伴糖尿病抑郁症患者甘油三酯的预测因素探析

Analysis of predictors of triglycerides in depressive patients with type 2 diabetes

目的探析伴2型糖尿病抑郁症患者基线甘油三酯(TG)的预测因素。方法予94例伴糖尿病抑郁症患者(研究组)和80例同一时期门诊健康体检者(对照组)依次收集一般临床资料、评估汉密尔顿焦虑量表(HAMA)总分和汉密尔顿抑郁量表(24项)(HAMD-24)总分、测定血清TG和空腹血糖(FBG),并将基线TG作为因变量,将两组间初筛可疑的13项研究指标作为自变量进行多重线性回归分析。结果研究组在阳性抑郁症家族史、阳性糖尿病家族史、吸烟、体质指数(BMI)、HAMD-24总分、HAMA总分、基线TG及基线FBG与对照组间的差异有统计学意义(P均<0.05);多重线性回归分析结果表明,糖尿病病程、BMI、HAMA总分、年龄及吸烟对基线TG的影响有统计学意义(P均<0.05),估计影响最大的是糖尿病病程,影响最小的是吸烟。结论糖尿病病程、BMI、HAMA总分、年龄及吸烟能够作为伴2型糖尿病抑郁症患者基线TG水平变异的预测因素;及时进行医学干预,有助于改善患者异常的血清TG水平,进而提高临床疗效和减少心脑血管并发症。

Objective To analysis the predictors of triglyceride(TG) in depressive patients with type 2 diabetes.Methods Total 94 depressive patients with type 2 diabetes(study group)and 80 outpatient health examinees in the same period(control group) were collected general clinical data, evaluated HAMA scores and HAMD-24 scores,determinated serum TG and fasting blood glucose(FBG)in turn,and then did the multiple linear regression analysis with baseline TG as dependent variable and with 13 suspicious study indicators of the initial screening between the two groups as the independent variable.Results The difference in positive family history of depression,positive family history of diabetes mellitus,smoking,body mass index(BMI),HAMD-24 scores, HAMA scores,baseline TG and baseline FBG between study group and control groups was statistically significant(P<0.05).The result of the multiple linear regression analysis show that the effect of duration of diabetes,BMI,HAMA scores,age and smoking on the baseline TG was statistical different(P<0.05).It is estimated that the greatest impact is duration of diabete,and the smallest impact is smoking.Conclusion Duration of diabetes,BMI,HAMA scores,age and smoking can be used as the predictors of the baseline TG in depressive patients with type 2 diabetes.Timely medical intervention can help to improve abnormal serum TG levels of these patients,and then to improve clinical efficacy and reduce cardiovascular and cerbrovascular complications.