Corneal Confocal Microscopy in the Diagnosis of Small Fiber Neuropathy: Faster, Easier, and More Efficient Than Skin Biopsy?

Recommendations on neurologic, cognitive, and psychiatric manifestations in patients with Sjögren's disease by the Brazilian Society of Rheumatology

BACKGROUND

Neurological and psychiatric manifestations occur in patients with primary Sjogren's disease (SjD) with a wide-ranging clinical presentation, affecting quality of life, social participation, and prognosis. Despite this, neither central nor peripheral neurological symptoms are systematically evaluated in the context of autoimmunity or identified as manifestations of SjD. The EULAR Sjogren's Syndrome Disease Activity Index (ESSDAI) covers only part of them in the neurological domain.

METHODS

We performed a systematic review of the diagnosis and prevalence of central, peripheral, and autonomic nervous system manifestations in primary SjD, following the recommendations proposed by the Cochrane Collaboration Handbook. Observational studies were included when their main issue was the diagnosis and the prevalence of the manifestations individually. We employed a generalized linear mixed model (GLMM) method with a random-effects model, and the results were computed using logit transformation, implemented through the 'meta' and 'metafor' packages in the R software (version 3.6.1). To present these recommendations, agreement among experts was investigated using the Delphi method in in-person meetings.

RESULTS

We propose ten recommendations regarding the investigation and management of neurological involvement in SjD that had 100% agreement among participants.

CONCLUSION

These recommendations add to the literature on the clinical care of patients with SjD.

Small fiber neuropathy in the post-COVID condition and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: Clinical significance and diagnostic challenges

BACKGROUND

Patients with post-COVID condition (PCC) and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) experience symptoms potentially associated with small fiber neuropathy (SFN).

METHODS

A sample of 90 participants, comprising 30 PCC patients, 30 ME/CFS patients, and 30 healthy controls (HC), matched by sex and age, was assessed. Neuropathic, autonomic, and fatigue symptoms were measured with TaskForce Monitor, the Sudoscan, heat and cold evoked potentials, In Vivo Corneal Confocal Microscopy (IVCCM), and specialized questionaries.

RESULTS

PCC and ME/CFS patients demonstrated significantly higher levels of autonomic symptoms (H = 39.89, p < 0.001), neuropathic symptoms (H = 48.94, p < 0.001), and fatigue (H = 49.29, p < 0.001) compared to HC. Quantitative sensory testing revealed significant differences in heat detection thresholds between PCC patients and HC (F = 4.82; p < 0.01). Regarding corneal small fiber tortuosity, there were statistically significant differences between patients and HC (F = 6.80; p < 0.01), indicating pathological responses in patients. Small fiber tortuosity in IVCCM was identified as the main discriminator between patients and HC (AUC = 0.720; p < 0.01).

CONCLUSION

PCC and ME/CFS patients demonstrated sensory SFN, as evidenced by impaired heat detection and increased tortuosity of small fibers in the central corneal subbasal plexus. The findings underscore the importance of a multimodal approach to comprehensively detect and characterize SFN. This study provides valuable scientific insights into the neuropathic manifestations associated with these conditions.

Artificial Intelligence to Diagnose Complications of Diabetes

Artificial intelligence (AI) is increasingly being used to diagnose complications of diabetes. Artificial intelligence is technology that enables computers and machines to simulate human intelligence and solve complicated problems. In this article, we address current and likely future applications for AI to be applied to diabetes and its complications, including pharmacoadherence to therapy, diagnosis of hypoglycemia, diabetic eye disease, diabetic kidney diseases, diabetic neuropathy, diabetic foot ulcers, and heart failure in diabetes.Artificial intelligence is advantageous because it can handle large and complex datasets from a variety of sources. With each additional type of data incorporated into a clinical picture of a patient, the calculation becomes increasingly complex and specific. Artificial intelligence is the foundation of emerging medical technologies; it will power the future of diagnosing diabetes complications.

Scleritis and episcleritis in patients with idiopathic small fiber neuropathy

Purpose

To report the prevalence of scleritis and episcleritis in patients with idiopathic small fiber neuropathy (SFN).

Methods

The Mass General Brigham (MGB) hospital database was queried for patients with SFN, scleritis and episcleritis using diagnostic codes and natural language processing. Electronic medical chart review of patients diagnosed with SFN and episcleritis/scleritis who had at least one ophthalmology visit was conducted. The prevalence of scleritis and episcleritis in patients diagnosed with SFN was compared to those without SFN using logistic regression to adjust for covariates. All statistical analyses were performed in RStudio 4.2.1.

Results

From the 2100 SFN patients with an eye exam in the MGB database, 23 patients had episcleritis or scleritis (1.1 %) confirmed by chart review. Ten patients had episcleritis (0.48 %) and thirteen patients had scleritis (0.62 %). Of the episcleritis and scleritis patients, 16 (69.6 %) were women and 7 (30.4 %) were men. Ten (43.5 %) had bilateral ocular disease. The mean age of ocular diagnosis was 51.0 years (range, 22-77 years). Out of the 507,128 controls without SFN in the MGB database, 1481 (0.29 %) had scleritis and 1430 (0.28 %) had episcleritis. Episcleritis and scleritis were more prevalent in patients with SFN than in those without SFN: 0.48 % vs. 0.28 % for episcleritis and 0.62 % vs 0.29 % for scleritis (P values = 0.32 and 0.02, respectively).

Conclusions and Importance

There were higher rates of scleritis in SFN patients compared to non-SFN patients. This potential systemic disease association had not been previously reported.

Dysmetabolism-related Early Sensory Deficits and Their Relationship With Peripheral Neuropathy Development

AIM

To investigate the association of early peripheral sensory dysfunction (EPSD) identified through quantitative sensory testing (QST) with factors related to a dysmetabolic status in individuals with and without type 2 diabetes (T2DM) without peripheral neuropathy (PN), and the impact of those factors on PN development.

METHODS

A total of 225 individuals (117 and 108 without and with T2DM, respectively) without PN based on clinical and electrophysiological criteria were analyzed. Comparative analysis was conducted between those identified as "healthy" and those with EPSD based on a standardized QST protocol. A total of 196 were followed-up over a mean of 2.64 years for PN occurrence.

RESULTS

Among those without T2DM, apart from male sex, height, and higher fat and lower lean mass, only higher insulin resistance (IR; homeostatic model assessment for IR: odds ratio [OR], 1.70; P = .009; McAuley index OR, 0.62, P = .008), was independently associated with EPSD. In T2DM, metabolic syndrome (OR, 18.32; P < .001) and skin advanced glycation end-products (AGEs; OR, 5.66; P = .003) were independent predictors of EPSD. In longitudinal analysis, T2DM (hazard ratio [HR], 3.32 vs no diabetes mellitus; P < .001), EPSD (adjusted HR, 1.88 vs healthy; P = .049 adjusted for diabetes mellitus and sex), higher IR and AGEs predicted PN development. Among the 3 EPSD-associated sensory phenotypes, "sensory loss" was most strongly associated with PN development (adjusted HR, 4.35; P = .011).

CONCLUSION

We demonstrate for the first time the utility of a standardized QST-based approach in identifying early sensory deficits in individuals with and without T2DM. These are associated with a dysmetabolic status signified by IR markers, metabolic syndrome, and higher AGEs, which in turn are shown to influence PN development.

Peripheral Neuropathy in Diabetes Mellitus: Pathogenetic Mechanisms and Diagnostic Options

Diabetic neuropathy (DN) is one of the main microvascular complications of both type 1 and type 2 diabetes mellitus. Sometimes, this could already be present at the time of diagnosis for type 2 diabetes mellitus (T2DM), while it appears in subjects with type 1 diabetes mellitus (T1DM) almost 10 years after the onset of the disease. The impairment can involve both somatic fibers of the peripheral nervous system, with sensory-motor manifestations, as well as the autonomic system, with neurovegetative multiorgan manifestations through an impairment of sympathetic/parasympathetic conduction. It seems that, both indirectly and directly, the hyperglycemic state and oxygen delivery reduction through the vasa nervorum can determine inflammatory damage, which in turn is responsible for the alteration of the activity of the nerves. The symptoms and signs are therefore various, although symmetrical painful somatic neuropathy at the level of the lower limbs seems the most frequent manifestation. The pathophysiological aspects underlying the onset and progression of DN are not entirely clear. The purpose of this review is to shed light on the most recent discoveries in the pathophysiological and diagnostic fields concerning this complex and frequent complication of diabetes mellitus.

Measuring pain and nociception: Through the glasses of a computational scientist. Transdisciplinary overview of methods

In a healthy state, pain plays an important role in natural biofeedback loops and helps to detect and prevent potentially harmful stimuli and situations. However, pain can become chronic and as such a pathological condition, losing its informative and adaptive function. Efficient pain treatment remains a largely unmet clinical need. One promising route to improve the characterization of pain, and with that the potential for more effective pain therapies, is the integration of different data modalities through cutting edge computational methods. Using these methods, multiscale, complex, and network models of pain signaling can be created and utilized for the benefit of patients. Such models require collaborative work of experts from different research domains such as medicine, biology, physiology, psychology as well as mathematics and data science. Efficient work of collaborative teams requires developing of a common language and common level of understanding as a prerequisite. One of ways to meet this need is to provide easy to comprehend overviews of certain topics within the pain research domain. Here, we propose such an overview on the topic of pain assessment in humans for computational researchers. Quantifications related to pain are necessary for building computational models. However, as defined by the International Association of the Study of Pain (IASP), pain is a sensory and emotional experience and thus, it cannot be measured and quantified objectively. This results in a need for clear distinctions between nociception, pain and correlates of pain. Therefore, here we review methods to assess pain as a percept and nociception as a biological basis for this percept in humans, with the goal of creating a roadmap of modelling options.

Corneal Sub-Basal Nerve Plexus in Non-Diabetic Small Fiber Polyneuropathies and the Diagnostic Role of In Vivo Corneal Confocal Microscopy

In vivo corneal confocal microscopy (IVCM) allows the immediate analysis of the corneal nerve quantity and morphology. This method became, an indispensable tool for the tropism examination, as it evaluates the small fiber plexus in the cornea. The IVCM provides us with direct information on the health of the sub-basal nerve plexus and indirectly on the peripheral nerve status. It is an important tool used to investigate peripheral polyneuropathies. Small-fiber neuropathy (SFN) is a group of neurological disorders characterized by neuropathic pain symptoms and autonomic complaints due to the selective involvement of thinly myelinated Aδ-fibers and unmyelinated C-fibers. Accurate diagnosis of SFN is important as it provides a basis for etiological work-up and treatment decisions. The diagnosis of SFN is sometimes challenging as the clinical picture can be difficult to interpret and standard electromyography is normal. In cases of suspected SFN, measurement of intraepidermal nerve fiber density through a skin biopsy and/or analysis of quantitative sensory testing can enable diagnosis. The purpose of the present review is to summarize the current knowledge about corneal nerves in different SFN. Specifically, we explore the correlation between nerve density and morphology and type of SFN, disease duration, and follow-up. We will discuss the relationship between cataracts and refractive surgery and iatrogenic dry eye disease. Furthermore, these new paradigms in SFN present an opportunity for neurologists and clinical specialists in the diagnosis and monitoring the peripheral small fiber polyneuropathies.

Assessment of Hearing and Vestibular Functions in a Post-COVID-19 Patient: A Clinical Case Study

SARS-CoV-2 infection may cause such complications as post-COVID-19 syndrome, which includes chronic fatigue, myalgia, arthralgia, as well as a variety of neurological manifestations, e.g., neuropathy of small fibers, hearing and vestibular dysfunction, and cognitive impairment. This clinical case describes a 41-year-old patient suffering from post-COVID-19 syndrome and chronic fatigue syndrome. A detailed examination was performed, including an in-depth study of peripheral and central hearing and vestibular functions, as well as small nerve fibers length and density in the skin and cornea of the eye. Contrary to expectations, no peripheral nervous system dysfunction was detected, despite the presence of dizziness and gait instability in the patient. Hearing tests (gap detection test and dichotic test) showed central auditory processing disorders. The evaluated lesion in the processing of temporal and verbal auditory information can be a significant factor contributing to additional overload of the neural activity and leading to chronic fatigue when performing daily activities in patients with CFS and post-COVID-19 complications.

Update on Corneal Confocal Microscopy Imaging

In vivo corneal confocal microscopy (IVCM) is a non-invasive ophthalmic imaging technique that provides images of the cornea at the cellular level. Despite the uses in ocular surface pathologies, in the last decades IVCM has been used to provide more knowledge in refractive surgery wound healing, in neuropathies diagnosis, etc. The observation of the corneal cells, both normal and inflammatory, and the possibility of quantification of the corneal nerve density with manual or automated tools, makes IVCM have a significant potential to improve the diagnosis and prognosis in several systemic and corneal conditions.

Corneal Confocal Microscopy Findings in Neuro Lyme Disease: A Case Report

Neuro Lyme disease is caused by several bacteriae of the Borreliaceae family, such as Borrelia Miyamotoi. In late stages of illness, patients with Lyme disease may develop chronic neurologic symptoms such as cognitive disturbances or small fiber peripheral neuropathy. Confocal microscopy is a non-invasive method designed to evaluate the human cornea in vivo. Thus, all the corneal layers, including the cells and the sub-basal nerve plexus, can be easily visualized and analyzed. This is the first report of the morphology of small-fiber peripheral neuropathy analyzed by confocal microscopy in a patient diagnosed of neuro Lyme disease. The decrease in the number of unmyelinated sub-basal nerve fibers with abundant presence of dendritic cells (DC) in comparison with healthy corneas strongly supports the diagnosis of small fiber peripheral neuropathy in a case of neuroborreliosis disease.