An unbiased stereological method for corneal confocal microscopy in patients with diabetic polyneuropathy

Cardiovascular autonomic neuropathy in patients with type 2 diabetes with and without sensorimotor polyneuropathy

BACKGROUND AND AIMS

Cardiovascular autonomic neuropathy (CAN) in patients with diabetes is associated with poor prognosis. We aimed to assess signs of CAN and autonomic symptoms and to investigate the impact of sensorimotor neuropathy on CAN by examining type 2 diabetes patients with (DPN [distal sensorimotor polyneuropathy]) and without distal sensorimotor polyneuropathy (noDPN) and healthy controls (HC). Secondarily, we aimed to describe the characteristics of patients with CAN.

METHODS

A population of 374 subjects from a previously described cohort of the Danish Centre for Strategic Research in Type 2 Diabetes (DD2) were included. Subjects were examined with the Vagus™ device for the diagnosis of CAN, where two or more abnormal cardiovascular autonomic reflex tests indicate definite CAN. Autonomic symptoms were assessed with Composite Autonomic Symptom Score 31 (COMPASS 31) questionnaire. DPN was defined according to the Toronto consensus panel definition.

RESULTS

Definite CAN was present in 22% with DPN, 7% without DPN and 3% of HC, and 91% of patients with definite CAN had DPN. Patients with DPN and definite CAN reported higher COMPASS 31 scores compared to patients with noDPN (20.0 vs. 8.3, p < 0.001) and no CAN (22.1 vs. 12.3, p = 0.01). CAN was associated with HbA1c and age in a multivariate logistic regression analysis but was not associated with IEFND or triglycerides.

INTERPRETATION

One in five patients with DPN have CAN and specific CAN characteristics may help identify patients at risk for developing this severe diabetic complication. Autonomic symptoms were strongly associated with having both DPN and CAN, but too unspecific for diagnosing CAN.

Assessing Corneal Confocal Microscopy and Other Small Fiber Measures in Diabetic Polyneuropathy

BACKGROUND AND OBJECTIVES

Damage to small nerve fibers is common in diabetic polyneuropathy (DPN), and the diagnosis of DPN relies on subjective symptoms and signs in a combination with objective confirmatory tests, typically electrophysiology or intraepidermal nerve fiber density (IENFD) from skin biopsy. Corneal confocal microscopy (CCM) has been introduced as a tool to detect DPN. However, it is unclear if CCM can reliably be used to diagnose DPN and how the technique compares with other commonly used measures of small fiber damage, such as IENFD, cold detection threshold (CDT), and warm detection threshold (WDT). Therefore, we assessed and compared the use of CCM, IENFD, CDT, and WDT in the diagnosis of DPN in patients with type 2 diabetes.

METHODS

In this cohort study, the participants underwent detailed neurologic examination, electrophysiology, quantification of IENFD, CCM, and quantitative sensory testing. Definition of DPN was made in accordance with the Toronto criteria for diabetic neuropathy (without relying on IENFD and thermal thresholds).

RESULTS

A total of 214 patients with at least probable DPN, 63 patients without DPN, and 97 controls without diabetes were included. Patients with DPN had lower CCM measures (corneal nerve fiber length [CNFL], nerve fiber density, and branch density), IENFD, CDT, and WDT compared with patients without DPN (p ≤ 0.001, <0.001, 0.002, p < 0.001, p = 0.003, and <0.005, respectively), whereas there was no difference between controls and patients with diabetes without DPN. All 3 CCM measures showed a very low diagnostic sensitivity with CNFL showing the highest (14.4% [95% CI 9.8-18.4]) and a specificity of 95.7% (88.0-99.1). In comparison, the sensitivity of abnormal CDT and/or WDT was 30.5% (24.4-37.0) with a specificity of 84.9% (74.6-92.2). The sensitivity of abnormal IENFD was highest among all measures with a value of 51.1% (43.7-58.5) and a specificity of 90% (79.5-96.2). CCM measures did not correlate with IENFD, CDT/WDT, or neuropathy severity in the group of patients with DPN.

DISCUSSION

CCM measures showed the lowest sensitivity compared with other small fiber measures in the diagnosis of DPN. This indicates that CCM is not a sensitive method to detect DPN in recently diagnosed type 2 diabetes.

CLASSIFICATION OF EVIDENCE

This study provides Class III evidence that CCM measures aid in the detection of DPN in recently diagnosed type 2 diabetics but with a low sensitivity when compared with other small fiber measures.

Diabetic Corneal Neuropathy: Pathogenic Mechanisms and Therapeutic Strategies

Diabetes mellitus (DM) is a major global public health problem that can cause complications such as diabetic retinopathy, diabetic neuropathy, and diabetic nephropathy. Besides the reporting of reduction in corneal nerve density and decrease in corneal sensitivity in diabetic patients, there may be a subsequent result in delayed corneal wound healing and increased corneal infections. Despite being a potential cause of blindness, these corneal nerve changes have not gained enough attention. It has been proposed that corneal nerve changes may be an indicator for diabetic neuropathy, which can provide a window for early diagnosis and treatment. In this review, the authors aimed to give an overview of the relationship between corneal nerves and diabetic neuropathy as well as the underlying pathophysiological mechanisms of corneal nerve fiber changes caused by DM for improved prediction and prevention of diabetic neuropathy. In addition, the authors summarized current and novel therapeutic methods for delayed corneal wound healing, nerve protection and regeneration in the diabetic cornea.

Diabetes Distal Peripheral Neuropathy: Subtypes and Diagnostic and Screening Technologies

Diabetes distal symmetrical peripheral neuropathy (DSPN) is the most prevalent form of neuropathy in industrialized countries, substantially increasing risk for morbidity and pre-mature mortality. DSPN may manifest with small-fiber disease, large-fiber disease, or a combination of both. This review summarizes: (1) DSPN subtypes (small- and large-fiber disease) with attention to clinical signs and patient symptoms; and (2) technological diagnosis and screening for large- and small-fiber disease with inclusion of a comprehensive literature review of published studies from 2015-present (N = 66). Review findings, informed by the most up-to-date research, advance critical understanding of DSPN large- and small-fiber screening technologies, including those designed for point-of-care use in primary care and endocrinology practices.

Corneal confocal microscopy for the diagnosis of diabetic peripheral neuropathy: A systematic review and meta-analysis

INTRODUCTION

Corneal confocal microscopy (CCM) is a rapid non-invasive ophthalmic imaging technique that identifies corneal nerve fiber damage. Small studies suggest that CCM could be used to assess patients with diabetic peripheral neuropathy (DPN).

AIM

To undertake a systematic review and meta-analysis assessing the diagnostic utility of CCM for sub-clinical DPN (DPN- ) and established DPN (DPN+ ).

DATA SOURCES

Databases (PubMed, Embase, Central, ProQuest) were searched for studies using CCM in patients with diabetes up to April 2020.

STUDY SELECTION

Studies were included if they reported on at least one CCM parameter in patients with diabetes.

DATA EXTRACTION

Corneal nerve fiber density (CNFD), corneal nerve branch density (CNBD), corneal nerve fiber length (CNFL), and inferior whorl length (IWL) were compared between patients with diabetes with and without DPN and controls. Meta-analysis was undertaken using RevMan V.5.3.

DATA SYNTHESIS

Thirty-eight studies including ~4,000 participants were included in this meta-analysis. There were significant reductions in CNFD, CNBD, CNFL, and IWL in DPN- vs controls (P < 0.00001), DPN+ vs controls (P < 0.00001), and DPN+ vs DPN- (P < 0.00001).

CONCLUSION

This systematic review and meta-analysis shows that CCM detects small nerve fiber loss in subclinical and clinical DPN and concludes that CCM has good diagnostic utility in DPN.

Intraepidermal Nerve Fiber Density as Measured by Skin Punch Biopsy as a Marker for Small Fiber Neuropathy: Application in Patients with Fibromyalgia

Small fiber neuropathy (SFN) is a type of peripheral neuropathy that occurs from damage to the small A-delta and C nerve fibers that results in the clinical condition known as SFN. This pathology may be the result of metabolic, toxic, immune-mediated, and/or genetic factors. Small fiber symptoms can be variable and inconsistent and therefore require an objective biomarker confirmation. Small fiber dysfunction is not typically captured by diagnostic tests for large-fiber neuropathy (nerve conduction and electromyographic study). Therefore, skin biopsies stained with PGP 9.5 are the universally recommended objective test for SFN, with quantitative sensory tests, autonomic function testing, and corneal confocal imaging as secondary or adjunctive choices. Fibromyalgia (FM) is a heterogenous syndrome that has many symptoms that overlap with those found in SFN. A growing body of research has shown approximately 40-60% of patients carrying a diagnosis of FM have evidence of SFN on skin punch biopsy. There is currently no clearly defined phenotype in FM at this time to suggest whom may or may not have SFN, though research suggests it may correlate with severe cases. The skin punch biopsy provides an objective tool for use in quantifying small fiber pathology in FM. Skin punch biopsy may also be repeated for surveillance of the disease as well as measuring response to treatments. Evaluation of SFN in FM allows for better classification of FM and guidance for patient care as well as validation for their symptoms, leading to better use of resources and outcomes.

Painful and non-painful diabetic neuropathy, diagnostic challenges and implications for future management

Peripheral neuropathy is one of the most common complications of both type 1 and type 2 diabetes. Up to half of patients with diabetes develop neuropathy during the course of their disease, which is accompanied by neuropathic pain in 30-40% of cases. Peripheral nerve injury in diabetes can manifest as progressive distal symmetric polyneuropathy, autonomic neuropathy, radiculo-plexopathies, and mononeuropathies. The most common diabetic neuropathy is distal symmetric polyneuropathy, which we will refer to as DN, with its characteristic glove and stocking like presentation of distal sensory or motor function loss. DN or its painful counterpart, painful DN, are associated with increased mortality and morbidity; thus, early recognition and preventive measures are essential. Nevertheless, it is not easy to diagnose DN or painful DN, particularly in patients with early and mild neuropathy, and there is currently no single established diagnostic gold standard. The most common diagnostic approach in research is a hierarchical system, which combines symptoms, signs, and a series of confirmatory tests. The general lack of long-term prospective studies has limited the evaluation of the sensitivity and specificity of new morphometric and neurophysiological techniques. Thus, the best paradigm for screening DN and painful DN both in research and in clinical practice remains uncertain. Herein, we review the diagnostic challenges from both clinical and research perspectives and their implications for managing patients with DN. There is no established DN treatment, apart from improved glycaemic control, which is more effective in type 1 than in type 2 diabetes, and only symptomatic management is available for painful DN. Currently, less than one-third of patients with painful DN derive sufficient pain relief with existing pharmacotherapies. A more precise and distinct sensory profile from patients with DN and painful DN may help identify responsive patients to one treatment versus another. Detailed sensory profiles will lead to tailored treatment for patient subgroups with painful DN by matching to novel or established DN pathomechanisms and also for improved clinical trials stratification. Large randomized clinical trials are needed to identify the interventions, i.e. pharmacological, physical, cognitive, educational, etc., which lead to the best therapeutic outcomes.