A clinical screening score for diabetic polyneuropathy: KORA F4 and AusDiab studies

Prediction Model for Polyneuropathy in Recent-Onset Diabetes Based on Serum Neurofilament Light Chain, Fibroblast Growth Factor-19 and Standard Anthropometric and Clinical Variables

BACKGROUND

Diabetic sensorimotor polyneuropathy (DSPN) is often asymptomatic and remains undiagnosed. The ability of clinical and anthropometric variables to identify individuals likely to have DSPN might be limited. Here, we aimed to integrate protein biomarkers for reliably predicting present DSPN.

METHODS

Using the proximity extension assay, we measured 135 neurological and protein biomarkers of inflammation in blood samples of 423 individuals with recent-onset diabetes from the German Diabetes Study (GDS). DSPN was diagnosed based on the Toronto Consensus Criteria. We constructed (i) a protein-based prediction model using LASSO logistic regression, (ii) an optimised traditional risk model with age, sex, waist circumference, height and diabetes type and (iii) a model combining both. All models were bootstrapped to assess the robustness, and optimism-corrected AUCs (95% CI) were reported.

RESULTS

DSPN was present in 16% of the study population. LASSO logistic regression selected the neurofilament light chain (NFL) and fibroblast growth factor-19 (FGF-19) as the most predictive protein biomarkers for detecting DSPN in individuals with recent-onset diabetes. The protein-based model achieved an AUC of 0.66 (0.59, 0.73), while the traditional risk model had an AUC of 0.66 (0.61, 0.74). However, combined features boosted the model performance to an AUC of 0.72 (0.67, 0.79).

CONCLUSION

We developed a prediction model for DSPN in recent-onset diabetes based on two protein biomarkers and five standard anthropometric, demographic and clinical variables. The model has a fair discrimination performance and might be used to inform the referral of patients for further testing.

Development and validation of a risk prediction model for early diabetic peripheral neuropathy based on a systematic review and meta-analysis

Background

Early identification and intervention of diabetic peripheral neuropathy is beneficial to improve clinical outcome.

Objective

To establish a risk prediction model for diabetic peripheral neuropathy (DPN) in patients with type 2 diabetes mellitus (T2DM).

Methods

The derivation cohort was from a meta-analysis. Risk factors and the corresponding risk ratio (RR) were extracted. Only risk factors with statistical significance were included in the model and were scored by their weightings. An external cohort were used to validate this model. The outcome was the occurrence of DPN.

Results

A total of 95,604 patients with T2DM from 18 cohorts were included. Age, smoking, body mass index, duration of diabetes, hemoglobin A1c, low HDL-c, high triglyceride, hypertension, diabetic retinopathy, diabetic kidney disease, and cardiovascular disease were enrolled in the final model. The highest score was 52.0. The median follow-up of validation cohort was 4.29 years. The optimal cut-off point was 17.0, with a sensitivity of 0.846 and a specificity of 0.668, respectively. According to the total scores, patients from the validation cohort were divided into low-, moderate-, high- and very high-risk groups. The risk of developing DPN was significantly increased in moderate- (RR 3.3, 95% CI 1.5-7.2, P = 0.020), high- (RR 15.5, 95% CI 7.6-31.6, P < 0.001), and very high-risk groups (RR 45.0, 95% CI 20.5-98.8, P < 0.001) compared with the low-risk group.

Conclusion

A risk prediction model for DPN including 11 common clinical indicators were established. It is a simple and reliable tool for early prevention and intervention of DPN in patients with T2DM.

American Association of Clinical Endocrinology Clinical Practice Guideline: Developing a Diabetes Mellitus Comprehensive Care Plan-2022 Update

OBJECTIVE

The objective of this clinical practice guideline is to provide updated and new evidence-based recommendations for the comprehensive care of persons with diabetes mellitus to clinicians, diabetes-care teams, other health care professionals and stakeholders, and individuals with diabetes and their caregivers.

METHODS

The American Association of Clinical Endocrinology selected a task force of medical experts and staff who updated and assessed clinical questions and recommendations from the prior 2015 version of this guideline and conducted literature searches for relevant scientific papers published from January 1, 2015, through May 15, 2022. Selected studies from results of literature searches composed the evidence base to update 2015 recommendations as well as to develop new recommendations based on review of clinical evidence, current practice, expertise, and consensus, according to established American Association of Clinical Endocrinology protocol for guideline development.

RESULTS

This guideline includes 170 updated and new evidence-based clinical practice recommendations for the comprehensive care of persons with diabetes. Recommendations are divided into four sections: (1) screening, diagnosis, glycemic targets, and glycemic monitoring; (2) comorbidities and complications, including obesity and management with lifestyle, nutrition, and bariatric surgery, hypertension, dyslipidemia, retinopathy, neuropathy, diabetic kidney disease, and cardiovascular disease; (3) management of prediabetes, type 2 diabetes with antihyperglycemic pharmacotherapy and glycemic targets, type 1 diabetes with insulin therapy, hypoglycemia, hospitalized persons, and women with diabetes in pregnancy; (4) education and new topics regarding diabetes and infertility, nutritional supplements, secondary diabetes, social determinants of health, and virtual care, as well as updated recommendations on cancer risk, nonpharmacologic components of pediatric care plans, depression, education and team approach, occupational risk, role of sleep medicine, and vaccinations in persons with diabetes.

CONCLUSIONS

This updated clinical practice guideline provides evidence-based recommendations to assist with person-centered, team-based clinical decision-making to improve the care of persons with diabetes mellitus.

Association of persistent organic pollutants with sensorimotor neuropathy in participants with and without diabetes or prediabetes: Results from the population-based KORA FF4 study

BACKGROUND

Concentrations of persistent organic pollutants (POPs) have been associated with an increased type 2 diabetes (T2D) risk. It remains unclear whether POPs are also associated with the risk of diabetes complications including neuropathy and evidence on this topic is scarce. We aimed to investigate the hypothesis that low-dose background concentrations of POPs were positively associated with distal sensorimotor polyneuropathy (DSPN).

METHODS

This cross-sectional study was based on data from the second follow-up (FF4, 2013-2014, N = 2279) of the population-based KORA S4 study (Augsburg, Germany). The study sample consisted of 200 participants, including four groups of 50 persons each with known T2D, prediabetes, newly diagnosed diabetes, and normal glucose tolerance (NGT) based on an oral glucose tolerance test. We analyzed the association of six most abundant serum concentrations of POPs, including polychlorinated biphenyls (PCBs) as well as organochlorine (OC) pesticides, with DSPN by multivariable logistic regression adjusted for age, sex, glycaemic status, body mass index, physical activity, smoking and alcohol consumption. We assessed effect modification by age, sex, glycaemic status and obesity and conducted two-pollutant models to check the robustness of the estimates.

RESULTS

For all pollutants, the main models indicated no significant association of having DSPN but pointed to rather decreased odds for DSPN. Two-pollutant models supported these findings, though only the association between the combination of PCB-138 and beta-hexachlorocyclohexane (β-HCH) (OR: 0.59; 95% CI: 0.35-0.99) with DSPN became significant. No effect modification was found by age, sex, glycaemic status and obesity.

CONCLUSION

Low-dose concentrations of POPs were not associated with increased odds of having DSPN in T2D, prediabetes and NGT.

Novel Insights into Sensorimotor and Cardiovascular Autonomic Neuropathy from Recent-Onset Diabetes and Population-Based Cohorts

The most prevalent chronic complications of diabetes are diabetic neuropathies, among which distal sensorimotor polyneuropathy (DSPN) and cardiovascular autonomic neuropathy (CAN) are the best studied. Their major clinical sequelae such as foot ulcers, neuropathic pain, and orthostatic hypotension are associated with lower quality of life and increased risk of mortality. Here we discuss the recent insights into DSPN and CAN focusing on two prospective cohorts; that is, the German Diabetes Study (GDS) including recent-onset diabetes patients and the population-based Cooperative Health Research in the Region of Augsburg, Germany (KORA) surveys. The insights from these studies investigating novel tools for early detection and prediction of (pre)diabetic neuropathy as well as biomarkers of oxidative stress and inflammation should ultimately culminate in improving the health care of patients affected by this serious condition.

The Quest for more Research on Painful Diabetic Neuropathy

A 62-year-old diabetologist diagnosed himself to have diabetes type-2, with an HbA1c of 9.5. Five months after lifestyle intervention and a multi-drug approach, HbA1c was 6.3, systolic blood pressure was below 135mmHg and BMI reduced to 27. But he suffered from severe painful diabetic neuropathy. Therefore he decided to visit his friend, a famous neuroscientist at an even more famous university. He asked him several plain questions: 1. What is the natural course of painful diabetic neuropathy? 2. Why do I have, despite almost normalizing HbA1c, more problems than before? 3. Are you sure my problems are due to diabetes or should we do a nerve biopsy? 4. Are there imaging techniques helpful for the diagnosis of this diabetic complication, starting in the distal nerve endings of the foot and slowly moving ahead? 5. Can you suggest any drug, specific and effective, for relieving painful diabetic neuropathy? This review will use the experts' answers to the questions of the diabetologist, not only to give a summary of the current knowledge, but even more to highlight areas of research needed for improving the fate of patients with painful diabetic neuropathy. Based on the unknowns, which exceed the knowns in diabetic neuropathy, a quest for more public support of research is made.

Trends of barriers to eye care among adults with diagnosed diabetes in Germany, 1997-2012

BACKGROUND AND AIMS

To study trends of barriers to receiving recommended eye care among subjects with diabetes aged 20-81 years in northeast Germany.

METHODS AND RESULTS

We analyzed population-based data from two repeated cross-sectional surveys conducted in 1997-2001 and 2008-2012 (Ns of 4308 and 4402). Andersen's Behavioral Model of Health Services Utilization was used to identify individual-level demographic, financial and health-related barriers to annual eye-care utilization in subjects with a self-reported physician's diabetes and to examine population trends in these barriers. The prevalence of diabetes increased from 6.5% to 11.4%. The prevalence of annual eye-care utilization among persons with diabetes decreased from 69.4% to 56.0% (adjusted relative risk = 0.77, p < 0.001). The decline of eye care utilization over the past decade in eye-care use was more pronounced in groups at risk for diabetes-related complications (i.e., lower socio-economic status, >5 years since diagnosis of diabetes, poor glycemic control, obesity, smoking, lack of physical activity, co-existing diseases). We identified relevant predictors of missed annual eye-care use among diabetics.

CONCLUSION

The increase of diabetes prevalence and downward trend of eye-care visits at the recommended level call for development, implementation and evaluation of continued efforts to improve access to eye specialists, particularly among those with poor diabetic control, co-existing diabetic complications, and comorbidities.