关键词: 血糖变异性参数, 痛性糖尿病周围神经病变, 心血管事件

Abstract:

Objective To investigate the relationship between fasting blood glucose variability parameters and painful diabetic peripheral neuropathy（PDPN）. Methods In this study,135 patients with type 2 diabetes mellitus（T2DM）and diabetic peripheral neuropathy（DPN）,including 58 patients with PDPN and 77 patients with non-painful diabetic peripheral neuropathy（NPDPN） group,63 T2DM patients and 42 healthy subjects（healthy control group）were enrolled. The general information of all subjects was collected. And glycosylated hemoglobin（HbA1c）,fasting blood glucose（FPG）,2 h postprandial blood glucose（2 h PG）,fasting insulin（FINS）,blood lipids [triglycerides（TG）,total cholesterol（TC）,high-density lipoprotein cholesterol（HDL-C）,low-density lipoprotein cholesterol（LDL-C）],brain-derived neurotrophic factor（BDNF）,high mobility group box B1（HMGB1）,blood glucose variability parameters [ within-day largest amplitude of glycemic excursion（LAGE）,mean blood glucose（MBG）throughout the day,standard deviation of blood glucose（SDBG）throughout the day,coefficient of variation of fasting blood glucose（FBG-CV）],as well as nerve conduction velocity [motor nerve conduction velocity of median nerve（MMCV）,motor nerve conduction velocity of common peroneal nerve（PMCV）,sensory nerve conduction velocity of median nerve（MSCV）,and sensory nerve conduction velocity of common peroneal nerve（PSCV）] were detected. Receiver operating characteristic（ROC）curve was used for evaluating the role of fasting blood glucose variability for the diagnosis of PDPN. Unconditional Logistic regression analysis was used to evaluate the influence factors of PDPN. The risk of cardiovascular disease and disability in patients with DPN was assessed by Kaplan-Meier curve. Spearman correlation analysis was used to evaluate the correlation between various indicators. Results Compared with healthy control group,There were significant differences in terms of body mass index（BMI）,diabetes mellitus course,FBG,2 h PG,TG,HDL-C,HbA1c,BDNF,HMGB1,MMCV,PMCV,MSCV and PSCV between healthy control group and PDPN group,between healthy control group and NDPDN group, between healthy control group and T2DM group（P<0.05,P<0.01）. FBG,TG,HbA1c,BDNF,HMGB1 and PSCV in PDNP group had statistical significance compared with those in NPDPN and T2DM groups（P<0.05,P<0.01）. ROC curve analysis showed that the area under curve（AUC） of LAGE,MBG,SDBG and FPG-CV was 0.748,0.727,0.785 and 0.837,respectively. The efficiency of FBG-CV in diagnosis of PDPN was better than those of LAGE,MBG and SDBG. Spearman correlation analysis showed that LAGE, MBG, SDBG and FBG-CV were significantly correlated with BDNF and PMCV（P<0.05）. Unconditional Logistic regression analysis showed that LAGE,MBG,SDBG and FBG-CV were risk factors for PDPN. The cumulative incidence of cardiovascular events in PDPN group was significantly higher than that in NPDPN group（P=0.017）. The cut-off value of FBG-CV for the diagnosis of PDPN was 30.00%. The cumulative incidence of cardiovascular events in patient with FBG-CV≥30.00% was significantly higher than that in patients with FBG-CV<30.00%（P=0.013）. Conclusions Fasting blood glucose variability parameters may be involved in PDPN. It is an independent risk factor for long-term cardiovascular events in PDPN patients.

Key words: Fasting blood glucose variability parameters, Painful diabetic peripheral neuropathy, Cardiovascular events