背景:在一些研究中,腹膜溶质通过腹膜的转移率(PSTR)与死亡风险增加相关.在文献中已经观察到,溶质通过腹膜快速扩散(高/快速转移)的那些患者以及可能具有以腹膜平衡测试(PET)为特征的高平均转移的那些患者与具有慢转移速率的那些患者相比具有更高的死亡率。然而,一些作者没有记录这一事实。在本研究中,我们希望使用竞争风险模型评估2007-2017年间RTS哥伦比亚腹膜透析事件人群的腹膜转移特征与该技术的死亡率和生存率之间的(病因)关系.
方法:一项回顾性队列研究于2007年至2017年期间在哥伦比亚RTS进行。总的来说,有8170名18岁以上的患者,从治疗开始到180天之间进行腹膜平衡测试(PET)。人口统计,临床,和实验室变量进行了评估。使用竞争风险模型(Royston-Lambert描述的特定原因比例风险模型)分析了治疗开始时腹膜溶质转移速率的类型与总死亡率和技术生存率之间的(病因)关系。
结果:根据PET结果将患者分为四类:慢/低转移(16.0%),低平均值(35.4%),高平均水平(32.9%),和高/快速转移(15.7%)。随访期间,中位数为730天,3025例(37.02%)患者死亡,1079例(13.2%)转移至血液透析,661例(8.1%)移植。在对竞争风险的分析中,根据年龄调整,性别,DM的存在,HTA,身体质量指数,残差函数,白蛋白,血红蛋白,磷,以及治疗开始时PD的模式,我们发现,与低/慢转移率相比,高/快转移的病因特异性HR(HRce)为1.13(95%CI0.98-1.30)p=0.078,高平均1.08(95%CI0.96-1.22)p=0.195,低平均1.09(95%CI0.96-1.22)p=0.156.为了技术生存,高/快速转移的原因特异性HR为1.22(95%CI0.98-1.52)p=0.66,高平均HR为1.10(95%CI0.91-1.33)p=0.296,低平均HR为1.03(95%CI0.85-1.24)p=0.733,根据年龄调整,性别,DM,HTA,BMI,残余肾功能,白蛋白,磷,血红蛋白,和治疗开始时的PD模式。非显著差异。
结论:在使用竞争风险模型评估腹膜溶质转移率类型与该技术的总死亡率和生存率之间的病因关系时,我们发现,根据Twardowski在腹膜透析治疗开始时评估的分类,腹膜转移的特征与校正模型中的总死亡率或技术生存率之间没有病因学关系.然后将从预后模型进行分析,目的是使用风险子分布模型(Fine&Gray)预测该技术的死亡率和生存率。
BACKGROUND: In some studies, the peritoneal solute transfer rate (PSTR) through the peritoneal membrane has been related to an increased risk of mortality. It has been observed in the literature that those patients with rapid diffusion of solutes through the peritoneal membrane (high/fast transfer) and probably those with high average transfer characterized by the Peritoneal Equilibrium Test (PET) are associated with higher mortality compared to those patients who have a slow transfer rate. However, some authors have not documented this fact. In the present study, we want to evaluate the (etiological) relationship between the characteristics of peritoneal membrane transfer and mortality and survival of the technique in an incident population on peritoneal dialysis in RTS Colombia during the years 2007-2017 using a competing risk model.
METHODS: A retrospective cohort study was carried out at RTS Colombia in the period between 2007 and 2017. In total, there were 8170 incident patients older than 18 years, who had a Peritoneal Equilibration Test (PET) between 28 and 180 days from the start of therapy. Demographic, clinical, and laboratory variables were evaluated. The (etiological) relationship between the type of peritoneal solute transfer rate at the start of therapy and overall mortality and technique survival were analyzed using a competing risk model (cause-specific proportional hazard model described by Royston-Lambert).
RESULTS: Patients were classified into four categories based on the PET result: Slow/Low transfer (16.0%), low average (35.4%), high average (32.9%), and High/Fast transfer (15.7%). During follow-up, with a median of 730 days, 3025 (37.02%) patients died, 1079 (13.2%) were transferred to hemodialysis and 661 (8.1%) were transplanted. In the analysis of competing risks, adjusted for age, sex, presence of DM, HTA, body mass index, residual function, albumin, hemoglobin, phosphorus, and modality of PD at the start of therapy, we found cause-specific HR (HRce) for high/fast transfer was 1.13 (95% CI 0.98-1.30) p = 0.078, high average 1.08 (95% CI 0.96-1.22) p = 0.195, low average 1.09 (95% CI 0.96-1.22) p = 0.156 compared to the low/slow transfer rate. For technique survival, cause-specific HR for high/rapid transfer of 1.22 (95% CI 0.98-1.52) p = 0.66, high average HR was 1.10 (95% CI 0.91-1.33) p = 0.296, low average HR of 1.03 (95% CI 0.85-1.24) p = 0.733 compared with the low/slow transfer rate, adjusted for age, sex, DM, HTA, BMI, residual renal function, albumin, phosphorus, hemoglobin, and PD modality at start of therapy. Non-significant differences.
CONCLUSIONS: When evaluating the etiological relationship between the type of peritoneal solute transfer rate and overall mortality and survival of the technique using a competing risk model, we found no etiological relationship between the characteristics of peritoneal membrane transfer according to the classification given by Twardowski assessed at the start of peritoneal dialysis therapy and overall mortality or technique survival in adjusted models. The analysis will then be made from the prognostic model with the purpose of predicting the risk of mortality and survival of the technique using the risk subdistribution model (Fine & Gray).