RBP作为高血压预测因子的可信性分析
Reliability Analysis of RBP as a Predictor of Hypertension

目的：探讨视黄醇结合蛋白(Retinol binding protein, RBP)作为高血压预测因子的可信性。方法：回顾性分析在2020年7月1日至2020年9月31日期间内就诊于北华大学附属医院的330名患者。按照是否患有高血压疾病将上述收录患者分为高血压组和无高血压组，收集所有患者的一般情况资料(姓名、病案号、年龄、身高、体重、心率、收缩压、舒张压)；个人史(吸烟史、饮酒史)；既往史(高血压、糖尿病、冠心病)；血脂检查(HDL-C、LDL-C、ApoB、ApoA1、TG、TC)；RBP。数据分析应用SPSS 23.0软件，进行相关统计分析。计量资料：应用两独立样本t检验，结果用均数 ± 标准差来表示。计数资料：采用卡方检验，应用百分数来表示。线性回归模型分别分析了RBP与收缩压(SBP)、舒张压(DBP)、体重指数(BMI)、年龄(Age)、空腹血糖(FBG)、甘油三酯(TG)间的线性关系。采用受试者工作特征(Receiver operating characteristic curve, ROC)曲线来衡量RBP作为高血压预测因子的诊断价值。结果：两独立样本t检验、卡方检验分析显示：两组在Age、BMI、SBP、DBP、FBG、RBP及TG间差异具有统计学意义(P < 0.05)。线性回归模型分析显示RBP与SBP、DBP、FBG、TG呈正相关(r = 0.125、1.171，0.024，0.332均P < 0.05)。受试者工作特征(Receiver operating characteristic curve, ROC)曲线结果显示当RBP指数取截值为27.780时，ROC曲线下面积最大(0.606)，其特异度为78.4%。结论：将RBP作为高血压的预测因子具有可信性。
Objective: To explore the confidence of retinol binding protein (Retinol binding protein, RBP) as a predictor of hypertension. Methods: A retrospective analysis included 330 patients presenting to the North China University Affiliated Hospital between July 1, 2020 and September 31, 2020. The patients were divided into hypertension and no hypertension, and collected general condition data of all patients (name, record number, age, height, weight, heart rate, systolic BP, diastolic pressure); personal history (smoking history, drinking history); past history (hypertension, diabetes, coronary heart disease); blood lipid examination (HDL-C, LDL-C, ApoB, ApoA 1, TG, TC); RBP. Data analysis applied SPSS 23.0 software for related statistical analysis. Metric Data: Two independent samples t-tests were applied, and the results were expressed as mean ± standard deviation. Count Data: Chi-square test with percentage applied. The linear relationship between RBP and systolic blood pressure (SBP), diastolic blood pressure (DBP), body mass index (BMI), age (Age), fasting blood glucose (FBG), and triglycerides (TG) was analyzed separately. A receiver operating characteristic (Receiver operating characteristic curve, ROC) curve was used to measure the diagnostic value of RBP as a predictor of hypertension. Results: The t-test and chi-square test showed significant differences between Age, BMI, SBP, DBP, DBP, FBG, RBP and TG (P < 0.05). Linear regression model analysis showed a positive correlation between RBP and SBP, DBP, FBG and TG (r = 0.125, 1.171, 0.024, 0.332 all P < 0.05). The results of the receiver operating characteristic (Receiver operating characteristic curve, ROC) curve showed that when the RBP index is 27.780, the area under the ROC curve is the largest (0.606), with a specificity of 78.4%.