INSERM 1094 & IRD, University of Limoges, 2, Rue Marcland, 87025, Limoges, France.
INSERM 1094 & IRD, University of Limoges, 2, Rue Marcland, 87025, Limoges, France; Department of Cardiology, Dupuytren 2 University Hospital, 16, Rue B. Descottes, 87042, Limoges, France.
Prim Care Diabetes. 2022 Feb;16(1):196-201. doi: 10.1016/j.pcd.2021.12.014. Epub 2022 Jan 4.
Chronic kidney disease (CKD), defined by a low glomerular filtration rate (GFR), is a predictor of cardiovascular disease in patients with type-2 diabetes (T2D). We aimed to compare four GFR equations in predicting future cardiovascular events in T2D and the presence of subclinical vascular disease.
Four equations were used to estimate GFR in asymptomatic T2D patients consulting our centre for cardiovascular assessment. Follow-up was performed to collect cardiovascular events. Cox proportional hazard ratio (HR) was used to build and compare prediction models, and the incremental value of the addition of GFR with any of the 4 formulas was evaluated. The ability to triage patients with and without CVD events according to GFR were assessed by comparing the receiver operator characteristics (ROC) curves with the 4 models.
Among 829 asymptomatic T2D patients, the CKD prevalence was 20.2% for Modification of Diet in Renal Disease (MDRD), 17.3% for Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI), 20.7% for Lund-Malmö Revised (LMR) and 21.4% for Full Age Spectrum (FAS). All the estimated GFRs were well correlated from one formula to another, with stronger agreement to define CKD (GFR <60 mL/min/1.73 m) between MDRD and CKD-EPI, and between LMR and FAS. The 5-year incidence of cardiovascular events was 8% (n = 63). After adjustment on covariables, CKD was significantly associated with cardiovascular events when defined by MDRD (HR = 2.04; 1.15-3.60) and CKD-EPI (HR = 1.90; 1.05-3.41) but missed statistical significance when using LMR (HR = 1.74; 0.97-3.14) or FAS (HR = 1.71; 0.94-3.14). Only the prediction models including MDRD and CKD-EPI provided a significant incremental information to the predictive model without GFR, but the area under the ROC curves were similar with the 4 models: 0.60 [0.54-0.68] for MDRD, 0.61 [0.49-0.65] for CKD-EPI and 0.62 [0.55-0.69] for LMR and FAS, without any significant difference among formulas.
In asymptomatic T2D patients, MDRD and CKD-EPI may be preferable when more specificity is desired (stronger association between GFR and CVD events), while LMR and FAS appear more sensitive by including a higher number of patients with GFR <60 mL/min/1.73 m.
慢性肾脏病（CKD）定义为肾小球滤过率（GFR）降低，是 2 型糖尿病（T2D）患者心血管疾病的预测因素。我们旨在比较四种 GFR 方程在预测 T2D 患者未来心血管事件和亚临床血管疾病方面的作用。
使用四种方程估算咨询我们中心进行心血管评估的无症状 T2D 患者的 GFR。进行随访以收集心血管事件。使用 Cox 比例风险比（HR）构建和比较预测模型，并评估任何 4 种公式添加 GFR 的增量价值。通过比较 4 种模型的接收者操作特征（ROC）曲线，评估根据 GFR 对有和无 CVD 事件患者进行分诊的能力。
在 829 名无症状 T2D 患者中，根据改良肾脏病饮食研究（MDRD），CKD 患病率为 20.2%，根据慢性肾脏病流行病学合作研究（CKD-EPI）为 17.3%，根据隆德-马尔默修订版（LMR）为 20.7%，根据全年龄谱（FAS）为 21.4%。所有估计的 GFR 之间均具有良好的相关性，MDRD 和 CKD-EPI 之间以及 LMR 和 FAS 之间对定义 CKD（GFR<60mL/min/1.73m）的一致性更强。心血管事件的 5 年发生率为 8%（n=63）。调整协变量后，CKD 与 MDRD（HR=2.04；1.15-3.60）和 CKD-EPI（HR=1.90；1.05-3.41）定义的心血管事件显著相关，但 LMR（HR=1.74；0.97-3.14）或 FAS（HR=1.71；0.94-3.14）定义的 CKD 未达到统计学意义。只有包括 MDRD 和 CKD-EPI 的预测模型为不包括 GFR 的预测模型提供了显著的增量信息，但 ROC 曲线下的面积与 4 种模型相似：MDRD 为 0.60 [0.54-0.68]，CKD-EPI 为 0.61 [0.49-0.65]，LMR 和 FAS 为 0.62 [0.55-0.69]，各公式之间无显著差异。
在无症状 T2D 患者中，当需要更高的特异性（GFR 与 CVD 事件之间更强的关联）时，MDRD 和 CKD-EPI 可能更可取，而 LMR 和 FAS 通过纳入更多 GFR<60mL/min/1.73m 的患者，似乎更敏感。
