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.

Axonal Excitability Does Not Differ between Painful and Painless Diabetic or Chemotherapy-Induced Distal Symmetrical Polyneuropathy in a Multicenter Observational Study.

OBJECTIVE: Axonal excitability reflects ion channel function, and it is proposed that this may be a biomarker in painful (vs painless) polyneuropathy. Our objective was to investigate the relationship between axonal excitability parameters and chronic neuropathic pain in deeply phenotyped cohorts with diabetic or chemotherapy-induced distal symmetrical polyneuropathy. METHODS: Two hundred thirty-nine participants with diabetic polyneuropathy were recruited from sites in the UK and Denmark, and 39 participants who developed chemotherapy-induced polyneuropathy were recruited from Denmark. Participants were separated into those with probable or definite neuropathic pain and those without neuropathic pain. Axonal excitability of large myelinated fibers was measured with the threshold tracking technique. The stimulus site was the median nerve, and the recording sites were the index finger (sensory studies) and abductor pollicis brevis muscle (motor studies). RESULTS: Participants with painless and painful polyneuropathy were well matched across clinical variables. Sensory and motor axonal excitability measures, including recovery cycle, threshold electrotonus, strength-duration time constant, and current-threshold relationship, did not show differences between participants with painful and painless diabetic polyneuropathy, and there were only minor changes for chemotherapy-induced polyneuropathy. INTERPRETATION: Axonal excitability did not significantly differ between painful and painless diabetic or chemotherapy-induced polyneuropathy in a multicenter observational study. Threshold tracking assesses the excitability of myelinated axons; the majority of nociceptors are unmyelinated, and although there is some overlap of the "channelome" between these axonal populations, our results suggest that alternative measures such as microneurography are required to understand the relationship between sensory neuron excitability and neuropathic pain. ANN NEUROL 2022;91:506-520.

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.

Axonal swellings are related to type 2 diabetes, but not to distal diabetic sensorimotor polyneuropathy.

AIMS/HYPOTHESIS: Distal diabetic sensorimotor polyneuropathy (DSP) is a common complication of diabetes with many patients showing a reduction of intraepidermal nerve fibre density (IENFD) from skin biopsy, a validated and sensitive diagnostic tool for the assessment of DSP. Axonal swelling ratio is a morphological quantification altered in DSP. It is, however, unclear if axonal swellings are related to diabetes or DSP. The aim of this study was to investigate how axonal swellings in cutaneous nerve fibres are related to type 2 diabetes mellitus, DSP and neuropathic pain in a well-defined cohort of patients diagnosed with type 2 diabetes. METHODS: A total of 249 participants, from the Pain in Neuropathy Study (UK) and the International Diabetic Neuropathy Consortium (Denmark), underwent a structured neurological examination, nerve conduction studies, quantitative sensory testing and skin biopsy. The study included four groups: healthy control study participants without diabetes (n = 45); participants with type 2 diabetes without DSP (DSP-; n = 31); and participants with evidence of DSP (DSP+; n = 173); the last were further separated into painless DSP+ (n = 74) and painful DSP+ (n = 99). Axonal swellings were defined as enlargements on epidermal-penetrating fibres exceeding 1.5 µm in diameter. Axonal swelling ratio is calculated by dividing the number of axonal swellings by the number of intraepidermal nerve fibres. RESULTS: Median (IQR) IENFD (fibres/mm) was: 6.7 (5.2-9.2) for healthy control participants; 6.2 (4.4-7.3) for DSP-; 1.3 (0.5-2.2) for painless DSP+; and 0.84 (0.4-1.6) for painful DSP+. Swelling ratios were calculated for all participants and those with IENFD > 1.0 fibre/mm. When only those participants with IENFD > 1.0 fibre/mm were included, the axonal swelling ratio was higher in participants with type 2 diabetes when compared with healthy control participants (p < 0.001); however, there was no difference between DSP- and painless DSP+ participants, or between painless DSP+ and painful DSP+ participants. The axonal swelling ratio correlated weakly with HbA1c (r = 0.16, p = 0.04), but did not correlate with the Toronto Clinical Scoring System (surrogate measure of DSP severity), BMI or type 2 diabetes duration. CONCLUSIONS/INTERPRETATION: In individuals with type 2 diabetes where IENFD is >1.0 fibre/mm, axonal swelling ratio is related to type 2 diabetes but is not related to DSP or painful DSP. Axonal swellings may be an early marker of sensory nerve injury in type 2 diabetes.

Falls in individuals with type 2 diabetes; a cross-sectional study on the impact of motor dysfunction, postural instability and diabetic polyneuropathy.

AIM: To estimate the incidence of falls in individuals with type 2 diabetes compared to healthy controls and to describe the characteristics of fallers with type 2 diabetes in relation to motor dysfunction, postural instability and diabetic polyneuropathy (DPN). METHODS: This is a cross-sectional study of individuals with type 2 diabetes with DPN (n = 54), without DPN (n = 38) and healthy controls (n = 39). Falls were recorded within the preceding year. DPN was defined by clinical scores and nerve conduction studies. Motor function was assessed by a 6-min walk test (6 MWT), five-time sit-to-stand test (FTSST) and isokinetic dynamometry at the non-dominant ankle and knee. An instability index (ST) was measured using static posturography. Univariate and bivariate descriptive statistics were used for group comparisons. RESULTS: Compared with healthy controls, individuals with diabetes had a higher incidence of falls 36%, (n = 33) versus 15%, (n = 6), p = 0.02. There were no differences in falls when comparing individuals with and without DPN. Fallers had an impaired 6 MWT versus non-fallers (450 ± 153 m vs. 523 ± 97 m respectively), a slower FTSST (11.9 ± 4.2 s vs. 10.3 ± 2.9 s respectively) and a higher ST (53 ± 29 vs. 41 ± 17 respectively), p < 0.02 for all. CONCLUSION: Individuals with type 2 diabetes reported a higher number of falls within the preceding year compared to healthy controls, irrespective of the presence of DPN. The main factors associated with falls were increased postural instability, lower walking capacity and slower sit-to-stand movements. The 6 MWT, FTSST and posturography should be considered in future screening programs in identification of individuals at risk for falls.

MRI of Skeletal Muscles in Participants with Type 2 Diabetes with or without Diabetic Polyneuropathy.

BackgroundDiabetic polyneuropathy (DPN) is associated with loss of muscle strength. MRI including diffusion-tensor imaging (DTI) may enable detection of muscle abnormalities related to type 2 diabetes mellitus (DM2) and DPN.PurposeTo assess skeletal muscle abnormalities in participants with DM2 with or without DPN by using MRI.Materials and MethodsThis prospective cross-sectional study included participants with DM2 and DPN (DPN positive), participants with DM2 without DPN (DPN negative), and healthy control (HC) participants enrolled between August 2017 and June 2018. Muscle strength at the knee and ankle was determined with isokinetic dynamometry. MRI of the lower extremities included the Dixon sequence, multicomponent T2 mapping, and DTI calculated fat fractions (FFs), T2 relaxation of muscle (T2water), fractional anisotropy (FA), and diffusivity (mean, axial, and radial). One-way analysis of variance and Tukey honestly significant difference were applied for comparison between groups, and multivariate regression models were used for association between MRI parameters, nerve conduction, strength, and body mass index (BMI).ResultsTwenty participants with DPN (mean age, 65 years ± 9 [standard deviation]; 70% men; mean BMI, 34 kg/m2 ± 5), 20 participants without DPN (mean age, 64 years ± 9; 55% men; mean BMI, 30 kg/m2 ± 6), and 20 HC participants (mean age, 61 years ± 10; 55% men; mean BMI, 27 kg/m2 ± 5) were enrolled in this study. Muscle strength adjusted for age, sex, and BMI was lower in participants with DPN than in DPN-negative and HC participants in the upper and lower leg (plantar flexors [PF], 62% vs 78% vs 89%; P < .001; knee extensors [KE], 73% vs 95% vs 93%; P < .001). FF was higher in leg muscle groups of participants with DPN than in DPN-negative and HC participants (PF, 20% vs 10% vs 8%; P < .001; KE, 13% vs 8% vs 6%; P < .001). T2water was prolonged in leg muscle groups of participants with DPN when compared with HC participants (PF, 33 msec vs 31 msec; P < .001; KE, 32 msec vs 31 msec; P = .002) and in the lower leg when compared with participants without DPN (PF, 33 msec vs 32 msec; P = .03). In multivariate regression models, strength was associated with FA (b = -0.0004), T2water (b = -0.03 msec), and FF (b = -0.1%) at thigh level (P < .001). Furthermore, FA (b = -0.007), T2water (b = -0.53 msec), and FF (b = -4.0%) were associated with nerve conduction at calf level (P < .001).ConclusionMRI of leg muscle groups revealed fat accumulation, differences in water composition, and structural changes in participants with type 2 diabetes mellitus and neuropathy. Abnormalities were most pronounced in the plantar flexors.© RSNA, 2020Online supplemental material is available for this article.See also the editorial by Sneag and Tan in this issue.