目的 探讨维持性血液透析患者体外循环管路凝血所致非计划性下机的影响因素,建立维持性血液透析患者体外循环管路凝血所致非计划性下机的Nomogram模型并验证。 方法 回顾性选取2022年4月—2023年6月在绍兴第二医院医共体总院进行治疗的维持性血液透析患者,按照7∶3的比例分为建模组和验证组。收集建模组临床资料,根据患者是否发生体外循环管路凝血分为凝血组和非凝血组。比较2组临床资料,采用多因素Logistic回归分析维持性血液透析患者体外循环管路凝血的危险因素,构建维持性血液透析患者体外循环管路凝血的Nomogram模型并进行验证。 结果 共纳入286例患者,其中建模组200例、验证组86例。建模组中凝血组38例、非凝血组162例,维持性血液透析患者体外循环管路凝血发生率为19%。凝血组及非凝血组在是否合并低血压(χ2=4.630,P=0.031)、凝血酶原时间(t=2.392,P=0.018)、血小板计数(t=3.090,P=0.002)、是否首次接受血液透析(χ2=4.935,P=0.026)、抗凝方式(χ2=8.546,P=0.014)、治疗时间(χ2=9.497,P=0.009)、血流速度(χ2=5.194,P=0.023)、是否透析前健康教育(χ2=6.991,P=0.008)等方面比较差异有统计学意义。多因素Logistic回归分析结果显示:合并低血压(OR=3.160,95% CI:1.182~8.447,P=0.022)、血小板计数(OR=1.081,95% CI:1.049~1.115,P<0.001)、是否首次接受血液透析(OR=3.354,95% CI:1.202~9.359,P=0.021)、抗凝方式为无抗凝(OR=5.845,95% CI:1.697~20.132,P=0.005)、未接受健康教育(OR=6.524,95% CI:2.322~18.330,P<0.001)是发生体外循环管路凝血的独立危险因素;凝血酶原时间长(OR=0.378,95% CI:0.261~0.547,P<0.001)、血流速度≥200 ml/min(OR=0.226,95% CI:0.081~0.625,P=0.004)是体外循环管路凝血的保护因素。对Nomogram模型进行验证,ROC曲线下面积为0.891(95% CI:0.835~0.947),区分度良好,最大约登值为0.641,灵敏度为0.789,特异度为0.852。校准曲线的理论值和实际值有较好的一致性。 结论 本研究构建的维持性血液透析患者体外循环管路凝血所致非计划性下机的风险列线图Nomogram模型效果较好,为临床提供参考。
Objective To investigate the influential factors of unplanned disembarkation due to clotting in cardiopulmonary bypass line in maintenance hemodialysis (MHD) patients, and to establish a nomogram model of unplanned disembarkation due to clotting in cardiopulmonary bypass line in MHD patients and to validate the nomogram. Methods The MHD patients treated in the General Hospital of Shaoxing Second Hospital from April 2022 to June 2023 were retrospectively studied. They were divided into modeling group and validation group with the ratio of 7:3. The clinical data of the modeling group were collected and were then divided into coagulation subgroup and non-coagulation subgroup according to the presence or absence of clotting in cardiopulmonary bypass line. By comparing the clinical data of the two subgroups, multivariate logistic regression was used to analyze the risk factors for clotting in cardiopulmonary bypass line in the MHD patients, and a nomogram model of clotting in cardiopulmonary bypass line in MHD patients was established and validated. Results A total of 286 patients were recruited as the study subjects. They were divided into modeling group (n=200) and verification group (n=86) with the ratio of 7:3. The modeling group were divided into coagulation subgroup (n=38) and non-coagulation subgroup (n=162). The incidence of clotting in cardiopulmonary bypass line in MHD patients was 19%. Hypotension (χ2=4.630, P=0.031), prothrombin time (t=2.392, P=0.018), platelet count (t=3.090, P=0.002), hemodialysis for the first time (χ2=4.935, P=0.026), anticoagulation method (χ2=8.546, P=0.014), treatment time (<8h/d, 8-16h/d, >16h/d) (χ2=9.497, P=0.009), blood flow velocity (<200ml/min, ≥200ml/min) (χ2=5.194, P=0.023) and health education before dialysis (χ2=6.991, P=0.008) were statistically different between the two subgroups. Multivariate logistic regression showed that hypotension (OR=3.160, 95% CI: 1.182~8.447, P=0.022), platelet count (OR=1.081, 95% CI: 1.049~1.115, P<0.001), hemodialysis for the first time (OR=3.354, 95% CI: 1.202~9.359, P=0.021), no anticoagulation used (OR=5.845, 95% CI:1.697~20.132, P=0.005), and lack of health education (OR=6.524, 95% CI: 2.322~18.330, P<0.001) were the independent risk factors for clotting in cardiopulmonary bypass line; longer prothrombin time (OR=0.378, 95% CI:0.261~0.547, P<0.001) and blood flow velocity ≥200 ml/min (OR=0.226, 95% CI:0.081~0.625, P=0.004) were the protective factors for clotting in cardiopulmonary bypass line. For verification of the nomogram, the area under ROC curve was 0.891 (95% CI: 0.835~0.947), a better discrimination ability was identified, the maximum approximate entry value was 0.641, the sensitivity was 0.789, and the specificity was 0.852. The theoretical value of calibration curve was in better agreement with the actual value. Conclusion This nomogram model of unplanned disembarkation caused by clotting in cardiopulmonary bypass line in MHD patients shows a better efficiency, and provides a reference for clinical practice.
[1]张晋才,张锋,冯颖博,等.终末期肾病合并恶性肿瘤血透患者心理健康、生存质量与应对方式现状及其相关性分析[J].肿瘤预防与治疗,2022,35(12):1098-1102.
[2]韩苗苗,袁建军,申凯凯,等.基于射频信号全息血管硬度分析评价终末期肾病合并高尿酸血症患者颈动脉弹性[J].中国医学影像技术,2022,38(05):684-688.
[3]杨雅景,郑娜.时效性激励理论的健康教育在维持性血液透析患者体重管理中的应用研究[J].中国健康教育,2022,38(04):367-370.
[4]宋蓉蓉,何恩晓,李娜娜.分阶段教育联合分级随访在尿毒症维持性血液透析患者中的应用[J].河南医学研究,2022,31(11):2097-2100.
[5]王质刚.血液净化学[M].4版.北京:北京科学技术出版社,2016:535-536.
[6]Chaudhuri S, Larkin J, Guedes M, et al. Predicting mortality risk in dialysis: Assessment of risk factors using traditional and advanced modeling techniques within the Monitoring Dialysis Outcomes initiative. Hemodial Int. 2023 Jan;27(1):62-73.
[7]陈香美.血液净化标准操作规程[M].北京:人民卫生出版社,2021.
[8]张朝平,张永红,王园园.血液透析器凝血的原因分析及对策[J].基层医学论坛,2018,22(03):430-431.
[9]徐金艳.血液透析患者非计划性下机情况及影响因素分析[J].中国临床护理,2023,15(01):44-46+50.
[10]水光兴,邹峰,贺丹,等.简化枸橼酸抗凝在血液透析高危出血倾向患者中的临床应用研究[J].中国中西医结合肾病杂志,2021,22(03):237-239.
[11]朱旻霞,张伟明,倪兆慧,等.维持性血液透析患者透析期血压波动与透析相关并发症的相关性分析[J].上海交通大学学报(医学版),2020,40(04):484-488.
[12]付平,唐万欣,崔天蕾.连续性肾脏替代治疗的临床应用进展[J].中国实用内科杂志,2006(06):411-413.
[13]张仲华,曾铁英,徐蓉,等.无抗凝连续性肾脏替代治疗非计划性下机相关因素分析[J].护士进修杂志,2019,34(18):1633-1639.
[14]Ginel-Mendoza L, Hidalgo-Natera A, Reina-Gonzalez R, et al. Efficacy of a joint didactic intervention using the Junta De Andalucía School for Patients method to control prothrombin time in patients taking anticoagulants: protocol for a randomized controlled trial. Trials. 2021 Jan 11;22(1):45.
[15]王海波,李克鹏,徐丽娟,等.重症合并急性肾损伤患者持续静脉-静脉血液透析滤过治疗时滤器凝血预测模型的建立与评价[J].潍坊医学院学报,2019,41(01):52-54+74.