Is renal impairment predictor of future diabetic peripheral neuropathy? A 6-year follow-up cohort study

The relationship between renal impairment and diabetic peripheral neuropathy (DPN) remains inconclusive. We aim to investigate the risk factors for the occurrence of DPN in Taiwanese adults with type 2 diabetes mellitus (T2DM) and focus on renal impairment. A hospital-based cohort study was conducted from 2013 to 2019 and 552 Taiwanese people who had T2DM without DPN at baseline were enrolled. DPN was diagnosed using the Michigan Neuropathy Screening Instrument. Potential risk factors were recorded, including patient’s sociodemographic factors, current medication usage and biochemical markers. As of 2019, 73 developed DPN and 479 had no DPN. The cumulative incidence during the 6-year period was 13.22%. A multivariate logistic regression analysis revealed that lower estimated glomerular ltration rate (eGFR) (odds ratio [OR] 0.98, p=0.008), higher serum creatinine concentration in people under the age of 65 (OR 5.25, p=0.013), advanced age (OR 1.06, p=0.001), increased body weight (OR 1.04, p=0.018), duration of DM (OR 1.05, p=0.036) and male gender (OR 3.69, p=0.011) were signicantly associated with future DPN. In conclusion, this is the rst large scaled cohort study to investigate risk factors for DPN in Taiwanese. Lower eGFR, higher serum creatinine concentration, particularly in people under the age of 65, advanced age, increased body weight, duration of DM and male gender are predictors of future DPN. Our study not only conrms the association between renal impairment and future DPN but also provides a commonly available assessment to predict the future DPN.


Introduction
The global burden of diabetes mellitus (DM) has increased enormously in recent decades and will continue to soar in the next few decades. In fact, the global incidence of diabetes has increased by 102.9% from 11.3 million in 1990 to 22.9 million in 2017. Consequently, the prevalence of the complications resulting from type 2 diabetes (T2DM) is likely to rise [1]. DPN is the most common complication, and its lifetime prevalence is up to 50% in adults with T2DM [2]. DPN is associated with a wide range of clinical manifestations, of which distal sensory neuropathy is predominant. This manifestation contributes to numerous disabling morbidities, such as diabetic foot ulceration, impaired balance, and distressing neuropathic pain, which are often di cult to treat. Furthermore, DPN is the most common cause of non-traumatic lower-limb amputations in most highincome countries [3]. The current study focuses on distal and symmetric polyenruopathy.
Unfortunately, the early manifestations of this insidious disease are often missed until the disease is well established, at which point it seems to be irreversible [2]. There is a lack of treatments that target the underlying nerve damage other than serum glucose control, which shows limited e cacy in T2DM [4].
Thus, prevention is the critical component of diabetes care to reduce the burden of care. Previous studies have reported risk factors that include older age, hyperglycemia, longer diabetes duration, metabolic syndrome and dyslipidemia [5,6]. For dyslipidemia, increased low-density lipoprotein (LDL) [7] and triglycerides (TG) [8] have been identi ed as predictors of diabetic sensory neuropathy in type 1 DM. In contrast, it remained inconclusive in T2DM [10,11] and there were some studies reported high level of TG and low level of high-density lipoprotein (HDL) as risk factors [3,9].
Apart from these, it attracts much more attention that whether renal impairment was a predictor of future diabetic peripheral neuropathy. Con icting data have been reported between renal impairment and future DPN [12,13]. As far as we know, recent studies have not described a de nite list of risk factors of DPN, especially renal impairment, which may be due to the majority of studies having cross-sectional designs.
Longitudinal studies are the key tools to establish predictors of the development of DPN. Therefore, the objective of the current cohort study was to investigate the predictors for future DPN in Taiwanese adults with T2DM and focus on impaired renal function. Look forward to help improve therapeutic strategies in clinical practice.

Methods
This study was approved by Institutional Review Board (No. CG18082B-1) at Taichung Veterans General Hospital. All methods and experiments were carried out in accordance with relevant guidelines and hospital regulations. Informed consent was obtained from all subjects and their informants before study participation.

Study Design and Participants
This is a hospital-based, prospective, observational, cohort study. Between January 2013 and October 2013, patients over 18 years old with prevalent or newly diagnosed T2DM were eligible for inclusion. The diagnosis of T2DM were based on the criteria of American Diabetes Association (ADA). Data were obtained from patient's medical records, laboratory examinations, questionnaires and anthropometric measurements at the time of enrollment. Exclusion criteria were as follows: patients having type 1 DM or gestational diabetes, patients had DPN at baseline and whose did not complete the questionnaires or blood sample test at baseline or during the following 6 years. Finally, 552 participants were enrolled in our study.
Participants have been followed observationally via clinical follow-up examination and questionnaires.
The blood sample test was performed at least once a year. Our study consequently carried out to 2019 -6 years after the trial baseline.
Each of the participants was diagnosed by endocrinologists in the outpatient units at a tertiary medical center in middle Taiwan, which serves approximately 6600 outpatients and 1400 inpatients per day and mainly Han-Chinese population. Before drawn for analysis, the patients' information was anonymized by computer system, and the researchers were blinded to these data.

Biochemical data
Laboratory examination were administrated during endocrinological follow-up. Blood samples were obtained in the morning after an overnight fasting period from the antecubital vein. Fasting plasma glucose (FPG; using standard enzymatic methods), glycated hemoglobin (HbA1c; using high-performance liquid chromatography), serum creatinine concentration and plasma lipid pro les (using standard enzymatic methods), including total cholesterol (TC), HDL, LDL, and TG. For lipid pro le, we de ned the

Assessment of diabetic peripheral neuropathy
All of the included patients received assessment of DPN by the same trained and certi cated caremanagement nurse to minimize the inter-rater reliability. DPN was evaluated based on the second component of MNSI. Physical appearance of feet, ulceration, ankle deep tendon re exes, and the perception of light touch (using Semmes-Weinstein 5.07 10-g mono lament) and distal vibration (using 128-Hz tuning fork) were investigated. As previous validated studies in adults [15], individuals whose MNSI examination (MNSIE) score > 2 were diagnosed with DPN.

Assessment of renal function
We evaluated participants' baseline renal function with serum creatinine concentration and eGFR in 2013. The eGFR was estimated by MDRD equation which contains elements as serum creatinine, age and gender (a constant in the equation). Because the relationship between serum creatinine, age and eGFR is hyperbolic, we establish a model that do not adjust the serum creatinine, age and gender for eGFR in multivariate logistic regression analyses (Table 3) to statistic the interference between baseline eGFR and the occurrence of DPN.
Besides, it is well-established that serum creatinine had multiple limitations to represent the true renal function and age is an important factor among these [16]. Furthermore, renal function declines with advancing age. Recent research reported that there were high percentage (14.4%~17% varied by gender) of people aged 65 and above had a serum creatinine concentration above the laboratory reported upper reference limit of normal [17]. Thus we strati ed the serum creatinine concentration by age group into age≧65 and age<65. Each groups were carried out the multivariate logistic regression analysis (Table 4).

Statistical Methods
Descriptive statistics were presented as the mean values ± standard deviation (SD) and as the numbers with percentages. We used Fisher's exact test or chi-squared test to analyze categorical variables, while the analyses of continuous variables were conducted using ANOVA tests.
Multivariate logistic regression analyses were carried out to explore the effect of each identi ed independent variable on DPN. The multivariate regression models included all the confounders and the variables that had shown a signi cant correlation, and the adjusted odds ratios (OR) with 95% con dence interval (CI) were calculated between the comparison groups. The statistical signi cance level chosen was P value less than 0.05 (P < 0.05), and all tests were two-sided. All the data were analyzed using statistical package SAS version 9.4 for Windows.

Results
We recruited 681 participants who had T2DM at baseline in 2013. Of these, 116 (17%) who had DPN at baseline and 13 non-T2DM patients were excluded. Thus, 552 were deemed to be eligible to be included in the study. The participants' median age was 59.7±10.7 years, and 60.1% were males. The mean duration of diabetes was 15.2±6.9 years, and the mean level of HbA1c was 7.4±1.3%. Table 1 summarizes their sociodemographic factors, diabetes-related factors, biochemical factors, comorbidities, and medication usage.
We de ned the patients who developed DPN during follow-up as the "incident DPN" group (n = 73  Comparison of baseline renal function between patients with or without incident DPN After adjusted for height, weight, SBP, duration of diabetes and HDL-C, we found that higher baseline eGFR (OR 0.98 [95% CI 0,971; 0,996], p=0.008) was signi cantly associated with a lower risk of DPN (Table 3). In addition, the strati ed analysis also revealed that a higher baseline serum creatinine  Table 4).

Discussion
To our knowledge, this is the rst large scaled, observational, longitudinal cohort study to investigate risk factors for DPN in a Taiwanese adult population. Using MNSIE for the diagnosis of DPN, we found that participants without DPN at baseline had a 13% cumulative incidence of DPN over the 6 years of followup (corresponding with an annual incidence of 2.204%) in a population where the duration of DM was as long as 15.2±6.9 years. The incidence of DPN in our study is comparable with that of a previous longitudinal, large-scale, nationwide, population-based study in Taiwan (n = 37375, annual incidence of 3.2%) [18] However, it was lower than that reported Western populations [19,20]. This discrepancy might be due to differences in the sample size, ethnicity of the study population (the prevalence of DPN is about 32.1% in the UK [21] and about 23.5% in Taiwan [22]), diagnostic criteria, and measurement instruments.
Apart from these, one of the crucial factors is the baseline duration of DM. One study well established that the prevalence of diabetic neuropathy increased from 8-42% in patients with T2DM when patients were monitored for 10 years [23]. Compared with the previous cohort study, patients had newly diagnosed DM with a cumulative incidence of 10% over the 13-year follow-up period and an annual incidence of 0.7% [9]. The relatively high cumulative incidence over our 6-year follow-up period might be attributable to the longer baseline duration of DM.

The association between renal function and incident DPN
In our study, baseline renal function was found to be an independent risk factor for DPN, including baseline eGFR (Table 3) and baseline serum creatinine concentration ( To date, the mechanisms of neurotoxicity in T2DM patients with renal impairment remains unclear, but they have been demonstrated in some studies [24,25]. Experimental evidence indicates that alterations in membrane excitability is induced by inhibition of the axonal Na + /K + pump, which abolishes the direct contribution of the hyperpolarizing pump current to the membrane potential, leading to an accumulation of extracellular K + that causes depolarization [26]. Disruption of these various ionic gradients may affect the Na + /Ca 2+ exchanger, leading to increased levels of intracellular Ca 2+ and axonal loss [27].
In addition, it is clear from previous research that impaired renal function results in microvascular endothelial dysfunction, even in the early stages of chronic kidney disease. Endothelial injury is caused by various factors, including in ammation, hypertension, diabetes-associated factors, and a uremic milieu [25,28]. Eventually, it leads to neuropathy due to impaired nerve blood ow, epineurial arteriovenous shunting, and reduced nerve oxygen tension [29].
Other studies examining nephropathy as a risk factor for DPN have been inconclusive [13]. However, it is suggested that the selection of disease markers for renal impairment may be important (for example, eGFR or creatinine), and further investigation is needed. Based on the current study, we recommend that increased serum creatinine concentration or lower baseline eGFR be used as an indicator to enhance the awareness of incident DPN.

Other risk factors of future DPN
After adjustment for potential confounding factors, we also found that a higher risk of DPN was linked with increased age, body weight, duration of DM, and male gender. Our ndings are consistent with most previous reports from cross-sectional studies and a meta-analysis of patients with T2DM in Western, Korean, and Taiwanese populations [5,6,30]. Concerning sugar control, previous studies indicated hyperglycemia as a risk factor for the development of DPN [5,8], but we found no association between baseline HbA1c levels and incident DPN. This is likely explained by low levels of HbA1c at baseline (7.3±1.2% in the no-DPN group and 7.6±1.7% in the incident-DPN group) compared with the levels usually found in previous studies. These data possibly re ect better medication adherence among Taiwanese DM patients [31] compared with worldwide [32]. Our study also showed equally high numbers of hypoglycemic medication prescriptions in both groups.
In the current study, increased weight was independent risk factor of incident DPN, but no statistically signi cant associations with incident DPN were found for BMI and waist circumference. This is inconsistent with previous studies [5,9,10] but previous studies have not identi ed a consistent list of risk factors related to markers of obesity [10,12]. A possible explanation is that previous investigators did not adequately correct the reference cut-off values and the units for tests. This is not to say that markers of obesity may not be risk factors for DPN, but corrections must rst be made for these characteristics in the cut-off values and the units [12].
In terms of dyslipidemia, we found that serum lipid components had no statistically signi cant associations with the risk of DPN in T2DM. As stated above, these ndings were consisted with some previous studies [34,35]. In fact, accumulated evidence has shown a correlation between DPN and serum lipid pro les but has shown inconsistent results [33]. The possible underlying mechanisms of dyslipidemia leading to DPN are complex which may include insulin resistance, chronic in ammatory status, oxidative stress induced by elevated LDL, and demyelination [33]. Nevertheless, these mechanisms are mainly reported in preclinical studies [36][37][38]. It is well established that DPN is a multifactorial disease and our ndings indicate that lipid metabolism may play a minor role in its pathogenesis.
The major strengths of the current study are its large sample size in a cohort design, the unselected nature of participants, standardized data collection procedures, and inclusion of several potential risk factors at baseline. But despite these strengths, there are still plenty of limitations. First, our results might not apply to treatment-naïve cohorts of early-stage T2DM. A high proportion of medication prescription might have affected the cardiovascular risk factors. Furthermore, we did not use con rmatory tests such as nerve conduction studies or skin biopsy for DPN diagnosis. However, the diagnosis of DPN is principally a clinical one according to ADA recommendations, and the MNSIE is a sensitive, speci c, validated clinical screening tool. Lastly, we included participants from a single hospital, which might limit the generalizability of the results.

Conclusion
Lower eGFR and higher serum creatinine concentration, particularly in people under the age of 65, are predictors of future DPN in Taiwanese people with T2DM. Other risk factors included advanced age, increased body weight, duration of DM, and male gender which were compatible with most previous studies. These ndings not only con rm the association between renal impairment and future DPN but also provides a commonly available assessment to predict the future DPN. Early detection of risk factors and control of the modi able factors could enrich therapeutic strategies in clinical practice. Thus, we suggest that the therapeutic strategy for diabetes should provide early management of renal impairment and prevent overweight. Also, these ndings could provide useful information for researchers exploring the underlying mechanisms of DPN and inspire disease-modifying therapies in the future.