Prevalence and risk factors of diabetic peripheral neuropathy: A population-based cross-sectional study in China

Obesity-related neuropathy: the new epidemic

PURPOSE OF REVIEW

To examine the evidence evaluating the association between obesity and neuropathy as well as potential interventions.

RECENT FINDINGS

Although diabetes has long been associated with neuropathy, additional metabolic syndrome components, including obesity, are increasingly linked to neuropathy development, regardless of glycemic status. Preclinical rodent models as well as clinical studies are shedding light on the mechanisms of obesity-related neuropathy as well as challenges associated with slowing progression. Dietary and surgical weight loss and exercise interventions are promising, but more data is needed.

SUMMARY

High-fat-diet rodent models have shown that obesity-related neuropathy is a product of excess glucose and lipid accumulation leading to inflammation and cell death. Clinical studies consistently demonstrate obesity is independently associated with neuropathy; therefore, likely a causal risk factor. Dietary weight loss improves neuropathy symptoms but not examination scores. Bariatric surgery and exercise are promising interventions, but larger, more rigorous studies are needed. Further research is also needed to determine the utility of weight loss medications and ideal timing for obesity interventions to prevent neuropathy.

Construction of an Early Risk Prediction Model for Type 2 Diabetic Peripheral Neuropathy Based on Random Forest

Diabetic peripheral neuropathy is a major cause of disability and death in the later stages of diabetes. A retrospective chart review was performed using a hospital-based electronic medical record database to identify 1020 patients who met the criteria. The objective of this study was to explore and analyze the early risk factors for peripheral neuropathy in patients with type 2 diabetes, even in the absence of specific clinical symptoms or signs. Finally, the random forest algorithm was used to rank the influencing factors and construct a predictive model, and then the model performance was evaluated. Logistic regression analysis revealed that vitamin D plays a crucial protective role in preventing diabetic peripheral neuropathy. The top three risk factors with significant contributions to the model in the random forest algorithm eigenvalue ranking were glycosylated hemoglobin, disease duration, and vitamin D. The areas under the receiver operating characteristic curve of the model ware 0.90. The accuracy, precision, specificity, and sensitivity were 0.85, 0.83, 0.92, and 0.71, respectively. The predictive model, which is based on the random forest algorithm, is intended to support clinical decision-making by healthcare professionals and help them target timely interventions to key factors in early diabetic peripheral neuropathy.

Prevalence of painful and painless diabetic peripheral neuropathy in the Northern Danish Region: A population-based study

BACKGROUND

Diabetic peripheral neuropathy (DPN) is a common complication of diabetes, yet varying estimates of its prevalence exist. The present study aimed to estimate a questionnaire-centered prevalence of painful and painless DPN in the Northern Danish Region, examine its geographical distribution within the region, and investigate associations between DPN and potential risk factors.

METHODS

A questionnaire-based survey was sent to all persons living with diabetes in the Northern Danish Region using electronic mail. Persons with diabetes were identified using The National Health Insurance Service Registry. The survey included information on demographics, socioeconomics, municipality, diabetes type, duration, and treatment, as well as the validated questionnaires Michigan Neuropathy Screening Instrument-questionnaire (MNSIq) and the Douleur Neuropathique en 4 Questions (DN4)-interview. Possible DPN was defined as an MNSIq-score ≥ 4, while possible painful DPN was defined as pain in both feet and a DN4-interview score ≥ 3.

RESULTS

A total of 23,206 eligible people were identified as having diabetes and approximately 33 % answered all questionnaires. The prevalence of possible DPN was 23.3 % (95 % CI: 22.4-24.3 %), while the prevalence of possible painful DPN was 18.0 % (17.1-18.8 %). The prevalence of possible DPN ranged from 22.1 % to 35.0 % between municipalities, while the prevalence of possible painful DPN ranged from 15.6 % to 20.0 %. High body-mass index, long diabetes duration, insulin use, glucagon-like-peptide-1-analogue use, and low income were associated with increased risk of DPN.

CONCLUSION

The high prevalence of possible painless and painful DPN emphasizes the need for better prevention and careful screening even in high-income countries.

Correlation between Neutrophil-to-Lymphocyte Ratio and Diabetic Neuropathy in Chinese Adults with Type 2 Diabetes Mellitus Using Machine Learning Methods

Objective

One of the most frequent consequences of diabetes mellitus has been identified as diabetic peripheral neuropathy (DPN), and numerous inflammatory disorders, including diabetes, have been documented to be reflected by the neutrophil-to-lymphocyte ratio (NLR). This study aimed to explore the correlation between peripheral blood NLR and DPN, and to evaluate whether NLR could be utilized as a novel marker for early diagnosis of DPN among those with type 2 Diabetes Mellitus (T2DM).

Methods

We reviewed the medical records of 1154 diabetic patients treated at Tongji Hospital Affiliated to Tongji University from January 2022 to March 2023. These patients did not have evidence of acute infections, chronic inflammatory status within the past three months. The information included the clinical, laboratory, and demographic characteristics of the patient. Finally, a total of 442 T2DM individuals with reliable, complete, and accessible medical records were recruited, including 216 T2DM patients without complications (DM group) and 226 T2DM patients with complications of DPN (DPN group). One-way ANOVA and multivariate logistic regression were applied to analyze data from the two groups, including peripheral blood NLR values and other biomedical indices. The cohort was divided in a 7 : 3 ratio into training and internal validation datasets following feature selection and data balancing. Based on machine learning, training was conducted using extreme gradient boosting (XGBoost) and support vector machine (SVM) methods. K-fold cross-validation was applied for model assessment, and accuracy, precision, recall, F1-score, and the area under the receiver operating characteristic curve (AUC) were used to validate the models' discrimination and clinical applicability. Using Shapley Additive Explanations (SHAP), the top-performing model was interpreted.

Results

The values of 24-hour urine volume (24H UV), lower limb arterial plaque thickness (LLAB thickness), carotid plaque thickness (CP thickness), D-dimer and onset time were significantly higher in the DPN group compared to the DM group, whereas the values of urine creatinine (UCr), total cholesterol (TC), low-density lipoprotein (LDL), alpha-fetoprotein (AFP), fasting c-peptide (FCP), and nerve conduction velocity and wave magnitude of motor and sensory nerve shown in electromyogram (EMG) were considerably lower than those in the DM group (P < 0.05, respectively). NLR values were significantly higher in the DPN group compared to the DM group (2.60 ± 4.82 versus 1.85 ± 0.98, P < 0.05). Multivariate logistic regression analysis revealed that NLR (P = 0.008, C = 0.003) was a risk factor for DPN. The multivariate logistic regression model scores were 0.6241 for accuracy, 0.6111 for precision, 0.6667 for recall, 0.6377 for F1, and 0.6379 for AUC. Machine learning methods, XGBoost and SVM, built prediction models, showing that NLR can predict the onset of DPN. XGBoost achieved an accuracy of 0.6541, a precision of 0.6316, a recall of 0.7273, a F1 value of 0.6761, and an AUC value of 0.690. SVM scored an accuracy of 0.5789, a precision of 0.5610, a recall of 0.6970, an F1 value of 0.6216, and an AUC value of 0.6170.

Conclusions

Our findings demonstrated that NLR is highly correlated with DPN and is an independent risk factor for DPN. NLR might be a novel indicator for the early diagnosis of DPN. XGBoost and SVM models have great predictive performance and could be reliable tools for the early prediction of DPN in T2DM patients. This trial is registered with ChiCTR2400087019.

Interpretable machine learning models for detecting peripheral neuropathy and lower extremity arterial disease in diabetics: an analysis of critical shared and unique risk factors

BACKGROUND

Diabetic peripheral neuropathy (DPN) and lower extremity arterial disease (LEAD) are significant contributors to diabetic foot ulcers (DFUs), which severely affect patients' quality of life. This study aimed to develop machine learning (ML) predictive models for DPN and LEAD and to identify both shared and distinct risk factors.

METHODS

This retrospective study included 479 diabetic inpatients, of whom 215 were diagnosed with DPN and 69 with LEAD. Clinical data and laboratory results were collected for each patient. Feature selection was performed using three methods: mutual information (MI), random forest recursive feature elimination (RF-RFE), and the Boruta algorithm to identify the most important features. Predictive models were developed using logistic regression (LR), random forest (RF), and eXtreme Gradient Boosting (XGBoost), with particle swarm optimization (PSO) used to optimize their hyperparameters. The SHapley Additive exPlanation (SHAP) method was applied to determine the importance of risk factors in the top-performing models.

RESULTS

For diagnosing DPN, the XGBoost model was most effective, achieving a recall of 83.7%, specificity of 86.8%, accuracy of 85.4%, and an F1 score of 83.7%. On the other hand, the RF model excelled in diagnosing LEAD, with a recall of 85.7%, specificity of 92.9%, accuracy of 91.9%, and an F1 score of 82.8%. SHAP analysis revealed top five critical risk factors shared by DPN and LEAD, including increased urinary albumin-to-creatinine ratio (UACR), glycosylated hemoglobin (HbA1c), serum creatinine (Scr), older age, and carotid stenosis. Additionally, distinct risk factors were pinpointed: decreased serum albumin and lower lymphocyte count were linked to DPN, while elevated neutrophil-to-lymphocyte ratio (NLR) and higher D-dimer levels were associated with LEAD.

CONCLUSIONS

This study demonstrated the effectiveness of ML models in predicting DPN and LEAD in diabetic patients and identified significant risk factors. Focusing on shared risk factors may greatly reduce the prevalence of both conditions, thereby mitigating the risk of developing DFUs.

Association between serum uric acid levels and diabetic peripheral neuropathy in type 2 diabetes: a systematic review and meta-analysis

Background

The evidence supporting a connection between elevated serum uric acid (SUA) levels and diabetic peripheral neuropathy (DPN) is controversial. The present study performed a comprehensive evaluation of this correlation by conducting a systematic review and meta-analysis of relevant research.

Method

PubMed, Web of Science (WOS), Embase, and the Cochrane Library were searched for published literature from the establishment of each database to January 8, 2024. In total, 5 cohort studies and 15 cross-sectional studies were included, and 2 researchers independently screened and extracted relevant data. R 4.3.0 was used to evaluate the included literature. The present meta-analysis evaluated the relationship between SUA levels and the risk of DPN in type 2 diabetes (T2DM) by calculating the ratio of means (RoM) and 95% confidence intervals (CIs) using the method reported by JO Friedrich, and it also analyzed continuous outcome measures using standardized mean differences (SMDs) and 95% CIs to compare SUA levels between DPN and non-DPN groups. Funnel plot and Egger's test were used to assess publication bias. Sensitivity analysis was conducted by sequentially removing each study one-by-one.

Results

The meta-analysis included 20 studies, with 12,952 T2DM patients with DPN and 16,246 T2DM patients without DPN. There was a significant correlation between SUA levels and the risk of developing DPN [odds ratio (OR) = 1.23; 95% CI: 1.07-1.41; p = 0.001]. Additionally, individuals with DPN had higher levels of SUA compared to those without DPN (SMD = 0.4; 95% CI: -0.11-0.91; p < 0.01).

Conclusion

T2DM patients with DPN have significantly elevated SUA levels, which correlate with a heightened risk of peripheral neuropathy. Hyperuricemia (HUA) may be a risk indicator for assessing the risk of developing DPN in T2DM patients.

Systematic review registration

https://www.crd.york.ac.uk/PROSPERO, identifier CRD42024500373.

Correlations between distal sensorimotor polyneuropathy and cardiovascular complications in diabetic patients in the North-Eastern region of Hungary

Distal sensorimotor polyneuropathy (DSPN) is the earliest detectable and the most frequent microvascular complication in diabetes mellitus. Several studies have previously demonstrated correlations between cardiovascular risk factors in diabetic patients and independent risk factors for diabetic neuropathy. Our objective was to retrospectively analyze data from diabetic patients in the North-East region of Hungary who underwent neuropathy screening at the Diabetic Neuropathy Center, University of Debrecen, between 2017 and 2021. We aimed to investigate the correlations between cardiovascular risk factors and microvascular complications among patients with DSPN. The median age of the patients was 67 years, 59,6% were female, and 91,1% had type 2 diabetes. The prevalence of DSPN among the study subjects was 71.7%. A significantly longer duration of diabetes (p<0.01) was noted in patients with DSPN. Those with DSPN demonstrated a significantly higher HbA1c level (p<0.001) and a greater frequency of insulin use (p = 0.001). We observed a significantly elevated albumin/creatinine ratio (p<0.001) and a significantly lower eGFR (p<0.001) in patients with DSPN. Diabetic retinopathy exhibited a significantly higher prevalence in patients with DSPN (p<0.001). A higher prevalence of myocardial infarction (p<0.05), ischemic heart disease (p<0.001), peripheral arterial disease (p<0.05) and a history of atherosclerosis (p<0.05) was observed in patients with DSPN. In a multivariate logistic regression analysis, the following factors were independently associated with the presence of DSPN: higher HbA1c (OR:2.58, 95% CI:1.89-3.52, p<0.001), age (OR:1.03, 95% CI:1.01-1.05, p = 0.006), albumin/creatinine ratio above 3 mg/mmol (OR:1.23, 95% CI:1.06-1.45, p = 0.008), retinopathy (OR:6.06, 95% CI:1.33-27.53, p = 0.02), and composite cardiovascular endpoint (OR:1.95, 95% CI:1.19-3.19, p = 0.008). Our study revealed that age, elevated HbA1c levels, significant albuminuria, retinopathy, and cardiovascular complications may increase the risk of DSPN. Further investigation of these associations is necessary to understand the impact of patient characteristics during the treatment of diabetic neuropathy.

HbA1c and the risk of developing peripheral neuropathy in childhood-onset type 1 diabetes: A follow-up study over 3 decades

AIMS

We have evaluated long-term weighted mean HbA1c (wHbA1c), HbA1c variability, diabetes duration, and lipid profiles in relation to the development of diabetic peripheral neuropathy (DPN), nephropathy, and retinopathy in childhood-onset type 1 diabetes.

MATERIALS AND METHODS

In a longitudinal cohort study, 49 patients (21 women) with childhood-onset type 1 diabetes were investigated with neurophysiological measurements, blood tests, and clinical examinations after a diabetes duration of 7.7 (±3.3) years (baseline) and followed with repeated examinations for 30.6 (±5.2) years. We calculated wHbA1c by integrating the area under all HbA1c values since the diabetes diagnosis. Lipid profiles were analysed in relation to the presence of DPN. Long-term fluctuations of HbA1c variability were computed as the standard deviation of all HbA1c measurements. Data regarding the presence of other diabetes complications were retrieved from medical records.

RESULTS

In this follow-up study, 51% (25/49) of the patients fulfilled electrophysiological criteria for DPN. In nerve conduction studies, there was a deterioration in the amplitudes and conduction velocities for the median, peroneal, and sural nerves over time. Patients with DPN had a longer duration of diabetes, higher wHbA1c, and increased HbA1c variability. The lowest wHbA1c value associated with the development of DPN was 62 mmol/mol (7.8%). The presence of albuminuria and retinopathy was positively correlated with the presence of neuropathy.

CONCLUSIONS

More than half of the patients had developed DPN after 30 years. None of the patients who developed DPN had a wHbA1c of less than 62 mmol/mol (7.8%).

Expert opinion on screening, diagnosis and management of diabetic peripheral neuropathy: a multidisciplinary approach

The proposed expert opinion aimed to address the current knowledge on conceptual, clinical, and therapeutic aspects of diabetic peripheral neuropathy (DPN) and to provide a guidance document to assist clinicians for the best practice in DPN care. The participating experts consider the suspicion of the disease by clinicians as a key factor in early recognition and diagnosis, emphasizing an improved awareness of the disease by the first-admission or referring physicians. The proposed "screening and diagnostic" algorithm involves the consideration of DPN in a patient with prediabetes or diabetes who presents with neuropathic symptoms and/or signs of neuropathy in the presence of DPN risk factors, with careful consideration of laboratory testing to rule out other causes of distal symmetric peripheral neuropathy and referral for a detailed neurological work-up for a confirmative test of either small or large nerve fiber dysfunction in atypical cases. Although, the first-line interventions for DPN are currently represented by optimized glycemic control (mainly for type 1 diabetes) and multifactorial intervention (mainly for type 2 diabetes), there is a need for individualized pathogenesis-directed treatment approaches for DPN. Alpha-lipoic acid (ALA) seems to be an important first-line pathogenesis-directed agent, given that it is a direct and indirect antioxidant that works with a strategy targeted directly against reactive oxygen species and indirectly in favor of endogenous antioxidant capacity for improving DPN conditions. There is still a gap in existing research in the field, necessitating well-designed, robust, multicenter clinical trials with sensitive endpoints and standardized protocols to facilitate the diagnosis of DPN via a simple and effective algorithm and to track progression of disease and treatment response. Identification of biomarkers/predictors that would allow an individualized approach from a potentially disease-modifying perspective may provide opportunities for novel treatments that would be efficacious in early stages of DPN, and may modify the natural course of the disease. This expert opinion document is expected to increase awareness among physicians about conceptual, clinical, and therapeutic aspects of DPN and to assist them in timely recognition of DPN and translating this information into their clinical practice for best practice in the management of patients with DPN.

Correlation and influencing factors of neurophysiological examinations and serum uric acid in patients with diabetic peripheral neuropathy: an exploratory study

OBJECTIVE

This study aimed to investigate the correlation and influencing factors between neurophysiological examinations, serum uric acid (SUA), and glucose metabolism in patients with Diabetic Peripheral Neuropathy (DPN).

METHODS

A total of 114 patients with DPN who received treatment at the Endocrinology Department of our hospital from January 2022 to December 2023 were included. According to the median blood uric acid level, the patients were divided into high SUA group and low SUA group, and the demographic data, blood glucose indexes and motor nerve electrophysiological examination results of the two groups were compared.

RESULTS

The level of FPG and HbA1c was higher in the high SUA group. The motor nerve latency of the high SUA group was higher, the motor nerve amplitude and motor nerve conduction velocity of the high SUA group were lower than those of the low SUA group. SUA was positively correlated with motor nerve latency and negatively correlated with motor nerve amplitude and conduction velocity.

CONCLUSION

In DPN, high SUA levels are associated with poor glycemic control. With the increase in SUA levels, the motor nerve latency in patients with T2DM is prolonged, and amplitude and conduction velocity decrease, and high SUA is a risk factor and potential predictor of DPN.

Evidence mapping of traditional Chinese medicine in diabetic peripheral neuropathy treatment

Objective: Diabetic peripheral neuropathy (DPN) stands as a crucial complication of diabetes, significantly affecting patients' quality of life. This study aims to elucidate the evidence distribution from clinical randomized controlled trials (RCTs) on DPN treatment with traditional Chinese medicine (TCM) through evidence mapping. Methods: A comprehensive search was conducted from January 2017 to October 2022 in databases such as Wanfang (China Online Journals), CNKI (China National Knowledge Infrastructure), VIP (China Science and Technology Journal Database), SinoMed (Chinese Biomedical Literature Database), PubMed, Web of Science, and Cochrane Library. Literature related to the treatment of DPN with TCM was selected. From the 1,229 RCTs identified over the past 6 years, relevant data were extracted. The evidence mapping approach was utilized, and trends in publications, study scales, intervention types, and evaluation indicators were analyzed using descriptive text combined with tables and bubble charts. Results: Research on the treatment of DPN with TCM is extensive. The publication trend remains relatively stable with predominantly smaller sample sizes. The main treatments encompass oral Chinese medicine and traditional external treatments. The most common evaluation indicators are neurophysiological, efficiency rate, symptom signs, neuropathy scores, and traditional Chinese symptoms, with less focus on psychological status and the ankle-brachial index (ABI). Conclusion: Shedding light on contemporary research, this study explores the current RCTs evaluating TCM's efficacy in treating DPN. The findings not only highlight the potential role of TCM in addressing diabetic complications but also underscore areas that could benefit from refined research approaches, expanded intervention methods, and broader assessment criteria. Our observations aim to inform and inspire future research directions and clinical practices concerning TCM's role in managing diabetes-associated complications.

Vitamin D deficiency increases the risk of diabetic peripheral neuropathy in elderly type 2 diabetes mellitus patients by predominantly increasing large-fiber lesions

AIMS

This study explores the link between Vitamin D deficiency (VDD) and diabetic peripheral neuropathy (DPN) in elderly type 2 diabetes mellitus (T2DM) patients.

METHODS

Involving 257 elderly T2DM patients, the study utilized propensity score matching to balance age, sex, and diabetes duration. VDD was defined as serum 25-hydroxyvitamin D [25(OH)D] levels below 20 ng/ml. Large nerve fiber lesions were evaluated by electromyogram, while small nerve fiber lesions were assessed by measuring skin conductance.

RESULTS

DPN patients had notably lower serum 25(OH)D levels than non-DPN patients [15.05 vs. 18.4 ng/ml, P = 0.018]. VDD was identified as an independent risk factor for DPN (odds ratio = 2.488, P = 0.008) in multivariate logistic regression analysis. Spearman's correlation showed negative correlations between serum 25(OH)D levels and specific nerve latencies, and positive correlations with specific nerve velocities and amplitudes. The VDD group exhibited longer median sensory nerve latencies and motor evoked potential latencies compared to the vitamin D-sufficient group. Further, VDD is associated with the prolongation of the median motor nerve latency (odds ratio = 1.362, P = 0.038).

CONCLUSIONS

VDD is independently associated with a higher risk of DPN. VDD may promote the development of DPN by affecting large nerve fibers.

Correlation study of renal function indices with diabetic peripheral neuropathy and diabetic retinopathy in T2DM patients with normal renal function

Background

The anticipation of diabetes-related complications remains a challenge for numerous T2DM patients, as there is presently no effective method for early prediction of these complications. This study aims to investigate the association between renal function-related indicators and the occurrence of peripheral neuropathy and retinopathy in individuals diagnosed with type 2 diabetes mellitus (T2DM) who currently have normal renal function.

Methods

Patients with T2DM who met the criteria were selected from the MMC database and divided into diabetic peripheral neuropathy (DPN) and diabetic retinopathy (DR) groups, with a total of 859 and 487 patients included, respectively. Multivariate logistic regression was used to analyze the relationship between blood urea nitrogen (BUN), creatinine (Cr), uric acid (UA), urine albumin(ALB), albumin-to-creatinine ratio (ACR), estimated glomerular filtration rate (eGFR), and diabetic peripheral neuropathy and retinopathy. Spearman correlation analysis was used to determine the correlation between these indicators and peripheral neuropathy and retinopathy in diabetes.

Results

In a total of 221 patients diagnosed with DPN, we found positive correlation between the prevalence of DPN and eGFR (18.2, 23.3, 35.7%, p < 0.05). Specifically, as BUN (T1: references; T2:OR:0.598, 95%CI: 0.403, 0.886; T3:OR:1.017, 95%CI: 0.702, 1.473; p < 0.05) and eGFR (T1: references; T2:OR:1.294, 95%CI: 0.857, 1.953; T3:OR:2.142, 95%CI: 1.425, 3.222; p < 0.05) increased, the odds ratio of DPN also increased. Conversely, with an increase in Cr(T1: references; T2:OR:0.86, 95%CI: 0.56, 1.33; T3:OR:0.57, 95%CI: 0.36, 0.91; p < 0.05), the odds ratio of DPN decreased. Furthermore, when considering sensitivity and specificity, eGFR exhibited a sensitivity of 65.2% and specificity of 54.4%, with a 95% confidence interval of 0.568-0.656.

Conclusion

In this experimental sample, we found a clear positive correlation between eGFR and DPN prevalence.

The role of C-peptide in diabetes and its complications: an updated review

Worldwide, diabetes and its complications have seriously affected people's quality of life and become a serious public health problem. C-peptide is not only an indicator of pancreatic β-cell function, but also a biologically active peptide that can bind to cell membrane surface signaling molecules and activate downstream signaling pathways to play antioxidant, anti-apoptotic and inflammatory roles, or regulate cellular transcription through internalization. It is complex how C-peptide is related to diabetic complications. Both deficiencies and overproduction can lead to complications, but their mechanisms of action may be different. C-peptide replacement therapy has shown beneficial effects on diabetic complications in animal models when C-peptide is deficient, but results from clinical trials have been unsatisfactory. The complex pattern of the relationship between C-peptide and diabetic chronic complications has not yet been fully understood. Future basic and clinical studies of C-peptide replacement therapies will need to focus on baseline levels of C-peptide in addition to more attention also needs to be paid to post-treatment C-peptide levels to explore the optimal range of fasting C-peptide and postprandial C-peptide maintenance.