摘要
目的对比中央透析液供给系统(central dialysis fluid delivery system,CDDS)与普通透析机2种类型设备的透析液洁净度以及故障率,分析CDDS透析设备的临床应用优势与不足。方法于2017年8月~2018年3月选择解放军总医院透析中心CDDS透析机GC-110N与贝朗德佳透析机各5台,对比2组透析机入口与出口处样本细菌、内毒素水平。回顾性分析解放军总医院2类透析设备各18台在2017年3月~2019年3月期间水路、电路以及其他故障的发生率。结果透析机入口采样点CDDS组透析机细菌、内毒素水平均低于普通组透析机(t值分别为11.215、6.468,P值分别为<0.001,<0.001)。透析机出口采样点CDDS组透析机细菌、内毒素水平均低于普通组透析机(t值分别为9.154、5.490,P值分别为<0.001,<0.001)。CDDS组透析机水路、电路以及其他故障的总计发生率均低于普通组透析机,差异有统计学意义(t=9.147,P=0.010)。结论CDDS系统可提高透析液洁净度,降低透析设备故障率在临床应用中具有一定优势。
Objective To compare the cleanliness and failure rate between the dialysis machines with central dialysis fluid delivery (CDDS) system and the conventional dialysis machines, and to analyze the clinical application advantages of the dialysis machines with CDDS system. Methods From August 2017 to March 2018, the bacteria number and endotoxin level at the inlet and outlet sites were compared between the dialysis machines with CDDS system (5 sets) and the Berengdejia dialyzer (5 sets) in the PLA General Hospital Dialysis Center. A retrospective analysis was performed on the incidence of water, circuit and other faults occurred in the dialysis machines with CDDS system (18 sets) and the Berengdejia dialyzer (18 sets) during the period from March 2017 to March 2019. Results The bacteria number and endotoxin level at the inlet were lower in the dialysis machines with CDDS system than in the conventional dialysis machines (t=11.215 and 6.468 respectively;P<0.001). The bacteria number and endotoxin level at the outlet were also lower in the dialysis machines with CDDS system than in the conventional dialysis machines (t=9.154 and 5.490 respectively;P<0.001). The incidence of water, circuit and other faults were lower in the dialysis machines with CDDS system than in the conventional dialysis machines (t=9.147, P=0.010). Conclusion CDDS system can improve the cleanliness of dialysate and reduce the failure rate of dialysis machines during clinical application.
作者
赵小淋
任琴琴
朱晗玉
马志芳
ZHAO Xiao-lin;REN Qin-qin;ZHU Han-yu;MA Zhi-fang(Department of Nephrology,First Medical Center of PLA General Hospital,Beijing 100853,China)
出处
《中国血液净化》
CSCD
2019年第11期801-804,共4页
Chinese Journal of Blood Purification
基金
国家自然科学基金(61971441):基于多模态深度学习的糖尿病肾病诊断方法研究
国家自然科学基金(61671479):原发性IgA肾病尿蛋白质组学数据库及无创诊断模型的建立
国家重点研发项目(2016YFC1305500):2型糖尿病肾病表观遗传改变及其调控机制研究