以质量求发展,以服务铸品牌

护理学报 ›› 2019, Vol. 26 ›› Issue (22): 1-5.doi: 10.16460/j.issn1008-9969.2019.22.001

• 研究生园地 •    下一篇

Autar量表与Caprini评估模型对肿瘤患者PICC相关静脉血栓形成预测效果的对比研究

李钱玲a, 甘秀妮a, 李源b, 唐玮c   

  1. 重庆医科大学附属第二医院a.护理部; b.重症医学科; c.肾内科,重庆 400010
  • 收稿日期:2019-04-14 发布日期:2020-07-27
  • 通讯作者: 唐 玮(1980-),女,四川广安人,硕士,主管护师,副护士长。E-mail:25653972@qq.com
  • 作者简介:李钱玲(1991-),女,重庆人,本科学历,硕士研究生在读。
  • 基金资助:
    重庆市卫生计生委2018年医学科研项目面上项目(2018MSXM093)

Comparison of Predictive Power for PICC-related Venous Thromboembolism among Cancer Patients of Autar DVT Risk Assessment Scale and Caprini Risk Assessment Scale

LI Qian-linga, GAN Xiu-nia, LI Yuanb, TANG Weic   

  1. a. Dept. of Nursing Administration; b. Dept. of Critical Care Medicine; c. Dept. of Nephrology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing 400010, China
  • Received:2019-04-14 Published:2020-07-27

摘要: 目的 比较Autar量表与Caprini评估模型对肿瘤患者PICC相关静脉血栓形成的预测效度。方法 采用病例对照研究,收集2012—2017年125例行PICC置管肿瘤患者的一般资料、置管资料。将确诊已发生PICC相关静脉血栓的肿瘤患者作为病例组,按照肿瘤类型相同采用1∶4配对方法,选取同期留置但未发生PICC相关静脉血栓的患者作为对照组,使用Autar量表与Caprini评估模型分别对患者进行评分并记录,并分析2个量表的最佳诊断界值。结果 Caprini评估模型最佳诊断界值为7分,灵敏度为0.661,特异度为0.724,曲线下面积为0.763;Autar量表最佳诊断界值为10分,灵敏度为0.642,特异度为0.555,曲线下面积为0.632。结论 Caprini评估模型灵敏度与特异度均高于Autar量表,能够更好地预测肿瘤患者发生PICC相关静脉血栓的风险。

关键词: Autar量表, Caprini评估模型, PICC相关静脉血栓, 风险评估

Abstract: Objective To compare the predictive power for PICC-related venous thromboembolism in cancer patients of Autar DVT risk assessment scale and Caprini risk assessment scale. Methods We retrospectively collected the data of 125 cases of cancer patients from 2012 to 2017 including their general information and PICC information. Patients with confirmed PICC-related venous thromboembolism were selected as case group, and according to the same tumor type, a 1∶4 pairing method was used, those without PICC-related venous thrombosis were selected as control group. Autar scale and Caprini risk assessment scale were used and we analyzed the best diagnostic threshold value of the two scales. Results The sensitivity and specificity of Caprini risk assessment scale were 0.661 and 0.724 respectively and the best diagnostic threshold value of it was 7. The sensitivity and specificity of of Autar scale was 0.642 and 0.555 respectively and the best diagnostic threshold value 10. The area under the ROC curve of Autar scale was 0.632 and that of Caprini risk assessment scale 0.763. Conclusion The predictive power of Caprini risk assessment scale is higher than that of Autar scale, which could better predict PICC-related venous thromboembolism for cancer patients for its higher sensitivity and specificity.

Key words: Autar scale, Caprini risk assessment scale, PICC-related venous thromboembolism, risk assessment

中图分类号: 

  • R473.73
[1] Luo L, Jing X, Wang G, et al.Peripherally Inserted Central Catheter-related Upper Extremity Venous Thrombosis in Oncology Patients[J]. J Ultrasound Med, 2016,35(8):1759-1763.DOI:10.7863/ultra.15.08019.
[2] Fallouh N, McGuirk H M, Flanders S A, et al. Peripherally Inserted Central Catheter-associated Deep Vein Thrombosis: A Narrative Review[J]. Am J Med, 2015,128(7):722-738.10.7863.DOI:10.1016/j.amjmed.2015.01.027.
[3] Zhang X, Huang J, Xia Y, et al.High Risk of Deep Vein Thrombosis Associated with Peripherally Inserted Central Catheters in Lymphoma[J]. Oncotarget, 2016,7(23):35404-35411.DOI:10.18632/oncotarget.8639.
[4] Menéndez J J, Verdú C, Calderón B, et al.Incidence and Risk Factors of Superficial and Deep Vein Thrombosis Associated with Peripherally Inserted Central Catheters in Children[J]. J Thromb Haemost, 2016,14(11):2158-2168.DOI:10.1111/jth.13478.
[5] Paauw J D, Borders H, Ingalls N, et al.The Incidence of PICC Line-associated Thrombosis with and without the Use of Prophylactic Anticoagulants[J]. J Parenter Enteral Nutr, 2008, 32(4):443-447.DOI:10.1177/0148607108319801.
[6] Cotogni P, Barbero C, Garrino C, et al.Peripherally Inserted Central Catheters in Non-hospitalized Cancer Patients: 5-Year Results of a Prospective Study[J]. Support Care Cancer, 2015, 23(2):403-409. DOI:10.1007/s00520-014-2387-9.
[7] 宋燕伶,何金爱,刘胤佃,等. PICC导管/静脉直径比最佳临界值的研究[J]. 中国护理管理, 2017,17(6):737-742.DOI:10.3969/j.issn.1672-1756.2017.06.005.
[8] Autar R.Nursing Assessment of Clients at Risk of Deep Vein Thrombosis (DVT): The Autar DVT Scale[J]. J Adv Nurs, 1996, 23(4):763-770.DOI:10.1111/j.1365-2648.1996.tb00049.x.
[9] Autar R.Evidence for the Prevention of Venous Thromboembolism[J]. Br J Nurs, 2006,15(18):980-986.
[10] 陈亚萍,张慧,王婷婷,等. 不同风险评估量表预测静脉血栓栓塞症风险的效果研究[J]. 护理研究, 2017,31(34):4404-4407.DOI:10.3969/j.issn.1009-6493.2017.34.026.
[11] 张成欢,李莹,刘云,等. 不同量表对髋膝关节置换患者深静脉血栓形成预测效果的对比研究[J]. 中华护理杂志,2017,52(4):503-506.DOI:10.3761/j.issn.0254-1769.2017.04.028.
[12] 张成欢,刘云. 骨科手术患者相关血栓形成风险评估的研究进展[J]. 医学研究生学报, 2015(4):445-448.DOI:10.3969/j.issn.1008-8199.2015.04.027.
[13] 万光明. Autar量表在肺癌患者经外周静脉置入中心静脉导管相关上肢静脉血栓形成风险评估中的应用[J]. 中华临床营养杂志, 2016,24(6):376-379.DOI:10.3760/cma.j.issn.1674-635X.2016.06.010.
[14] 万光明,颜美琼. 风险预警管理在预防肺癌患者经外周静脉置入中心静脉导管相关性血栓的临床观察[J]. 中华临床营养杂志, 2014,22(5):313-316.DOI:10.3760/cma.j.issn.1674-635X.2014.05.014.
[15] Caprini J A.Thrombosis Risk Assessment as a Guide to Quality Patient Care[J]. Dis Mon, 2005,51(2/3):70-78.DOI:10.1016/j.disamonth.2005.02.003.
[16] 周亚婷,史颜梅,白琳,等. 两种血栓风险评估模型在住院患者深静脉血栓形成中的预测价值研究[J]. 解放军护理杂志, 2018,35(4):27-31.DOI:10.3969/j.issn.1008-9993.2018.04.005.
[17] 朱薇,应燕萍,黄惠桥,等. 三种评分表预测PICC相关上肢深静脉血栓效果比较研究[J]. 护理学杂志, 2018,33(7):54-56.DOI:10.3807/j.ssn.1001-4152.2018.07.054.
[18] 陈亚萍,马玉芬,邢颖,等. 不同风险评估量表预测骨科术后病人静脉血栓栓塞症风险的研究[J].护理研究, 2018(15):2485-2487.DOI:10.3969/j.issn.1009-6493.2017.34.026.
[19] 张成欢,李莹,刘云,等. 关节置换患者围手术期深静脉血栓形成预防现状的多中心研究[J]. 中国护理管理, 2016, 16(2):180-185.DOI:10.3969/j.issn.1672-1756.2016.02.009.
[20] 张晓勤,何丹,黎嘉嘉,等. Caprini血栓风险评估量表评估重症住院患者静脉血栓栓塞风险的有效性研究[J]. 四川大学学报(医学版), 2015,46(5):732-735.DOI:10.13464/j.scuxbyxb.2015.05.017.
[21] 陈小兰,王勇,潘磊. Caprini评估模型筛选老年重症肺炎深静脉血栓的有效性[J]. 北京医学, 2016,38(10):989-993.DOI:10.15932/j.0253-9713.2016.10.006.
[22] 马军,吴一龙,秦叔逵,等. 中国肿瘤相关静脉血栓栓塞症预防与治疗专家指南(2015版)[J]. 中国实用内科杂志, 2015,35(11):907-920.DOI:10.3969/j.issn.1000-8179.2015.20.015.
[1] 范芳莲, 吕莹, 笪亚红. 新生儿医用粘胶相关性皮肤损伤风险评估量表的预测效能研究[J]. 护理学报, 2024, 31(11): 68-72.
[2] 周飞洋, 邓露, 龙柯宇, 杨婷婷, 谢琳琳, 吕倩, 郭春波. 老年人认知衰弱风险预测模型的系统评价[J]. 护理学报, 2023, 30(19): 45-50.
[3] 许汇娟, 刘颖, 姚嘉丽, 姚晶晶, 陈敏, 邱甜甜, 徐丹. 3种量表预测急性髓系白血病患者有症状性PICC相关血栓形成风险效果的比较[J]. 护理学报, 2023, 30(11): 59-64.
[4] 向御婷, 褚婕, 严敏, 乐曲, 余嘉欣. 孕产妇孕产期静脉血栓栓塞风险评估的最佳证据总结[J]. 护理学报, 2022, 29(3): 46-51.
[5] 陈浩, 张金俊, 刘菲, 吕梦, 王晶, 刘夏, 张淑香. 居家老年人静脉血栓风险自评量表的研制与应用[J]. 护理学报, 2022, 29(22): 15-19.
[6] 张瑞珂, 王玉秀. 基于危害分析与关键控制点理论的边缘型人格障碍住院患者非自杀性自伤行为护理管理实践[J]. 护理学报, 2022, 29(22): 20-25.
[7] 龚艳, 蒋琪霞, 陈文芳, 王海宏, 马丽. 手术获得性压力性损伤风险评估量表对手术患者压力性损伤预测效果的研究[J]. 护理学报, 2021, 28(9): 66-70.
[8] 张萍, 刘丽萍. 气管插管患者非计划拔管风险评估量表的构建[J]. 护理学报, 2021, 28(21): 18-22.
[9] 胡惠菊, 韩静, 唐启群, 成杰, 李慧源. Morse跌倒评估量表与STEADI跌倒风险自评量表在养老机构老年人中的应用比较[J]. 护理学报, 2021, 28(19): 8-12.
[10] 姚勋霞, 张理想, 曹教育, 欧安平, 胡芳, 吴金玉. 外周静脉应用血管活性药物致静脉炎危险因素的评估指标体系构建[J]. 护理学报, 2021, 28(12): 65-70.
[11] 张庆伟, 杨巧芳, 于漫. 风险评估和预警工具在心血管系统疾病中临床应用与思考[J]. 护理学报, 2019, 26(16): 34-37.
[12] 张亚,李琳,孟嘉,刘云,张成欢,李倩倩,赵泽华,马娜. 骨科大手术术前Autar评分联合D-二聚体值在深静脉血栓形成风险评估中的应用研究[J]. 护理学报, 2018, 25(5): 12-14.
[13] 吴巧媚,张利娟,郑静霞. 基于Delphi法ICU患者误吸风险评估体系的构建[J]. 护理学报, 2018, 25(2): 1-6.
[14] 刘瑞红,张霞,万晶晶,谭文红. 肾移植术后妊娠风险评估研究进展[J]. 护理学报, 2018, 25(2): 33-36.
[15] 胡娟娟,高兴莲,杨英,马琼. 基于手术室护理信息系统的手术压疮风险评估模块的应用[J]. 护理学报, 2018, 25(18): 27-29.
Viewed
Full text


Abstract

Cited

  Shared   
No Suggested Reading articles found!