink='null', onlineDate='null', pubDate='1765728000000', pubDateStr='2025-12-15', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793346455915, creator='13701087609', updateTime=1793346455915, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=3002, endPage=3008, ext={EN=ArticleExt(id=1322954282777064037, articleId=1322954280889627236, tenantId=1146029695717560320, journalId=1319373162502258839, language=EN, title=Development and validation of a risk prediction model for infiltration/extravasation in peripheral intravenous catheter therapy, columnId=1320441115505971258, journalTitle=Journal of Army Medical University, columnName=Evidence-Based Nursing Horizons, runingTitle=null, highlight=null, articleAbstract=
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.

, authors=Cui WANG1, Lin TAN1, Xue ZHANG1, Xinyan HUANG1, Lu MAO1, Jiasi ZHANG2, authorsList=Cui WANG, Lin TAN, Xue ZHANG, Xinyan HUANG, Lu MAO, Jiasi ZHANG, authorCompany=null, correspAuthors=Jiasi ZHANG, authorNote=null, correspAuthorsNote=null, copyrightStatement=© 2025 Journal of Army Medical University, copyrightOwner=Editorial Office of Journal of Army Medical University, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1322954283880165993, articleId=1322954280889627236, tenantId=1146029695717560320, journalId=1319373162502258839, language=CN, title=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, columnId=1322954282919670374, journalTitle=陆军军医大学学报, columnName=循证护理前沿·论著, runingTitle=null, highlight=null, articleAbstract=
目的

探究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。

方法

回顾性选取2023年1-6月在陆军军医大学第一附属医院内分泌科、神经内科、消化科、肝胆外科等科室完成《外周静脉留置针输液渗出/外渗风险评估表》填写的942例患者为研究对象,根据行外周静脉留置针的时间顺序按照2∶1的比例分为建模组(628例)和验证组(314例),建模组用于外周静脉留置针输液渗出/外渗风险预测模型的建立和内部验证,验证组用于模型的外部验证。根据Logistic评分法构建风险模型,霍斯默-莱梅肖(Hosmer-Lemeshow,HL)检验对所建立模型进行拟合优度检验,用ROC曲线评价模型预测价值。外周静脉留置针输液渗出/外渗风险评估包括年龄、性别、慢性病史、操作护理人员工作年限、输液治疗依从性、输液总量等21个因素。

结果

942例患者共48例(其中建模组31例,验证组17例)发生渗出/外渗,总发生率为5.10%;21个因素中除性别、BMI、凝血功能、操作护理人员工作年限等以外均为渗出/外渗的影响因素(P<0.05),其中初中及以下文化、有慢性病史、依从性不好、穿刺血管为下肢静脉、输液总量≥1 000 mL、高渗/强酸/强碱等腐蚀性药物6个因素为独立危险因素(P<0.05)。外周静脉留置针输液渗出/外渗风险预测模型为:Y=2×初中及以下文化+1×有慢性病史+1×依从性不好+1×穿刺血管(下肢静脉)+1×输液总量≥1 000 mL+2×高渗/强酸/强碱等腐蚀性药物。建模组ROC曲线下面积(area under the curve,AUC)为0.967(95%CI:0.936~0.998),特异性为0.911,敏感性为0.935,HL检验提示模型校准度良好(χ²=4.135,P=0.845);验证组AUC为0.939(95%CI:0.853~1.000),特异性为0.919,敏感性为0.941;HL检验显示模型拟合尚可(χ²=8.998,P=0.085)。

结论

外周静脉留置针输液渗出/外渗风险预测模型具有良好的区分度与校准度,可为临床识别出外周静脉留置针输液渗出/外渗高风险患者并提供针对性预防措施及有效工具。

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张佳思,E-mail:
ZHANG Jiasi,E-mail:
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J Pract Gynecol Endocrinol Electron Ed,2016,3(15):30-31., articleTitle=Humanized nursing service in patients with this infusiondisease cognition and the influence of infusion adherence, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1322954284215710314, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322954280889627236, xref=1, ext=[AuthorCompanyExt(id=1322954284224098923, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322954280889627236, companyId=1322954284215710314, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1Department of Neurology, First Affiliated Hospital,Army Medical University (Third Military Medical University),Chongqing,China), AuthorCompanyExt(id=1322954284228293228, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322954280889627236, companyId=1322954284215710314, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1陆军军医大学(第三军医大学)第一附属医院:神经内科,重庆)]), AuthorCompany(id=1322954284307985005, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322954280889627236, xref=2, ext=[AuthorCompanyExt(id=1322954284320567918, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322954280889627236, companyId=1322954284307985005, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2Department of Hematology, First Affiliated Hospital,Army Medical University (Third Military Medical University),Chongqing,China), AuthorCompanyExt(id=1322954284328956527, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322954280889627236, companyId=1322954284307985005, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2陆军军医大学(第三军医大学)第一附属医院:血液内科,重庆)])], figs=[ArticleFig(id=1322954288695227030, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322954280889627236, language=EN, label=Figure 1, caption=ROC curve for predicting effusion/extravasation risk in modeling group and validation group, figureFileSmall=KHwgke62LTSWS9o3XEGPIg==, figureFileBig=7s9IPrq4XJev791IYxu1Ww==, tableContent=null), ArticleFig(id=1322954288762335895, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322954280889627236, language=CN, label=图1, caption=建模组与验证组渗出/外渗风险预测ROC曲线, figureFileSmall=KHwgke62LTSWS9o3XEGPIg==, figureFileBig=7s9IPrq4XJev791IYxu1Ww==, tableContent=null), ArticleFig(id=1322954288997216920, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322954280889627236, language=EN, label=Table 1, caption=

Results of univariate analysis for modeling group [n(%)]

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ItemNormal(n=597)Effusion/Extravasation(n=31)χ²P
Age/years6.1410.013
<60382(63.99)13(41.94)
≥60215(36.01)18(58.06)
Education22.815<0.001
High school or above301(50.42)2(6.45)
Junior high school or below296(49.58)29(93.55)
Barthel index/points10.7340.001
>40557(93.30)24(77.42)
≤4040(6.70)7(22.58)
Chronic disease45.477<0.001
None423(70.85)4(12.90)
Present174(29.15)27(87.10)
IV infusion compliance
Good575(96.31)24(77.42)23.889<0.001
Poor22(3.69)7(22.58)
Flushing and sealing/(time/d)4.4910.034
≤1328(54.94)11(35.48)
>1269(45.06)20(64.52)
Puncture site26.488<0.001
Upper limb/neck577(96.65)24(77.42)
Lower limb20(3.35)7(22.58)
Intravenous catheter gauge/G6.1270.013
>22290(48.58)8(25.81)
18~22307(51.42)23(74.19)
Puncture frequency/time24.281<0.001
1562(94.14)22(70.97)
≥235(5.86)9(29.03)
Infusion tool21.634<0.001
Non-pressurized573(95.98)24(77.42)
Pressurized24(4.02)7(22.58)
Infusion volume/mL42.182<0.001
<1 000414(69.35)4(12.90)
≥1 000183(30.65)27(87.10)
Drugs84.701<0.001
Non-corrosive507(84.92)6(19.35)
Corrosive90(15.08)25(80.65)
Indwelling time/h4.3570.037
<48268(44.89)8(25.81)
≥48329(55.11)23(74.19)
), ArticleFig(id=1322954289097880217, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322954280889627236, language=CN, label=表1, caption=

建模组单因素分析结果[例(%)]

, figureFileSmall=null, figureFileBig=null, tableContent=
ItemNormal(n=597)Effusion/Extravasation(n=31)χ²P
Age/years6.1410.013
<60382(63.99)13(41.94)
≥60215(36.01)18(58.06)
Education22.815<0.001
High school or above301(50.42)2(6.45)
Junior high school or below296(49.58)29(93.55)
Barthel index/points10.7340.001
>40557(93.30)24(77.42)
≤4040(6.70)7(22.58)
Chronic disease45.477<0.001
None423(70.85)4(12.90)
Present174(29.15)27(87.10)
IV infusion compliance
Good575(96.31)24(77.42)23.889<0.001
Poor22(3.69)7(22.58)
Flushing and sealing/(time/d)4.4910.034
≤1328(54.94)11(35.48)
>1269(45.06)20(64.52)
Puncture site26.488<0.001
Upper limb/neck577(96.65)24(77.42)
Lower limb20(3.35)7(22.58)
Intravenous catheter gauge/G6.1270.013
>22290(48.58)8(25.81)
18~22307(51.42)23(74.19)
Puncture frequency/time24.281<0.001
1562(94.14)22(70.97)
≥235(5.86)9(29.03)
Infusion tool21.634<0.001
Non-pressurized573(95.98)24(77.42)
Pressurized24(4.02)7(22.58)
Infusion volume/mL42.182<0.001
<1 000414(69.35)4(12.90)
≥1 000183(30.65)27(87.10)
Drugs84.701<0.001
Non-corrosive507(84.92)6(19.35)
Corrosive90(15.08)25(80.65)
Indwelling time/h4.3570.037
<48268(44.89)8(25.81)
≥48329(55.11)23(74.19)
), ArticleFig(id=1322954289194349210, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322954280889627236, language=EN, label=Table 2, caption=

Independent variable assignment

, figureFileSmall=null, figureFileBig=null, tableContent=
ItemAssignment
Age<60 years=0,≥60 years=1
EducationHigh school or above=0,junior high school or below=1
Barthel index>40 points=0,0~40 points=1
Chronic diseaseNone=0,Present=1
IV infusion complianceGood=0,Poor=1
Flushing and sealing0~1 time/day=0,>1 time/day=1
Puncture siteUpper limb/neck=0,lower limb=1
Catheter gauge>22 G=0,18 G~22 G=1
Puncture frequency0~1 time=0,>1 time=1
Infusion toolNon-pressurized=0,Pressurized=1
Infusion volume<1 000 mL=0,≥1 000 mL=1
Corrosive drugsNo=0,Yes=1
Indwelling time<48 h=0,≥48 h=1
), ArticleFig(id=1322954289269846683, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322954280889627236, language=CN, label=表2, caption=

自变量赋值情况

, figureFileSmall=null, figureFileBig=null, tableContent=
ItemAssignment
Age<60 years=0,≥60 years=1
EducationHigh school or above=0,junior high school or below=1
Barthel index>40 points=0,0~40 points=1
Chronic diseaseNone=0,Present=1
IV infusion complianceGood=0,Poor=1
Flushing and sealing0~1 time/day=0,>1 time/day=1
Puncture siteUpper limb/neck=0,lower limb=1
Catheter gauge>22 G=0,18 G~22 G=1
Puncture frequency0~1 time=0,>1 time=1
Infusion toolNon-pressurized=0,Pressurized=1
Infusion volume<1 000 mL=0,≥1 000 mL=1
Corrosive drugsNo=0,Yes=1
Indwelling time<48 h=0,≥48 h=1
), ArticleFig(id=1322954289366315676, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322954280889627236, language=EN, label=Table 3, caption=

Results of multivariate binary logistic regression analysis for modeling group

, figureFileSmall=null, figureFileBig=null, tableContent=
ItemβSEΖWald χ²POR95% CI
Age(≥60 years)0.7100.6951.0221.0440.3072.0350.521~7.952
Junior high school or below2.5910.9362.7697.6660.00613.3402.131~83.483
Barthel index(≤40 points)0.4040.8530.4730.2240.6361.4970.281~7.974
Chronic disease1.6040.7142.2465.0450.0254.9751.227~20.178
Poor IV infusion compliance1.7190.7852.1914.8000.0285.5811.199~25.988
Flushing and sealing (>1 time/d)0.5250.7620.6890.4740.4911.6900.380~7.527
Lower limb puncture1.8930.9362.0234.0920.0436.6371.061~41.529
Intravenous catheter gauge (18~22 G)0.8820.6171.4292.0420.1532.4150.721~8.094
Puncture frequency(>1 time)0.8440.7361.1481.3170.2512.3270.550~9.843
Pressurized tool0.1700.9580.1770.0310.8591.1850.181~7.742
Infusion volume(≥1 000 mL)2.3040.7513.0699.4190.00210.0122.299~43.595
Corrosive drugs2.7110.6584.12116.981<0.00115.0504.144~54.653
Indwelling time(≥48 h)0.3190.8330.3830.1470.7021.3760.269~7.042
Intercept-10.5941.516-6.98748.822<0.00100.000~0.000
), ArticleFig(id=1322954289487950493, tenantId=1146029695717560320, journalId=1319373162502258839, articleId=1322954280889627236, language=CN, label=表3, caption=

建模组多因素二元逻辑回归分析结果

, figureFileSmall=null, figureFileBig=null, tableContent=
ItemβSEΖWald χ²POR95% CI
Age(≥60 years)0.7100.6951.0221.0440.3072.0350.521~7.952
Junior high school or below2.5910.9362.7697.6660.00613.3402.131~83.483
Barthel index(≤40 points)0.4040.8530.4730.2240.6361.4970.281~7.974
Chronic disease1.6040.7142.2465.0450.0254.9751.227~20.178
Poor IV infusion compliance1.7190.7852.1914.8000.0285.5811.199~25.988
Flushing and sealing (>1 time/d)0.5250.7620.6890.4740.4911.6900.380~7.527
Lower limb puncture1.8930.9362.0234.0920.0436.6371.061~41.529
Intravenous catheter gauge (18~22 G)0.8820.6171.4292.0420.1532.4150.721~8.094
Puncture frequency(>1 time)0.8440.7361.1481.3170.2512.3270.550~9.843
Pressurized tool0.1700.9580.1770.0310.8591.1850.181~7.742
Infusion volume(≥1 000 mL)2.3040.7513.0699.4190.00210.0122.299~43.595
Corrosive drugs2.7110.6584.12116.981<0.00115.0504.144~54.653
Indwelling time(≥48 h)0.3190.8330.3830.1470.7021.3760.269~7.042
Intercept-10.5941.516-6.98748.822<0.00100.000~0.000
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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
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汪萃 1 , 谭琳 1 , 张雪 1 , 黄新艳 1 , 毛鹭 1 , 张佳思 2
陆军军医大学学报 | 循证护理前沿·论著 2025,47(23): 3002-3008
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陆军军医大学学报 |循证护理前沿·论著 2025 , 47 (23) : 3002 -3008
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
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汪萃1, 谭琳1, 张雪1, 黄新艳1, 毛鹭1, 张佳思2
作者信息
  • 1陆军军医大学(第三军医大学)第一附属医院:神经内科,重庆
  • 2陆军军医大学(第三军医大学)第一附属医院:血液内科,重庆
通讯作者:
张佳思,E-mail:
ZHANG Jiasi,E-mail:
Development and validation of a risk prediction model for infiltration/extravasation in peripheral intravenous catheter therapy
Cui WANG1, Lin TAN1, Xue ZHANG1, Xinyan HUANG1, Lu MAO1, Jiasi ZHANG2
Affiliations
  • 1Department of Neurology, First Affiliated Hospital,Army Medical University (Third Military Medical University),Chongqing,China
  • 2Department of Hematology, First Affiliated Hospital,Army Medical University (Third Military Medical University),Chongqing,China
出版时间: 2025-12-15 doi: 10.16016/j.2097-0927.202509021
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目的

探究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。

方法

回顾性选取2023年1-6月在陆军军医大学第一附属医院内分泌科、神经内科、消化科、肝胆外科等科室完成《外周静脉留置针输液渗出/外渗风险评估表》填写的942例患者为研究对象,根据行外周静脉留置针的时间顺序按照2∶1的比例分为建模组(628例)和验证组(314例),建模组用于外周静脉留置针输液渗出/外渗风险预测模型的建立和内部验证,验证组用于模型的外部验证。根据Logistic评分法构建风险模型,霍斯默-莱梅肖(Hosmer-Lemeshow,HL)检验对所建立模型进行拟合优度检验,用ROC曲线评价模型预测价值。外周静脉留置针输液渗出/外渗风险评估包括年龄、性别、慢性病史、操作护理人员工作年限、输液治疗依从性、输液总量等21个因素。

结果

942例患者共48例(其中建模组31例,验证组17例)发生渗出/外渗,总发生率为5.10%;21个因素中除性别、BMI、凝血功能、操作护理人员工作年限等以外均为渗出/外渗的影响因素(P<0.05),其中初中及以下文化、有慢性病史、依从性不好、穿刺血管为下肢静脉、输液总量≥1 000 mL、高渗/强酸/强碱等腐蚀性药物6个因素为独立危险因素(P<0.05)。外周静脉留置针输液渗出/外渗风险预测模型为:Y=2×初中及以下文化+1×有慢性病史+1×依从性不好+1×穿刺血管(下肢静脉)+1×输液总量≥1 000 mL+2×高渗/强酸/强碱等腐蚀性药物。建模组ROC曲线下面积(area under the curve,AUC)为0.967(95%CI:0.936~0.998),特异性为0.911,敏感性为0.935,HL检验提示模型校准度良好(χ²=4.135,P=0.845);验证组AUC为0.939(95%CI:0.853~1.000),特异性为0.919,敏感性为0.941;HL检验显示模型拟合尚可(χ²=8.998,P=0.085)。

结论

外周静脉留置针输液渗出/外渗风险预测模型具有良好的区分度与校准度,可为临床识别出外周静脉留置针输液渗出/外渗高风险患者并提供针对性预防措施及有效工具。

静脉输液  /  渗出  /  外渗  /  风险评估
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.

intravenous infusions  /  effusion  /  extravasation  /  risk assessment
汪萃, 谭琳, 张雪, 黄新艳, 毛鹭, 张佳思. 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. 陆军军医大学学报, 2025 , 47 (23) : 3002 -3008 . DOI: 10.16016/j.2097-0927.202509021
Cui WANG, Lin TAN, Xue ZHANG, Xinyan HUANG, Lu MAO, Jiasi ZHANG. Development and validation of a risk prediction model for infiltration/extravasation in peripheral intravenous catheter therapy[J]. Journal of Army Medical University, 2025 , 47 (23) : 3002 -3008 . DOI: 10.16016/j.2097-0927.202509021
药物渗出是指静脉输液过程中,非腐蚀性药液进入静脉管腔以外的周围组织;药物外渗是指静脉输液过程中,腐蚀性药液进入静脉管腔以外的周围组织[1]。尽管二者在药液性质上存在差异,但其发生初期的临床表现相似,早期处理原则也相通,因此在研究与临床预防中常合并阐释[2]。药物渗出/外渗作为外周静脉留置针常见的并发症,发生率为0.1%~6.0%[3],易导致患者出现穿刺点局部红肿、疼痛,甚至引起组织坏死、关节与神经损伤,这不仅直接影响患者的安全与结局,也通过延长照护周期、复杂化干预措施提高了护理工作的强度与复杂性。临床对于外周静脉留置针输液渗出/外渗的预防与管理,多依赖于护理人员的个体化经验与被动观察,缺乏标准化、前瞻性的风险评估工具作为决策支持。尽管既往研究已成功筛查并明确了诸多相关风险因素,但这些成果多停留在因素罗列与定性分析的层面[4-5],未能进一步整合、量化,构建成可直接应用于临床实践的预测模型,在早期识别与针对性干预中尚有局限。本研究将散在的风险因素转化为一个具有高预测效能的数学工具,从而为临床护理人员提供一种客观、量化的风险评估方法。不仅为实现个体化的风险预测与分级管理提供了关键工具,有望从根本上推动该并发症的防控策略从事后处理向事前预防转变,对于提升患者静脉治疗安全、优化护理资源配置具有重要的临床价值。
纳入标准:①年龄≥18岁;②行外周静脉留置针输液治疗;③完成《外周静脉留置针输液渗出/外渗风险评估表》的填写,且相关资料保存齐全。排除标准:①合并血液系统疾病者;② 合并免疫系统疾病者(如:系统性红斑狼疮、类风湿关节炎等);③重要器官(心、肺、肝、肾)存在严重功能不全者;④已患有静脉炎者;⑤有精神病史及认知障碍。本研究已通过陆军军医大学第一附属医院伦理委员会审查[(B)KY2025105]。根据样本量计算公式:n=Uα/22×pqδ2,进行样本量计算[6]。P值以文献报道的外周静脉留置针输液渗出/外渗发生率5.5%进行计算,即α=0.05,Uα/2=1.96,p=0.055,q=1-0.055,δ=0.05,根据公式计算得出建模组样本大于80例。采用便利抽样的方法,回顾性选取2023年1-6月在陆军军医大学第一附属医院内分泌科、神经内科、消化科、肝胆外科等科室完成《外周静脉留置针输液渗出/外渗风险评估表》填写的患者为研究对象,符合纳排标准的患者共计942例,根据行外周静脉留置针的时间顺序按照2∶1[7]的比例分为建模组(2023年1-4月)和验证组(2023年5-6月),即建模组628例、验证组314例。建模组用于外周静脉留置针输液渗出/外渗风险预测模型的建立和内部验证,验证组用于模型的外部验证。
本研究所需的观察指标均来源于本院静脉治疗护理专业委员会联络员搜集的《外周静脉留置针输液渗出/外渗风险评估表》。该表是2022年本院静脉治疗护理专业委员会通过文献研究、临床实践、专家访谈等研制而成,具有良好的内容效度。收集的核心变量包括——①患者基线特征:年龄、性别、文化程度、BMI、自理能力、慢性病史(如糖尿病、脑血管病、肿瘤等)及治疗依从性;②临床操作因素:操作护理人员工作年限、穿刺部位(上肢/下肢等)、置管血管、留置针型号、同一部位穿刺次数、冲封管频率及健康教育执行情况;③治疗相关因素:输液总量、输液时长及输注药物的性质,其中药物类别为高渗性药物、血管活性药物、化疗药物、抗生素、强碱性药物、强酸性药物、其他等。静脉输液依从性评估标准为①完全依从:指患者或其陪护人员能够主动、持续地保持穿刺肢体的稳定,无自行调整体位、频繁移动或抓挠穿刺部位等行为,无需护理人员反复提醒;②部分依从:指患者能在护理人员提醒下配合制动,但存在偶尔、无意识的肢体活动,或需要依靠约束工具等辅助措施才能维持体位稳定;③不依从:指患者由于躁动、意识障碍等原因,完全无法配合制动,肢体活动频繁且剧烈,存在极高的非计划性拔管或渗出的风险。“完全依从+部分依从”纳入“依从性好”;“不依从”纳入依从性不好。“自理能力评分”采用的是Barthel指数,为4个等级:≤20分,重度依赖;21~40分,中度依赖;41~60分,轻度依赖;>60分,无依赖。
为确保研究数据的准确性、完整性与一致性,采用双人独立录入、交叉核对、人工与计算机相结合核查等方法来确保最终数据的准确可靠[8]。
根据SULLIVAN等[9]的逻辑评分法构建风险模型,具体以多因素逻辑回归分析结果中的P<0.05相关项的回归系数大小来确定。选取回归分析结果中最小的回归系数为基数,其他变量的回归系数值与之相比的结果按四舍五入法,取其整数部分即为每个自变量相应权重分值。
采用SPSS 22.0和MedCalc软件进行分析处理。分类变量以频数(%)表示;对建模组与验证组相关变量对比分析时,除了BMI、自理能力、操作护理人员工作年限等需进行秩和检验外,其余均采用χ2检验或Fisher精确检验;建模组渗出/外渗的单因素分析中,各分类变量均为二分类变量,均采用χ2检验或Fisher精确检验;建模组渗出/外渗的多因素分析采用二元Logistic回归分析;霍斯默-莱梅肖(Hosmer-Lemeshow,HL)检验对所建立模型进行拟合优度检验,用ROC曲线评价模型预测价值。检验水准α=0.05。
942例患者共48例(其中建模组31例,验证组17例)发生渗出/外渗,总发生率为5.10%。建模组与验证组在基线资料上的比较结果显示,2组患者在渗出/外渗发生率、性别、年龄、文化程度、BMI、自理能力、慢性病史、凝血功能、护理操作者工作年限等所有观察变量上的分布差异均无统计学意义。提示建模组与验证组基线资料具有可比性。
以患者是否发生渗出/外渗作为因变量进行单因素分析,结果显示:年龄、文化程度、自理能力、慢性病史、治疗依从性、每天冲封管次数、穿刺血管、留置针型号、同一部位穿刺次数、是否使用加压输入工具、输液时长、输液总量、输液药物分类、留置时间等是影响外周静脉留置针输液发生渗出/外渗的因素(P<0.05),而性别、BMI、凝血功能、操作护理人员工作年限等变量组间无显著差异,见表1。提示外周静脉留置针输液渗出/外渗的发生与患者自身状况、治疗行为及药物特性等多方面因素有关。
将单因素分析中P<0.05的变量纳入二元Logistic回归模型,以筛选“渗出/外渗”独立危险因素。外周静脉留置针输液发生渗出/外渗的影响因素的自变量赋值方式见表2。分析结果表明,初中及以下文化、有慢性病史、依从性不好、穿刺血管为下肢静脉、输液总量≥1 000 mL、高渗/强酸/强碱等腐蚀性药物6个因素为独立危险因素(表3)。提示这6个因素是导致外周静脉留置针输液发生渗出/外渗的独立预测变量。
基于多因素Logistic回归分析得到的回归系数,构建了外周静脉留置针输液渗出/外渗的风险预测模型。最终模型为:Y=2×初中及以下文化+1×有慢性病史+1×依从性不好+1×穿刺血管(下肢静脉)+1×输液总量≥1 000 mL+2×高渗/强酸/强碱等腐蚀性药物。提示该模型能综合量化各独立危险因素的影响程度,用于计算个体的风险评分。
采用ROC曲线和HL拟合优度检验评价模型的区分度与校准度。结果显示,建模组ROC曲线下面积(area under the curve,AUC)为0.967(95%CI:0.936~0.998),特异性为0.911,敏感性为0.935,HL检验显示模型拟合良好(χ²=4.135,P=0.845),预测概率96.82%;验证组AUC为0.939(95%CI:0.853~1.000),特异性为0.919,敏感性为0.941;HL检验显示模型拟合较好(χ²=8.998,P=0.085),预测概率97.13%,见图1。提示本研究所构建的风险预测模型具有优异的区分能力和校准度,且在外部验证中表现出良好的泛化性能。
本研究所建立的外周静脉留置针输液渗出/外渗风险预测模型包含的指标易获取及控制,同时将相关因素直观展示到公式中,可行性佳,有助于早期识别风险。外周静脉留置针在静脉内不易滑出,可随时进行输液、输血,有减少穿刺次数、提高护理工作效率等优点[10-11]。不过也可能会出现并发症,如液体渗出、外渗、静脉炎、堵管等[12-14]。其中,液体渗出/外渗是静脉留置针输液常见并发症[15-16]。本研究将医护人员的视角由发生风险再处理转向在患者置入外周静脉留置针后进行有目的的预防,从而减少外周静脉留置针输液渗出/外渗的发生,实现从“研究模型”到“临床实践”的有效转化。
既往研究指出,渗出/外渗的影响因素涉及技术、机械、化学及并发症等多维度因素[17]。本研究发现,年龄、文化程度等13个方面是外周静脉留置针输液发生渗出/外渗的影响因素。其中,文化程度为初中及以下、存在慢性病史、治疗依从性较差、穿刺部位为下肢静脉、输液总量≥1 000 mL、使用高渗/强酸/强碱等腐蚀性药物6项为独立危险因素。
本研究结果显示,外周静脉留置针输液中高渗/强酸/强碱等腐蚀性药物是其独立影响因素,且风险系数最高。高渗/强酸/强碱等腐蚀性药物多为高渗溶液,进入血管后会直接刺激内皮细胞而引发血管平滑肌痉挛性收缩,同时形成的渗透梯度导致内皮细胞脱水等病理改变,促使血小板聚集及前列腺素E1/E2等炎性介质释放,增加静脉壁通透性并诱发白细胞浸润及炎症反应[18]。对此,我国《静脉治疗护理技术操作标准》提出,对于外周静脉留置针不宜持续静脉输注具有刺激性药物[2]。尽管本研究观察到刺激性药物在特定临床场景中的使用需求,但多因素分析结果以客观数据再次验证了其高风险性。因此,在输注前严格评估治疗方案与药物性质,优先推荐经中心静脉通路输注。紧急情况下或患者及家属拒绝使用中心静脉通路输注的情况下,需经外周静脉输注刺激性药物时,应与患者签署《经外周浅静脉输注刺激性药物知情同意书》,并将该患者作为需要重点监护的对象,主动增加评估频次,仔细检查穿刺部位,并严格调控输注浓度与速度,加强观察。
在单因素分析中,下肢静脉发生渗出/外渗的风险显著高于上肢及颈部血管,并成为该并发症的独立影响因素,其原因与血流动力学特征相关。与上肢静脉及颈部血管相比,下肢静脉的静脉瓣膜密度更高,药物的直接刺激容易出现机械性损伤,炎性反应风险较高,从而增加了血管通透性及液体渗漏风险[19-20]。为此,尽量避免使用下肢静脉,若无其他更好选择时,下肢静脉输液时应避免其他几个渗出/外渗影响因素的出现,还应进行体位、输液速度等调整。
本预测模型显示,当总输液量≥1 000 mL时,渗出/外渗风险升高。这可能是因为大量液体输注导致血管内胶体渗透压下降,以及长时间化学刺激,两者共同造成对内皮的损伤。对于此类患者,应系统性评估治疗方案及输注时长;科学规划输注节奏与速率;特别关注儿科及老年患者生理特征与剂量限制;动态监测及时识别不良反应并调整干预措施。
既往研究证实,高血压、糖尿病等慢性疾病会直接导致血管内皮功能紊乱、弹性下降及纤维化程度增加,其血管弹性指标显著劣于健康同龄人[21-22]。此类患者血管质量的下降,降低了血管耐受静脉输注物理与化学刺激的能力,从而更易发生内皮损伤与液体渗漏[23]。本研究模型中,慢性病史较生理年龄更能直接表观血管的生理状态与累积损耗。因此建议将风险评估的焦点从“患者的日历年龄”转向“其血管的生理年龄”。对于合并慢性病的患者,应建立前瞻性的动态血管评估机制,例如在置管前利用床旁超声量化评估血管直径、管壁厚度及血流情况,并结合患者的具体临床体征,制定真正个性化的穿刺方案与动态监护策略,从而实现风险的超早期识别与干预[24]。
文化程度会在一定程度上影响外周静脉留置针输液的渗出/外渗:①知识水平的差异可能导致这部分患者对输液过程中的注意事项、存在的风险缺乏充分理解,因此在输液过程中未能按照医护人员的指导进行恰当的自我观察和护理;②文化程度低的群体中老年患者比例较高,其本身可能因血管老化、通透性增加等生理性退变而具有更高的基础风险。因此,对此类患者应强化健康教育的有效性与可及性[25]。
留置针穿刺的创伤性、置管时长以及疾病带来的负性情绪与疾病认知不足,均可导致患者依从性下降,进而增加反复穿刺、渗出、回血等不良事件风险[26]。研究表明,通过更人性化的护理,构建良好输液环境,全程进行健康教育对提高输液时患者的依从性有积极作用[27]。
ROC曲线作为一种直观且有效的工具,能够综合反映模型在区分不同类别样本时的性能表现。本研究所构建的风险预测模型在建模组与验证组均表现出较高的区分度,AUC值理想,且灵敏度和特异性均维持在较高水平。结果表明,该模型不仅能有效鉴别已发生渗出/外渗的病例,更能较好地预测其发生风险,为临床实施针对性预防措施提供了可靠的量化工具。
本研究构建的预测模型整合了6大独立危险因素。经内部验证,该模型展现出可靠的预测效能,可为临床早期识别渗出/外渗风险提供量化评估工具。在实践上,可根据模型建立更精细化的护理路径或电子医嘱系统,从而实现从“风险预测”到“个性化精准预防”的跨越,最终全方位提升静脉治疗的安全性与质量,并可拓展至多中心协作,纳入更大规模的临床数据,通过外部验证进一步优化模型参数,提升其临床适用性和推广价值。但本研究存在以下局限:①将渗出/外渗进行了合并,腐蚀性药物可能是留置针“药物外渗”的风险因素,但在“药物渗出”的风险因素需要有待进一步验证;②样本全部来源于单中心三级甲等医院,且总体样本量有限。未来可进一步细化渗出与外渗的独立模型构建,或增加药物类型子项(如明确腐蚀性药物具体种类及对应留置时间阈值),以更精准指导临床实践。

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2025年第47卷第23期
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doi: 10.16016/j.2097-0927.202509021
  • 接收时间:2025-09-04
  • 首发时间:2026-10-30
  • 出版时间:2025-12-15
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  • 收稿日期:2025-09-04
  • 修回日期:2025-11-28
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    1陆军军医大学(第三军医大学)第一附属医院:神经内科,重庆
    2陆军军医大学(第三军医大学)第一附属医院:血液内科,重庆

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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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