Painful Diabetic Peripheral Neuropathy: Practical Guidance and Challenges for Clinical Management

Painful diabetic peripheral neuropathy (PDPN) is present in nearly a quarter of people with diabetes. It is estimated to affect over 100 million people worldwide. PDPN is associated with impaired daily functioning, depression, sleep disturbance, financial instability, and a decreased quality of life. Despite its high prevalence and significant health burden, it remains an underdiagnosed and undertreated condition. PDPN is a complex pain phenomenon with the experience of pain associated with and exacerbated by poor sleep and low mood. A holistic approach to patient-centred care alongside the pharmacological therapy is required to maximise benefit. A key treatment challenge is managing patient expectation, as a good outcome from treatment is defined as a reduction in pain of 30-50%, with a complete pain-free outcome being rare. The future for the treatment of PDPN holds promise, despite a 20-year void in the licensing of new analgesic agents for neuropathic pain. There are over 50 new molecular entities reaching clinical development and several demonstrating benefit in early-stage clinical trials. We review the current approaches to its diagnosis, the tools, and questionnaires available to clinicians, international guidance on PDPN management, and existing pharmacological and non-pharmacological treatment options. We synthesise evidence and the guidance from the American Association of Clinical Endocrinology, American Academy of Neurology, American Diabetes Association, Diabetes Canada, German Diabetes Association, and the International Diabetes Federation into a practical guide to the treatment of PDPN and highlight the need for future research into mechanistic-based treatments in order to prioritise the development of personalised medicine

Use of Factory-Calibrated Real-time Continuous Glucose Monitoring Improves Time in Target and HbA1c in a Multiethnic Cohort of Adolescents and Young Adults With Type 1 Diabetes:The MILLENNIALS Study

OBJECTIVEInternational type 1 diabetes registries have shown that HbA1c levels are highest in young people with type 1 diabetes; however, improving their glycemic control remains a challenge. We propose that use of the factory-calibrated Dexcom G6 CGM system would improve glycemic control in this cohort.RESEARCH DESIGN AND METHODSWe conducted a randomized crossover trial in young people with type 1 diabetes (16–24 years old) comparing the Dexcom G6 CGM system and self-monitoring of blood glucose (SMBG). Participants were assigned to the interventions in random order during two 8-week study periods. During SMBG, blinded continuous glucose monitoring (CGM) was worn by each participant for 10 days at the start, week 4, and week 7 of the control period. HbA1c measurements were drawn after enrollment and before and after each treatment period. The primary outcome was time in range 70–180 mg/dL.RESULTSTime in range was significantly higher during CGM compared with control (35.7 ± 13.5% vs. 24.6 ± 9.3%; mean difference 11.1% [95% CI 7.0–15.2]; P < 0.001). CGM use reduced mean sensor glucose (219.7 ± 37.6 mg/dL vs. 251.9 ± 36.3 mg/dL; mean difference −32.2 mg/dL [95% CI −44.5 to −20.0]; P < 0.001) and time above range (61.7 ± 15.1% vs. 73.6 ± 10.4%; mean difference 11.9% [95% CI −16.4 to −7.4]; P < 0.001). HbA1c level was reduced by 0.76% (95% CI −1.1 to −0.4) (−8.5 mmol/mol [95% CI −12.4 to −4.6]; P < 0.001). Times spent below range (<70 mg/dL and <54 mg/dL) were low and comparable during both study periods. Sensor wear was 84% during the CGM period.CONCLUSIONSCGM use in young people with type 1 diabetes improves time in target and HbA1c levels compared with SMBG

Corneal nerve fractal dimension: a novel corneal nerve metric for the diagnosis of diabetic sensorimotor polyneuropathy

Objective: Corneal confocal microscopy (CCM), an in vivo ophthalmic imaging modality, is a noninvasive and objective imaging biomarker for identifying small nerve fiber damage. We have evaluated the diagnostic performance of previously established CCM parameters to a novel automated measure of corneal nerve complexity called the corneal nerve fiber fractal dimension (ACNFrD). Methods: A total of 176 subjects (84 controls and 92 patients with type 1 diabetes) with and without diabetic sensorimotor polyneuropathy (DSPN) underwent CCM. Fractal dimension analysis was performed on CCM images using purpose-built corneal nerve analysis software, and compared with previously established manual and automated corneal nerve fiber measurements. Results: Manual and automated subbasal corneal nerve fiber density (CNFD) (P < 0.0001), length (CNFL) (P < 0.0001), branch density (CNBD) (P < 0.05), and ACNFrD (P < 0.0001) were significantly reduced in patients with DSPN compared to patients without DSPN. The areas under the receiver operating characteristic curves for identifying DSPN were comparable: 0.77 for automated CNFD, 0.74 for automated CNFL, 0.69 for automated CNBD, and 0.74 for automated ACNFrD. Conclusions: ACNFrD shows comparable diagnostic efficiency to identify diabetic patients with and without DSPN

Artificial Intelligence Based Analysis of Corneal Confocal Microscopy Images for Diagnosing Peripheral Neuropathy: A Binary Classification Model

Diabetic peripheral neuropathy (DPN) is the leading cause of neuropathy worldwide resulting in excess morbidity and mortality. We aimed to develop an artificial intelligence deep learning algorithm to classify the presence or absence of peripheral neuropathy (PN) in participants with diabetes or pre-diabetes using corneal confocal microscopy (CCM) images of the sub-basal nerve plexus. A modified ResNet-50 model was trained to perform the binary classification of PN (PN+) versus no PN (PN-) based on the Toronto consensus criteria. A dataset of 279 participants (149 PN-, 130 PN+) was used to train (n = 200), validate (n = 18), and test (n = 61) the algorithm, utilizing one image per participant. The dataset consisted of participants with type 1 diabetes (n = 88), type 2 diabetes (n = 141), and pre-diabetes (n = 50). The algorithm was evaluated using diagnostic performance metrics and attribution-based methods (gradient-weighted class activation mapping (Grad-CAM) and Guided Grad-CAM). In detecting PN+, the AI-based DLA achieved a sensitivity of 0.91 (95%CI: 0.79-1.0), a specificity of 0.93 (95%CI: 0.83-1.0), and an area under the curve (AUC) of 0.95 (95%CI: 0.83-0.99). Our deep learning algorithm demonstrates excellent results for the diagnosis of PN using CCM. A large-scale prospective real-world study is required to validate its diagnostic efficacy prior to implementation in screening and diagnostic programmes

Corneal Confocal Microscopy to Image Small Nerve Fiber Degeneration: Ophthalmology Meets Neurology.

Neuropathic pain has multiple etiologies, but a major feature is small fiber dysfunction or damage. Corneal confocal microscopy (CCM) is a rapid non-invasive ophthalmic imaging technique that can image small nerve fibers in the cornea and has been utilized to show small nerve fiber loss in patients with diabetic and other neuropathies. CCM has comparable diagnostic utility to intraepidermal nerve fiber density for diabetic neuropathy, fibromyalgia and amyloid neuropathy and predicts the development of diabetic neuropathy. Moreover, in clinical intervention trials of patients with diabetic and sarcoid neuropathy, corneal nerve regeneration occurs early and precedes an improvement in symptoms and neurophysiology. Corneal nerve fiber loss also occurs and is associated with disease progression in multiple sclerosis, Parkinson's disease and dementia. We conclude that corneal confocal microscopy has good diagnostic and prognostic capability and fulfills the FDA criteria as a surrogate end point for clinical trials in peripheral and central neurodegenerative diseases

Diagnosing and managing diabetic somatic and autonomic neuropathy

The diagnosis and management of diabetic neuropathy can be a major challenge. Late diagnosis contributes to significant morbidity in the form of painful diabetic neuropathy, foot ulceration, amputation, and increased mortality. Both hyperglycaemia and cardiovascular risk factors are implicated in the development of somatic and autonomic neuropathy and an improvement in these risk factors can reduce their rate of development and progression. There are currently no US Food and Drug Administration (FDA)-approved disease-modifying treatments for either somatic or autonomic neuropathy, as a consequence of multiple failed phase III clinical trials. While this may be partly attributed to premature translation, there are major shortcomings in trial design and outcome measures. There are a limited number of partially effective FDA-approved treatments for the symptomatic relief of painful diabetic neuropathy and autonomic neuropathy

Bariatric Surgery Leads to a Reduction in Antibodies to Apolipoprotein A-1: a Prospective Cohort Study

Purpose: Autoantibodies against apolipoprotein A-1 have been associated with cardiovascular disease, poorer CV outcomes and all-cause mortality in obese individuals. The impact of bariatric surgery (BS) on the presence of circulating anti-apoA-1 IgG antibodies is unknown. This study aimed to determine the effect of bariatric surgery on auto-antibodies titres against Apolipoprotein A-1 (anti-apoA-1 IgG), looking for changes associated with lipid parameters, insulin resistance, inflammatory profile and percentage of excess body mass index loss (%EBMIL).Materials and methods: We assessed 55 patients (40 women) before, 6 and 12 months post-operatively. Baseline and post-operative clinical history and measurements of body mass index (BMI), serum cholesterol, triglycerides, high- and low-density lipoprotein cholesterol (HDL-C and LDL-C), apoA-1, highly sensitive C-reactive protein (hsCRP), fasting glucose (FG), glycated haemoglobin (HbA1c) and HOMA-IR were taken at each point. Human anti-apoA-1 IgG were measured by ELISA.Results: The mean age of participants was 50 years. BS significantly improved BMI, %EBMIL triglycerides, HDL-C, apoA-1, hsCRP, HBA1c, FG and HOMA-IR. Baseline anti-apoA-1 IgG seropositivity was 25% and was associated with lower apoA-1 and higher hsCRP levels. One year after BS, anti-apoA-1 IgG seropositivity decreased to 15% (p = 0.007) and median anti-apoA-1 IgG values decreased from 0.70 (0.56-0.84) to 0.47 (0.37-0.61) AU (p Conclusion: Bariatric surgery results in significant reduction in anti-apoA-1 IgG levels, which may adversely influence weight loss. The exact mechanisms underpinning these results are elusive and require further study before defining any clinical recommendations.</p