RESUMO
AIM: To investigate the correlation between serum uric acid (SUA) and diabetic peripheral neuropathy (DPN) in type 2 diabetes mellitus (T2DM) patients. METHODS: Two hundred T2DM patients were divided into four groups at the cut-off points of 5, 7, and 9mg/dL of SUA levels. Nerve conduction studies (NCS), Semmes-Weinstein monofilament testing (SWMT), and vibration perception threshold (VPT) tests were performed on these patients. RESULTS: Significant differences in motor/sensory nerve amplitude and conduction velocity (CV) parameters among different SUA level groups were observed (all P<0.05). SUA levels were negatively correlated with the means of motor/sensory nerve amplitude and CV (all P<0.05). Duration of T2DM >10years, SUA >9mg/dL and total cholesterol (TC) >5.2mmol/L were found to be significantly associated with DPN (all P<0.05). Receiver-operating characteristic (ROC) analysis revealed that the cut-off points of T2DM duration combined with SUA and TC were 9years, 7.8mg/dL, and 4.97mmol/L, respectively (AUC=0.65; 95% CI: 0.53-0.77; sensitivity, 70.6%; specificity, 65.2%, P=0.009). CONCLUSION: There is a significant association between elevated SUA levels and DPN, and T2DM duration, SUA, and TC may be valuable indicators to predict the occurrence of DPN in T2DM patients.
Assuntos
Diabetes Mellitus Tipo 2/sangue , Diabetes Mellitus Tipo 2/complicações , Neuropatias Diabéticas/etiologia , Ácido Úrico/sangue , Adulto , Idoso , Colesterol/sangue , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Curva ROCRESUMO
This study aimed to identify the effect of CYP2C9-VKORC1 interaction on warfarin dosage requirement and its predictive algorithm by investigating four populations. Generalized linear model was used to evaluate the relationship between the interaction and warfarin stable dosage (WSD), whereas multiple linear regression analysis was applied to construct the WSD predictive algorithm. To evaluate the effect of CYP2C9-VKORC1 interaction on the predictive algorithms, we compared the algorithms with and without the interaction. The interaction was significantly associated with WSD in the Chinese and White cohorts (P values < 0.05). In the algorithms that considered the interaction, the predictive success rates improved by only 0.12% in the Chinese patients and by a maximum of 0.02% in the White patients under four different CYP2C9 classifications. Thus, VKORC1-CYP2C9 interaction can affect WSD. However, the discrepancy between the predictive results obtained using the predictive algorithm with and without CYP2C9-VKORC1 interaction was negligible and can therefore be disregarded.