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肾动脉阻力指数在糖尿病肾病鉴别诊断中的潜在作用及预测模型构建

Potential role of renal artery resistance index in differential diagnosis of diabetic nephropathy and construction of a predictive model

    摘要
  • 摘要:
    目的 分析肾动脉阻力指数(RI)在糖尿病肾病(DN)鉴别诊断中的潜在作用并构建列线图预测模型。
    方法 回顾性纳入312例2型糖尿病患者作为研究对象, 根据肾脏穿刺活检病理结果分为DN组患者187例和非糖尿病肾病(NDN)组患者125例。比较2组患者临床资料, 采用多因素Logistic回归分析筛选DN的危险因素并建立列线图预测模型, 绘制受试者工作特征(ROC)曲线, 比较预测模型与RI诊断DN的曲线下面积(AUC)。
    结果 与NDN组患者相比, DN组患者收缩压、空腹血糖、血肌酐、尿素氮和RI升高, 病程≥ 60个月、糖化血红蛋白(HbA1c) ≥ 7.0%和合并糖尿病视网膜病变(DR)者占比增高, 而血红蛋白和估算肾小球滤过率(eGFR)降低, 差异均有统计学意义(P < 0.05)。多因素Logistic回归分析显示, 病程≥ 60个月(OR=3.526, 95%CI: 2.425~5.023, P < 0.001)、DR(OR=5.528, 95%CI: 4.426~6.325, P < 0.001)、HbA1c ≥ 7.0%(OR=1.958, 95%CI: 1.235~3.526, P < 0.001)和RI ≥ 0.65(OR=4.025, 95%CI: 3.265~5.524, P < 0.001)均为DN的独立危险因素。ROC曲线显示, 包含RI的列线图预测模型诊断DN的AUC为0.895, 分别大于RI、不包含RI的列线图预测模型的AUC(0.701、0.799), 差异有统计学意义(P < 0.001)。Spearman相关性分析显示, RI与收缩压、病程、血肌酐、尿素氮呈正相关(P < 0.05), 与eGFR呈负相关(P < 0.05)。
    结论 基于超声无创定量检测的RI在DN的鉴别诊断中具有重要的应用潜力, RI联合病程、DR、HbA1c构建的列线图预测模型对DN具有较高的诊断效能。

     

    Abstract:
    Objective To analyze the potential role of renal artery resistance index (RI) for the differential diagnosis of diabetic nephropathy (DN), and construct a quantitative predictive model to guide clinical application.
    Methods A total of 312 patients with type 2 diabetes were retrospectively included, including DN group(187 patients with DN) and non-diabetic nephropathy (NDN) group(125 patients) according to renalpuncture and pathology results. The clinical data between the two groups were compared. Multivariate Logistic regression analysis was used to screen the risk factors of DN and the predictive model was established. Receiver operator characteristic (ROC) curve was drawn, and the areas under the curve (AUCs) of the model and RI for DN diagnosis were compared.
    Results Compared with patients in the NDN group, systolicblood pressure, fasting blood glucose, serum creatinine, urea nitrogen and RI of patients in the DN group were significantly higher, the course of disease ≥ 60 months, glycosylated hemoglobin (HbA1c) ≥ 7.0% and ratio of patients complicating diabetes retinopathy (DR) were significantly increased, while hemoglobin and estimated glomerular filtration rate (EGFR) were significantly reduced (P < 0.05). Multivariate Logistic regression analysis showed that the course of disease ≥ 60 months (OR=3.526; 95%CI, 2.425 to 5.023; P < 0.001), DR (OR=5.528; 95%CI, 4.426 to 6.325; P < 0.001), HbA1c ≥ 7.0% (OR=1.958; 95%CI, 1.235 to 3.526; P < 0.001) and RI ≥ 0.65 (OR=4.025; 95%CI, 3.265 to 5.524; P < 0.001) were the independent risk factors to DN (P < 0.05). ROC curve showed that AUC of nomograph model containing RI for DN diagnosis was significantly higher than RI alone and the nomograph without RI(0.701, 0.799; P < 0.001). Spearman correlation analysis showed that RI was positively correlated with systolic blood pressure, course of disease, blood creatinine and urea nitrogen, but negatively correlated with eGFR (P < 0.05).
    Conclusion Noninvasive quantitative detection of RI by ultrasound has important potential for the differential diagnosis of DN. The nomograph model combined with disease course, DR, HbA1c and RI has high efficiency in the diagnosis of DN.

     

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