Lumos for the long trail: Strategies for clinical diagnosis and severity staging for diabetic polyneuropathy and future directions

Electrophysiological grading scale for polyneuropathy severity

OBJECTIVE

To establish a simple electrophysiological scale for patients with distal symmetric axonal polyneuropathy, in order to promote standardized and informative electrodiagnostic reporting, and understand the complex relationship between electrophysiological and clinical polyneuropathy severity.

METHODS

We included 76 patients with distal symmetric axonal polyneuropathy, from a cohort of 151 patients with polyneuropathy prospectively recruited from November 2016 to May 2017. Patients underwent nerve conduction studies (NCS), were evaluated by the Toronto Clinical Neuropathy Score (TCNS), and additional tests. The number of abnormal NCS parameters was determined, within the range of 0-4, considering low amplitude or conduction velocity in the sural and peroneal nerve.

RESULTS

Higher number of NCS abnormalities was associated with higher TCNS, indicating more severe polyneuropathy. Polyneuropathy severity per the TCNS was most frequently (63%-70%) mild in patients with a low (0-1) number of NCS abnormalities, and most frequently (57%-67%) severe in patients with a high number (3-4) of NCS abnormalities, while patients with an intermediate (2) number of NCS abnormalities showed mainly mild and moderate severity with equal distribution (40%).

CONCLUSIONS

A simple NCS classification system can objectively grade polyneuropathy severity, although significant overlap exists especially at the intermediate range, underscoring the importance of clinical based scoring.

Glycemic variability is associated with sural nerve conduction velocity in outpatients with type 2 diabetes: Usefulness of a new point-of-care device for nerve conduction studies

AIMS/INTRODUCTION

Although several studies have shown the association between continuous glucose monitoring (CGM)-derived glycemic variability (GV) and diabetic peripheral neuropathy, no studies have focused on outpatients or used NC-stat®/DPNCheck™, a new point-of-care device for nerve conduction study (NCS). We investigated the association between CGM-derived GV and NCS using DPNCheck™ in outpatients with type 2 diabetes, and further analyzed the difference in results between patients with and without well-controlled HbA1c levels.

MATERIALS AND METHODS

All outpatients with type 2 diabetes using the CGM device (FreeStyle Libre Pro®) between 2017 and 2022 were investigated. Sural nerve conduction was evaluated by sensory nerve action potential (SNAP) amplitude and sensory conduction velocity (SCV) using DPNCheck™. Associations of CGM-derived GV metrics with SNAP amplitude and SCV were investigated.

RESULTS

In total, 304 outpatients with type 2 diabetes were included. In a linear regression model, most CGM-derived GV metrics except for the mean amplitude of glucose excursion and low blood glucose index were significantly associated with SCV, but not with SNAP amplitude. The significant associations of most CGM-derived GV metrics with SCV remained after adjustment for possible confounding factors, but not after adjustment for glycated hemoglobin (HbA1c). Most CGM-derived GV metrics were significantly associated with SCV after adjustment for HbA1c in patients with a HbA1c ≤ 6.9%, but not in those with a HbA1c ≥ 7.0%.

CONCLUSIONS

In outpatients with type 2 diabetes, multiple CGM-derived GV metrics were significantly associated with SCV obtained by DPNCheck™. GV may have independent impacts on peripheral nerve function, particularly in patients with well-controlled HbA1c levels.

Assessment of the severity of diabetic polyneuropathy aids in predicting the risk of developing diabetic complications in patients with untreated diabetes

This study aimed to determine the efficacy of assessing the severity of diabetic polyneuropathy (DPN) in patients with untreated diabetes. Seventy-two patients with untreated type 2 diabetes who were hospitalized for glycemic control were enrolled and divided into the following two groups: patients who had no prior diagnosis and patients who were unattended or had discontinued treatment. Electrophysiological criteria consistent with Baba's classification were used to diagnose and assess the severity of DPN. The patients were divided into three subgroups: no DPN (stage 0), mild DPN (stage 1), and moderate or more-severe DPN (stages 2-4). Intergroup comparisons were performed for the clinical characteristics and the results of the nerve conduction studies. Twenty-two (30%), 25 (35%), and 25 (35%) patients were categorized into the no DPN, mild DPN, and moderate or more-severe DPN subgroups, respectively. The number of patients who were unattended or had discontinued treatment in the moderate or more-severe DPN subgroup was significantly higher than that in the no DPN subgroup. The patients in the moderate or more-severe DPN subgroup had an increased risk of developing diabetic retinopathy and nephropathy, with odds ratios of 19.5 and 11.0 for advanced stages of retinopathy and nephropathy, respectively. Thus, the assessment of the severity of DPN could aid in the prediction of the risk of developing diabetic complications in patients with untreated diabetes.

Prevalence and characteristics of diabetic symmetric sensorimotor polyneuropathy in Japanese patients with type 2 diabetes: The Japan Diabetes Complication and its Prevention Prospective study (JDCP study 10)

This study aimed to investigate the prevalence and characteristics of diabetic symmetric sensorimotor polyneuropathy (DSPN) in patients with type 2 diabetes registered in the Japan Diabetes Complication and its Prevention Prospective study. In the study, 6,338 patients with diabetes who had been treated by diabetes specialists were registered in 2007-2009. Of these, patients with type 2 diabetes who could be evaluated for DSPN were analyzed using the t-test, χ2 -test and logistic regression analyses. DSPN was diagnosed using the Simple Diagnostic Criteria for Diabetic Polyneuropathy proposed by the Diabetic Neuropathy Study Group in Japan. Of the total participants, 5,451 patients (mean age 61.4 years, duration of diabetes 10.8 years) were analyzed. Based on the criteria, 35.8% of patients were diagnosed with DSPN. The prevalence of sensory symptoms was 25.8%. The following factors increased the risk for DSPN: age (odds ratio [OR] 1.57, 95% confidence interval [CI] 1.42-1.73), duration of diabetes (OR 1.32, 95% CI 1.21-1.43), body mass index (OR 1.19, 95% CI 1.09-1.30), systolic blood pressure (OR 1.06, 95% CI 1.01-1.10), hemoglobin A1c (OR 1.15, 95% CI 1.09-1.22), biguanides (OR 1.22, 95% CI 1.06-1.39) and insulin therapy (OR 1.59, 95% CI 1.36-1.84). The following factors decreased the risk for DSPN: total cholesterol (OR 0.98, 95% CI 0.96-1.00) and exercise therapy (OR 0.85, 95% CI 0.73-0.98). The baseline survey clarified the prevalence and characteristics of DSPN in Japanese patients with type 2 diabetes. The survey also showed the risk factors of DSPN.

Prevalence and characteristics of diabetic symmetric sensorimotor polyneuropathy in Japanese patients with type 2 diabetes: the Japan Diabetes Complication and its Prevention Prospective study (JDCP study 10)

Aim/introduction

This study aims to investigate the prevalence and characteristics of diabetic symmetric sensorimotor polyneuropathy (DSPN) in patients with type 2 diabetes registered in the Japan Diabetes Complication and its Prevention Prospective (JDCP) study.

Materials and methods

In the study, 6338 patients with diabetes who had been treated by diabetes specialists were registered in 2007-2009. Of these, patients with type 2 diabetes who could be evaluated for DSPN were analyzed using t test, chi-square test, and logistic regression analyses. DSPN was diagnosed using the Simple Diagnostic Criteria for Diabetic Polyneuropathy proposed by the Diabetic Neuropathy Study Group in Japan.

Results

Of the total participants, 5451 patients (mean age 61.4 years old and duration of diabetes 10.8 years) were analyzed. Based on the criteria, 35.8% of patients were diagnosed with DSPN. The prevalence of sensory symptoms was 25.8%. The following factors increased risk for DSPN: age [odds ratio (OR) 1.57, 95% confidence intervals (CI) 1.42-1.73], duration of diabetes (OR 1.32, 95% CI 1.21-1.43), body mass index (OR 1.19, 95% CI 1.09-1.30), systolic blood pressure (OR 1.06, 95% CI 1.01-1.10), hemoglobin A1c (OR 1.15, 95% CI 1.09-1.22), biguanides (OR 1.22, 95% CI 1.06-1.39), and insulin therapy (OR 1.59, 95% CI 1.36-1.84). The following factors decreased risk for DSPN: total cholesterol (OR 0.98, 95% CI 0.96-1.00) and exercise therapy (OR 0.85, 95% CI 0.73-0.98).

Conclusions

The baseline survey clarified the prevalence and characteristics of DSPN in Japanese patients with type 2 diabetes. The survey also revealed the risk factors of DSPN.

The impact of diabetic polyneuropathy on toe grip strength in patients with type 2 diabetes mellitus: a cross-sectional study

Purpose

Type 2 diabetes mellitus (T2DM) and concomitant diabetic polyneuropathy (DPN) induce muscle weakness. Muscle weakness in the foot is associated with foot deformities and falls. However, factors affecting toe grip strength (TGS) are not well known. Therefore, the present study investigated factors related to TGS in patients with T2DM.

Methods

This was a cross-sectional study involving 100 patients with T2DM who were hospitalized for the treatment of T2DM and 50 healthy adults. The subjects were divided into three groups: a group of healthy subjects, a group of T2DM patients without DPN, and a group of T2DM patients with DPN. Hierarchical multiple regression analysis was performed with TGS and the TGS-to-weight ratio (TGS/Wt%) as dependent variables and with age, the presence of T2DM, and DPN as independent variables, and sex and BMI as confounders.

Results

There were no significant differences in age or sex among the three groups. In the final regression analysis, age and presence of T2DM and DPN were associated in both models with TGS and TGS/Wt% as dependent variables.

Conclusion

DPN, T2DM, and age were found to be related to TGS. The findings of this study could contribute to healthcare providers developing foot care and rehabilitation programs for diabetic patients.

Trial registration

This study was registered with UMIN-CTR (UMIN000034320) on 1 November 2018.

Diagnostic accuracy of the 5.07 monofilament test for diabetes polyneuropathy: influence of age, sex, neuropathic pain and neuropathy severity

INTRODUCTION

There is a need for simple and cheap diagnostic tools for diabetic polyneuropathy (DPN). We aimed to assess the diagnostic accuracy of the 5.07/10 g monofilament test in patients referred to polyneuropathy assessments, as well as to examine how disease severity, age, sex and neuropathic pain (NP) impact diagnostic accuracy.

RESEARCH DESIGN AND METHODS

Five Norwegian university hospitals recruited patients with diabetes aged 18-70 referred to neurological outpatient clinics for polyneuropathy assessments. The 5.07/10 g Semmes-Weinstein monofilament examination (SWME) was validated against the Toronto consensus for diagnosing diabetic neuropathies; the results were stratified by age, sex and NP. Disease severity was graded by a combined nerve conduction study (NCS) Z-score, and logistic regression was applied to assess whether disease severity was a predictor of diagnostic accuracy.

RESULTS

In total, 506 patients were included in the study. Global sensitivity was 0.60 (95% CI 0.55, 0.66), specificity 0.82 (95% CI 0.75, 0.87), positive and negative predictive values were 0.86 (95% CI 0.81, 0.90) and 0.52 (95% CI 0.46, 0.58), respectively, positive and negative likelihood ratios were 3.28 (95% CI 2.37, 4.53) and 0.49 (95% CI 0.42, 0.57), respectively. The SWME was less sensitive in females (0.43), had lower specificity in patients with NP (0.56), and performed worse in patients ≥50 years. NCS-based disease severity did not affect diagnostic accuracy (OR 1.15, 95% CI 0.95, 1.40).

CONCLUSIONS

This multicenter study demonstrates poor diagnostic performance for the 5.07/10 g SWME in patients with diabetes referred to polyneuropathy assessments; it is particularly unsuited for female patients and those with NP. The diagnostic accuracy of the SWME was not influenced by NCS-based disease severity, demonstrating that it does not perform better in patients with later stages of DPN. We do not recommend the use of the 5.07/10 g monofilament in the evaluation of patients with diabetes referred to polyneuropathy assessments.

To Use or Not to Use a Self-monitoring of Blood Glucose System? Real-world Flash Glucose Monitoring Patterns Using a Cluster Analysis of the FGM-Japan Study

Objective This study investigated self-monitoring of blood glucose (SMBG) adherence and flash glucose monitoring patterns using a cluster analysis in Japanese type 1 diabetes (T1D) patients with intermittently scanned continuous glucose monitoring (isCGM). Methods We measured SMBG adherence and performed a data-driven cluster analysis using a hierarchical clustering in T1D patients from Japan using the FreeStyle Libre system. Clusters were based on three variables (testing glucose frequency and referred Libre data for hyperglycemia or hypoglycemia). Patients We enrolled 209 participants. Inclusion criteria were patients with T1D, duration of isCGM use ≥3 months, age ≥20 years old, and regular attendance at the collaborating center. Results The rate of good adherence to SMBG recommended by a doctor was 85.0%. We identified three clusters: cluster 1 (low SMBG test frequency but high reference to Libre data, 17.7%), cluster 2 (high SMBG test frequency but low reference to Libre data, 34.0%), and cluster 3 (high SMBG test frequency and high reference to Libra data, 48.3%). Compared with other clusters, individuals in cluster 1 were younger, those in cluster 2 had a shorter Libre duration, and individuals in cluster 3 had lower time-in-range, higher severe diabetic distress, and high intake of snacks and sweetened beverages. There were no marked differences in the incidence of diabetic complications and rate of wearing the Libre sensor among the clusters. Conclusion We stratified the patients into three subgroups with varied clinical characteristics and CGM metrics. This new substratification might help tailor diabetes management of patients with T1D using isCGM.

Peripheral Neuropathy in Diabetes: What Can MRI Do?

Diabetes peripheral neuropathy (DPN) is commonly asymptomatic in the early stage. However, once symptoms and obvious defects appear, recovery is not possible. Diagnosis of neuropathy is based on physical examinations, questionnaires, nerve conduction studies, skin biopsies, and so on. However, the diagnosis of DPN is still challenging, and early diagnosis and immediate intervention are very important for prevention of the development and progression of diabetic neuropathy. The advantages of MRI in the diagnosis of DPN are obvious: the peripheral nerve imaging is clear, the lesions can be found intuitively, and the quantitative evaluation of the lesions is the basis for the diagnosis, classification, and follow-up of DPN. With the development of magnetic resonance technology, more and more studies have been conducted on detection of DPN. This article reviews the research field of MRI in DPN.

Association between Diabetic Peripheral Neuropathy as Measured Using a Point-of-Care Sural Nerve Conduction Device and Urinary Albumin Excretion in Patients with Type 2 Diabetes

BACKGROUND

It is not well known whether diabetic peripheral neuropathy diagnosed using a non-invasive point-of-care nerve conduction device called DPN-Check^® is associated with diabetic nephropathy. Thus, we aimed to evaluate the association of diabetic peripheral neuropathy with urinary albumin excretion in patients with type 2 diabetes using DPN-Check^®.

METHODS

This retrospective observational study included 323 Japanese patients with type 2 diabetes. The urinary albumin-to-creatinine ratio in a spot urine sample was defined as urinary albumin excretion. Multiple linear regression analysis was used to determine the association of DPN-Check^®-determined diabetic peripheral neuropathy with urinary albumin excretion.

RESULTS

Patients with DPN-Check^®-determined diabetic peripheral neuropathy had significantly higher urinary albumin excretion than those without, while there was no difference in urinary albumin excretion between patients with and without diabetic peripheral neuropathy determined by simplified diagnostic criteria. In the multivariate model, the DPN-Check^® determined that diabetic peripheral neuropathy was significantly associated with urinary albumin excretion even after adjustment for covariates (standardized β, 0.123; p = 0.012).

CONCLUSIONS

Our study found a significant association between diabetic peripheral neuropathy diagnosed using DPN-Check^® and urinary albumin excretion in patients with type 2 diabetes.

Protective and risk factors of impaired awareness of hypoglycemia in patients with type 1 diabetes: a cross-sectional analysis of baseline data from the PR-IAH study

BACKGROUND

Hypoglycemia in type 1 diabetes (T1D) is associated with mortality and morbidity, especially when awareness of hypoglycemia is impaired. This study aimed to investigate the protective and risk factors for impaired awareness of hypoglycemia (IAH) in adults with T1D.

METHODS

This cross-sectional study enrolled 288 adults with T1D (mean age, 50.4 ± 14.6 years; male, 36.5%; diabetes duration, 17.6 ± 11.2 years; mean HbA1c level, 7.7 ± 0.9%), who were divided into IAH and non-IAH (control) groups. A survey was conducted to assess hypoglycemia awareness using the Clarke questionnaire. Diabetes histories, complications, fear of hypoglycemia, diabetes distress, hypoglycemia problem-solving abilities, and treatment data were collected.

RESULTS

The prevalence of IAH was 19.1%. Diabetic peripheral neuropathy was associated with an increased risk of IAH (odds ratio [OR] 2.63; 95% confidence interval [CI] 1.13-5.91; P = 0.014), while treatment with continuous subcutaneous insulin infusion and hypoglycemia problem-solving perception scores were associated with a decreased risk of IAH (OR, 0.48; 95% CI, 0.22-0.96; P = 0.030; and OR, 0.54; 95% CI, 0.37-0.78; P = 0.001, respectively). There was no difference in continuous glucose monitoring use between the groups.

CONCLUSION

We identified protective factors in addition to risk factors for IAH in adults with T1D. This information may help manage problematic hypoglycemia.

TRIAL REGISTRATION

University hospital Medical Information Network (UMIN) Center: UMIN000039475). Approval date 13 February 2020.

Factors associated with hemoglobin glycation index in adults with type 1 diabetes mellitus: The FGM-Japan study

AIMS/INTRODUCTION

The discrepancy between HbA1c and glucose exposure may have significant clinical implications; however, the association between the hemoglobin glycation index (HGI) and clinical parameters in type 1 diabetes remains controversial. This study aimed to find the factors associated with HGI (laboratory HbA1c - predicted HbA1c derived from the continuous glucose monitoring [CGM]).

MATERIALS AND METHODS

We conducted a cross-sectional study of adults with type 1 diabetes (n = 211, age 50.9 ± 15.2 years old, female sex = 59.2%, duration of CGM use = 2.1 ± 1.0 years). All subjects wore the CGM for 90 days before HbA1c measurement. Data derived from the FreeStyle Libre sensor were used to calculate the glucose management indicator (GMI) and glycemic variability (GV) parameters. HGI was defined as the difference between the GMI and the laboratory HbA1c levels. The participants were divided into three groups according to the HGI tertile (low, moderate, and high). Multivariate regression analyses were performed.

RESULTS

The female sex ratio, HbA1c, and % coefficient of variation (%CV) significantly increased over the HGI tertile, while eGFR and Hb decreased over the HGI tertile. In multivariate analysis, the factors associated with HGI were %CV and eGFR, after adjusting for HbA1c level and sex (R²  = 0.44).

CONCLUSIONS

This study demonstrated that HGI is associated with female sex, eGFR, and some glycemic variability indices, independently of HbA1c. Minimizing glycemic fluctuations might reduce HGI. This information provides diabetic health professionals and patients with personalized diabetes management for adults with type 1 diabetes.

Diabetic corneal neuropathy as a surrogate marker for diabetic peripheral neuropathy

Diabetic neuropathy is a prevalent microvascular complication of diabetes mellitus, affecting nerves in all parts of the body including corneal nerves and peripheral nervous system, leading to diabetic corneal neuropathy and diabetic peripheral neuropathy, respectively. Diabetic peripheral neuropathy is diagnosed in clinical practice using electrophysiological nerve conduction studies, clinical scoring, and skin biopsies. However, these diagnostic methods have limited sensitivity in detecting small-fiber disease, hence they do not accurately reflect the status of diabetic neuropathy. More recently, analysis of alterations in the corneal nerves has emerged as a promising surrogate marker for diabetic peripheral neuropathy. In this review, we will discuss the relationship between diabetic corneal neuropathy and diabetic peripheral neuropathy, elaborating on the foundational aspects of each: pathogenesis, clinical presentation, evaluation, and management. We will further discuss the relevance of diabetic corneal neuropathy in detecting the presence of diabetic peripheral neuropathy, particularly early diabetic peripheral neuropathy; the correlation between the severity of diabetic corneal neuropathy and that of diabetic peripheral neuropathy; and the role of diabetic corneal neuropathy in the stratification of complications of diabetic peripheral neuropathy.

Prevention and Management Strategies for Diabetic Neuropathy

Diabetic neuropathy (DN) is a common complication of diabetes that is becoming an increasing concern as the prevalence of diabetes rapidly rises. There are several types of DN, but the most prevalent and studied type is distal symmetrical polyneuropathy, which is the focus of this review and is simply referred to as DN. It can lead to a wide range of sensorimotor and psychosocial symptoms and is a major risk factor for diabetic foot ulceration and Charcot neuropathic osteoarthropathy, which are associated with high rates of lower limb amputation and mortality. The prevention and management of DN are thus critical, and clinical guidelines recommend several strategies for these based on the best available evidence. This article aims to provide a narrative review of DN prevention and management strategies by discussing these guidelines and the evidence that supports them. First, the epidemiology and diverse clinical manifestations of DN are summarized. Then, prevention strategies such as glycemic control, lifestyle modifications and footcare are discussed, as well as the importance of early diagnosis. Finally, neuropathic pain management strategies and promising novel therapies under investigation such as neuromodulation devices and nutraceuticals are reviewed.

Association between sarcopenia and the severity of diabetic polyneuropathy assessed by nerve conduction studies in Japanese patients with type 2 diabetes mellitus

AIMS/INTRODUCTION

This study examined the association between the severity of diabetic polyneuropathy (DPN) based on the Baba classification and sarcopenia and its related factors.

MATERIALS AND METHODS

The subjects were 261 patients with type 2 diabetes mellitus. DPN was classified as stages 0 to 4 according to the Baba classification. Sarcopenia was diagnosed based on measurements of the skeletal mass index, grip strength, and walking speed, using the Asia Working Group for Sarcopenia 2019 diagnostic criteria.

RESULTS

The median age of the subjects was 67 years, the proportion of men was 58.6%, the median estimated duration of diabetes was 10 years, and the median values for HbA1c were 10.3%. With regard to DPN, the prevalence of Baba classification stages 0 to 2 was 90.8% (n = 237), and that of stage 3 or 4 was 9.2% (n = 24). The prevalence of sarcopenia was 19.9%. A trend toward an increase in the frequency of slow walking speed was seen as the stage of DPN progressed. The frequencies of sarcopenia and slow walking speed were higher in the group with the Baba classification stages 3 and 4 than in the group with stages 0 to 2. On multiple logistic regression analyses, however, DPN was not significantly related to sarcopenia and walking speed.

CONCLUSIONS

Although severe DPN may be related to sarcopenia, the frequency of severe DPN is low in the clinical setting, indicating that its contribution to sarcopenia is modest.

Correlation of Baba's diabetic neuropathy classification with various diabetes-related complications

It is known that Baba's diabetic neuropathy classification (BDC) is useful in quantitative evaluation of Diabetic polyneuropathy (DPN). In this study, we aimed to investigate the possible association between BDC and various diabetic microvascular and macrovascular complications in patients whose neuropathy was evaluated with BDC. As the results, BDC was significantly correlated with the severity of diabetic retinopathy and nephropathy. BDC was also significantly correlated with history of myocardial infarction or cerebral infarction, carotid IMT, and ABI. These data suggest that BDC may be useful in predicting the presence of various diabetic microvascular and macrovascular complications. The data also support the idea that we should perform further investigation of other diabetes-related complications in patients with severe DPN.

Bilirubin is inversely related to diabetic peripheral neuropathy assessed by sural nerve conduction study

AIMS/INTRODUCTION

Diagnosis of diabetic peripheral neuropathy (DPN) depends on subjective findings, certain investigations for DPN risks have not been performed enough. Bilirubin protects against vascular complications by reducing oxidative stress in diabetes, but is not fully tested for DPN. This study aimed to evaluate sural nerve conduction impairments (SNCI) as an objective DPN marker and the contribution of bilirubin to SNCI.

MATERIALS AND METHODS

Using DPN-Check® , SNCI was defined as a decline of amplitude potential or conduction velocity below the normal limit in 150 inpatients with diabetes. The correlations between SNCI and conventional DPN diagnosis criteria, the incidence of diabetic retinopathy/nephropathy, biomarkers for atherosclerosis, cardiac function by ultrasonic cardiogram, and bilirubin were statistically tested, followed by the comparison of logistic regression models for SNCI to find confounders with bilirubin.

RESULTS

The incidence of SNCI was 72.0%. The sensitivity and specificity of SNCI for DPN prediagnosis by simplified criteria were 54.6 and 90.5%, respectively, and similarly corresponded with diabetic retinopathy and nephropathy (sensitivity 57.4 and 50.0%, respectively). SNCI significantly related to diabetes duration, declined estimated glomerular filtration rate, albuminuria and total bilirubin. SNCI incidence was attenuated in the higher bilirubin tertiles (89.8/65.3/54.8%, P < 0.001). Bilirubin was an independent inverse risk factor for SNCI, even after adjustment by known risk factors for DPN and markers for microvascular complications.

CONCLUSIONS

SNCI is a comprehensive marker for diabetic complications. We first showed the independent inverse relationship between bilirubin and SNCI through the independent pathway with other complications, provably reducing oxidative stress, as previously reported.

Prediction of Diabetic Sensorimotor Polyneuropathy Using Machine Learning Techniques

Diabetic sensorimotor polyneuropathy (DSPN) is a major complication in patients with diabetes mellitus (DM), and early detection or prediction of DSPN is important for preventing or managing neuropathic pain and foot ulcer. Our aim is to delineate whether machine learning techniques are more useful than traditional statistical methods for predicting DSPN in DM patients. Four hundred seventy DM patients were classified into four groups (normal, possible, probable, and confirmed) based on clinical and electrophysiological findings of suspected DSPN. Three ML methods, XGBoost (XGB), support vector machine (SVM), and random forest (RF), and their combinations were used for analysis. RF showed the best area under the receiver operator characteristic curve (AUC, 0.8250) for differentiating between two categories—criteria by clinical findings (normal, possible, and probable groups) and those by electrophysiological findings (confirmed group)—and the result was superior to that of linear regression analysis (AUC = 0.6620). Average values of serum glucose, International Federation of Clinical Chemistry (IFCC), HbA1c, and albumin levels were identified as the four most important predictors of DSPN. In conclusion, machine learning techniques, especially RF, can predict DSPN in DM patients effectively, and electrophysiological analysis is important for identifying DSPN.

Genetic loss-of-function of activating transcription factor 3 but not C-type lectin member 5A prevents diabetic peripheral neuropathy

We investigated the mediating roles of activating transcription factor 3 (ATF3), an injury marker, or C-type lectin member 5A (CLEC5A), an inflammatory response molecule, in the induction of endoplasmic reticulum (ER) stress and neuroinflammation in diabetic peripheral neuropathy in ATF3 and CLEC5A genetic knockout (aft3-/- and clec5a-/-, respectively) mice. ATF3 was expressed intranuclearly and was upregulated in mice with diabetic peripheral neuropathy (DN) and clec5a-/- mice. The DN and clec5a-/- groups also exhibited neuropathic behavior, but not in the aft3-/- group. The upregulation profiles of cytoplasmic polyadenylation element-binding protein, a protein translation-regulating molecule, and the ER stress-related molecules of inositol-requiring enzyme 1α and phosphorylated eukaryotic initiation factor 2α in the DN and clec5a-/- groups were correlated with neuropathic behavior. Ultrastructural evidence confirmed ER stress induction and neuroinflammation, including microglial enlargement and proinflammatory cytokine release, in the DN and clec5a-/- mice. By contrast, the induction of ER stress and neuroinflammation did not occur in the aft3-/- mice. Furthermore, the mRNA of reactive oxygen species-removing enzymes such as superoxide dismutase, heme oxygenase-1, and catalase were downregulated in the DN and clec5a-/- groups but were not changed in the aft3-/- group. Taken together, the results indicate that intraneuronal ATF3, but not CLEC5A, mediates the induction of ER stress and neuroinflammation associated with diabetic neuropathy.

Neuroretinal dysfunction revealed by a flicker electroretinogram correlated with peripheral nerve dysfunction and parameters of atherosclerosis in patients with diabetes

AIMS/INTRODUCTION

Diabetic polyneuropathy (DPN) develops in the early stage of diabetes. However, no common diagnostic protocol has yet been established. Here, to verify that the flicker electroretinogram using a hand-held device can detect the early dysfunction of the peripheral nervous system in patients with diabetes, we investigated the correlation between the progression of DPN and neuroretinal dysfunction.

MATERIALS AND METHODS

In total, 184 participants with type 1 or 2 diabetes underwent a flicker electroretinogram (ERG) using a hand-held device RETeval™ and nerve conduction study. Participants were also evaluated for intima-media thickness, ankle-brachial index, toe brachial index and brachial-ankle pulse wave velocity. Parameters of the nerve conduction study were used to diagnose the severity according to Baba's classification. A multiple regression analysis was used to examine the associations of ERG parameters with the severity of DPN categorized by Baba's classification. Diagnostic properties of the device in DPN were evaluated using a receiver operating characteristic curve.

RESULTS

A multiple regression model to predict the severity of DPN was generated using ERG. In the model, moderate-to-severe DPN was effectively diagnosed (area under the receiver operating characteristic curve 0.692, sensitivity 56.5%, specificity 78.3%, positive predictive value 70.6%, negative predictive value 66.1%, positive likelihood ratio 2.60, negative likelihood ratio 0.56). In the patients without diabetic retinopathy, the implicit time and amplitude in ERG significantly correlated with the parameters of the nerve conduction study, brachial-ankle pulse wave velocity and intima-media thickness.

CONCLUSIONS

Electroretinogram parameters obtained by the hand-held device successfully predict the severity of DPN. The device might be useful to evaluate DPN.

Diabetes is associated with greater leg pain and worse patient-reported outcomes at 1 year after lumbar spine surgery

Although patients with diabetes reportedly have more back pain and worse patient-reported outcomes than those without diabetes after lumbar spine surgery, the impact of diabetes on postoperative recovery in pain or numbness in other regions is not well characterized. In this study, the authors aimed to elucidate the impact of diabetes on postoperative recovery in pain/numbness in four areas (back, buttock, leg, and sole) after lumbar spine surgery. The authors retrospectively reviewed 993 patients (152 with diabetes and 841 without) who underwent decompression and/or fixation within three levels of the lumbar spine at eight hospitals during April 2017–June 2018. Preoperative Numerical Rating Scale (NRS) scores in all four areas, Oswestry Disability Index (ODI), and Euro quality of life 5-dimension (EQ-5D) were comparable between the groups. The diabetic group showed worse ODI/EQ-5D and greater NRS scores for leg pain 1 year after surgery than the non-diabetic group. Although other postoperative NRS scores tended to be higher in the diabetic group, the between-group differences were not significant. Diabetic neuropathy caused by microvascular changes may induce irreversible nerve damage especially in leg area. Providers can use this information when counseling patients with diabetes about the expected outcomes of spine surgery.

Alterations of retinal thickness measured by optical coherence tomography correlate with neurophysiological measures in diabetic polyneuropathy

AIMS/INTRODUCTION

Diabetic polyneuropathy (DPN) and diabetic retinopathy (DR) are traditionally regarded as microvascular complications. However, these complications may share similar neurodegenerative pathologies. Here we evaluate the correlations in the severity of DPN and changes in the thickness of neuroretinal layers to elucidate whether these complications exist at similar stages of progression.

MATERIALS AND METHODS

A total of 43 patients with type 2 diabetes underwent a nerve conduction study (NCS), a macular optical coherence tomography, and a carotid artery ultrasound scan. Diabetic polyneuropathy was classified according to Baba's classification using NCS. The retina was automatically segmented into four layers; ganglion cell complex (GCC), inner nuclear layer/outer plexiform layer (INL/OPL), outer nuclear layer/photoreceptor inner and outer segments, and retinal pigment epithelium (RPE). The thickness of each retinal layer was separately analyzed for the fovea and the parafovea.

RESULTS

Fourteen patients were classified as having moderate to severe diabetic polyneuropathy. The thicknesses of the foveal and parafoveal INL/OPL increased in patients with diabetic polyneuropathy compared with patients without. The thickness of the parafoveal retinal pigment epithelium decreased in patients with diabetic polyneuropathy. The thinning of parafoveal ganglion cell complex and foveal and parafoveal retinal pigment epithelium were positively correlated with deterioration of nerve functions in the nerve conduction study, but the thickening of INL/OPL was positively correlated with the nerve function deterioration. The thinning of parafoveal ganglion cell complex and foveal retinal pigment epithelium were positively correlated with the thickening of the carotid intima-media.

CONCLUSIONS

Depending on the progression of diabetic polyneuropathy, the ganglion cell complex and retinal pigment epithelium became thinner and the INL/OPL became thicker. These retinal changes might be noteworthy for pathological investigations and for the assessment of diabetic polyneuropathy and diabetic retinopathy.

Using mHealth to Provide Mobile App Users With Visualization of Health Checkup Data and Educational Videos on Lifestyle-Related Diseases: Methodological Framework for Content Development

Background

The number of people with lifestyle-related diseases continues to increase worldwide. Improving lifestyle behavior with health literacy may be the key to address lifestyle-related diseases. The delivery of educational videos using mobile health (mHealth) services can replace the conventional way of educating individuals, and visualization can replace the provision of health checkup data.

Objective

This paper aimed to describe the development of educational content for MIRAMED, a mobile app aimed at improving users’ lifestyle behaviors and health literacy for lifestyle-related diseases.

Methods

All videos were based on a single unified framework to provide users with a consistent flow of information. The framework was later turned into a storyboard. The final video contents were created based on this storyboard and further discussions with leading experts and specialist physicians on effective communication with app users about lifestyle-related diseases.

Results

The app uses visualization of personal health checkup data and educational videos on lifestyle-related diseases based on the current health guidelines, scientific evidence, and expert opinions of leading specialist physicians in the respective fields. A total of 8 videos were created for specific lifestyle-related diseases affecting 8 organs: (1) brain–cerebrovascular disorder, (2) eyes–diabetic retinopathy, (3) lungs–chronic obstructive pulmonary disease, (4) heart–ischemic heart disease, (5) liver–fatty liver, (6) kidneys–chronic kidney disease (diabetic kidney disease), (7) blood vessels–peripheral arterial disease, and (8) nerves–diabetic neuropathy.

Conclusions

Providing enhanced mHealth education using novel digital technologies to visualize conventional health checkup data and lifestyle-related diseases is an innovative strategy. Future studies to evaluate the efficacy of the developed content are planned.

Point-of-care nerve conduction device predicts the severity of diabetic polyneuropathy: A quantitative, but easy-to-use, prediction model

Aims/Introduction

A gold standard in the diagnosis of diabetic polyneuropathy (DPN) is a nerve conduction study. However, as a nerve conduction study requires expensive equipment and well‐trained technicians, it is largely avoided when diagnosing DPN in clinical settings. Here, we validated a novel diagnostic method for DPN using a point‐of‐care nerve conduction device as an alternative way of diagnosis using a standard electromyography system.

Materials and Methods

We used a multiple regression analysis to examine associations of nerve conduction parameters obtained from the device, DPNCheck™, with the severity of DPN categorized by the Baba classification among 375 participants with type 2 diabetes. A nerve conduction study using a conventional electromyography system was implemented to differentiate the severity in the Baba classification. The diagnostic properties of the device were evaluated using a receiver operating characteristic curve.

Results

A multiple regression model to predict the severity of DPN was generated using sural nerve conduction data obtained from the device as follows: the severity of DPN = 2.046 + 0.509 × ln(age [years]) − 0.033 × (nerve conduction velocity [m/s]) − 0.622 × ln(amplitude of sensory nerve action potential [µV]), r = 0.649. Using a cut‐off value of 1.3065 in the model, moderate‐to‐severe DPN was effectively diagnosed (area under the receiver operating characteristic curve 0.871, sensitivity 70.1%, specificity 87.7%, positive predictive value 83.0%, negative predictive value 77.3%, positive likelihood ratio 5.67, negative likelihood ratio 0.34).

Conclusions

Nerve conduction parameters in the sural nerve acquired by the handheld device successfully predict the severity of DPN.