Survey of Effective Factors in the Event of Neuropathy in Type 2 Diabetic Patients

Introduction: Diabetic neuropathy is a common and sever complication of diabetes that its progression can lead to disability and even amputation in diabetic patients. The aim of this study was to determine the effective factors in the event of neuropathy and to assess the cumulative incidence of neuropathy in patients with type 2 diabetes. Methods: In this cohort study, all patients with type 2 diabetes who were registered at Fereydunshahr Diabetes Clinic, Isfahan, Iran, were selected by census method. They were followed up for diagnosis of neuropathy since 2006 until March 2016. To investigate the quantitative and qualitative effective factors in the event of neuropathy, one-sample t-test and chi-square test, respectively, were used. And for modeling of effective factors in the event of neuropathy, logistic regression was used. All statistics were analyzed by R software (version 3.2.3) and P values less than 0.05 were considered significant. Results: At the end of 10-year follow-up, cumulative incidence and prevalence of neuropathy were estimated 31% and 41.6%, respectively. After removal of confounders in the final model, variables such as age, ethnicity, family history of diabetes, duration of diabetes, FBS and HDL levels were identified as effective factors in the event of neuropathy (P<0.05). Conclusion: Low levels of HDL and poor control of FBS level are modifiable risk factors for diabetic neuropathy. But non-modifiable risk factors include Persian ethnicity, family history of diabetes, age and increase of diabetes duration. For this reason, in order to increase the HDL level and to decrease FBS level, education is recommended particularly in elderly patients with a family history of diabetes

Survey of Effective Factors in the Event of Neuropathy in Type 2 Diabetic Patients

Introduction: Diabetic neuropathy is a common and sever complication of diabetes that its progression can lead to disability and even amputation in diabetic patients. The aim of this study was to determine the effective factors in the event of neuropathy and to assess the cumulative incidence of neuropathy in patients with type 2 diabetes. Methods: In this cohort study, all patients with type 2 diabetes who were registered at Fereydunshahr Diabetes Clinic, Isfahan, Iran, were selected by census method. They were followed up for diagnosis of neuropathy since 2006 until March 2016. To investigate the quantitative and qualitative effective factors in the event of neuropathy, one-sample t-test and chi-square test, respectively, were used. And for modeling of effective factors in the event of neuropathy, logistic regression was used. All statistics were analyzed by R software (version 3.2.3) and P values less than 0.05 were considered significant. Results: At the end of 10-year follow-up, cumulative incidence and prevalence of neuropathy were estimated 31% and 41.6%, respectively. After removal of confounders in the final model, variables such as age, ethnicity, family history of diabetes, duration of diabetes, FBS and HDL levels were identified as effective factors in the event of neuropathy (P<0.05). Conclusion: Low levels of HDL and poor control of FBS level are modifiable risk factors for diabetic neuropathy. But non-modifiable risk factors include Persian ethnicity, family history of diabetes, age and increase of diabetes duration. For this reason, in order to increase the HDL level and to decrease FBS level, education is recommended particularly in elderly patients with a family history of diabetes

Comparing of cox model and parametric models in analysis of effective factors on event time of neuropathy in patients with type 2 diabetes

Background: Cox proportional hazard model is the most common method for analyzing the effects of several variables on survival time. However, under certain circumstances, parametric models give more precise estimates to analyze survival data than Cox. The purpose of this study was to investigate the comparative performance of Cox and parametric models in a survival analysis of factors affecting the event time of neuropathy in patients with type 2 diabetes. Materials and Methods: This study included 371 patients with type 2 diabetes without neuropathy who were registered at Fereydunshahr diabetes clinic. Subjects were followed up for the development of neuropathy between 2006 to March 2016. To investigate the factors influencing the event time of neuropathy, significant variables in univariate model (P < 0.20) were entered into the multivariate Cox and parametric models (P < 0.05). In addition, Akaike information criterion (AIC) and area under ROC curves were used to evaluate the relative goodness of fitted model and the efficiency of each procedure, respectively. Statistical computing was performed using R software version 3.2.3 (UNIX platforms, Windows and MacOS). Results: Using Kaplan–Meier, survival time of neuropathy was computed 76.6 ± 5 months after initial diagnosis of diabetes. After multivariate analysis of Cox and parametric models, ethnicity, high-density lipoprotein and family history of diabetes were identified as predictors of event time of neuropathy (P < 0.05). Conclusion: According to AIC, “log-normal” model with the lowest Akaike's was the best-fitted model among Cox and parametric models. According to the results of comparison of survival receiver operating characteristics curves, log-normal model was considered as the most efficient and fitted model