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Diabetic neuropathy is diagnosed late due to lack of easy and readily available biomarkers; early identification can prompt proper interventions before the irreversible large fiber damage. The aim of this study is to assess small fiber dysfunction using cutaneous silent period (CSP) and sympathetic skin response (SSR) tests in patients with diabetic small fiber neuropathy (SFN) and compare results with clinical, neuropathy severity and quality of life measures. A total of 45 subjects were classified into: Group I: diabetic patients with pure SFN, group II: diabetic patients with mixed fiber neuropathy, and group III: healthy subjects. All underwent evaluation by anthropometric, clinical and quality of life measures, electrophysiological evaluation by CSP and SSR and distal leg skin biopsy.
Results
Age and gender distribution did not significantly differ between the studied groups. Both patients’ groups showed comparable poor quality of life in relation to healthy subjects. CSP onset latencies and SSR amplitudes significantly correlated with studied clinical and severity measures, but neither correlate with each other in diabetic pure SFN patients. Both CSP and SSR measures were specific in diagnosing diabetic pure SFN, but mostly with poor sensitivity. Combining sensitivities of different CSP and SSR measures improved the overall sensitivity to early screen for SFN in diabetic patients.
Conclusions
Both CSP and SSR may have the potential to early detect diabetic pure SFN. Suspected diabetic patients with SFN should be separately screened for both somatosensory and sudomotor/autonomic affection.
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aAmp
Average Amplitude
AUC
Area Under Curve
BMI
Body mass index
CI
Confidence Interval
Circ.
Circumference
CSP
Cutaneous silent period
CSP-M
Cutaneous silent period after median nerve stimulation
CSP-S
Cutaneous silent period after sural nerve stimulation
DBP
Diastolic blood pressure
DN4
Douleur Neuropathique en 4
DPN
Diabetic peripheral neuropathy
EMG
Electromyography
EQ-5D-5L
EuroQol-5 Dimensions, 5 Levels
IENF
Intraepidermal nerve fiber
IENFD
Intraepidermal nerve fiber density
IQR
Interquartile range
LFN
Large fiber neuropathy
MCET
Monte Carlo Exact Test
MetS
Metabolic syndrome
MFN
Mixed fiber neuropathy
Ms
Millisecond
NCS
Nerve conduction studies
NRS
11-Point numeric pain scale
OL
Onset Latency
PGP9.5
Protein gene product 9.5
ROC
Receiver operating characteristic
SBP
Systolic Blood Pressure
SD
Standard deviation
SFN
Small fiber neuropathy
SSR
Sympathetic skin response
TCNS
Toronto Clinical Neuropathy Score
UENS
Utah Early Neuropathy Scale
μv
Microvolt
Background
Peripheral neuropathy can be categorized according to pathological patterns and clinical symptoms into large and small fiber types. Large fiber neuropathy (LFN) develops from affection of large myelinated Aα and Aβ nerve fibers, and symptoms include limb weakness, sensory ataxia (due to affection of proprioception), and affection of touch and vibration sense, while small fiber neuropathy (SFN) develops from lesions affecting small thinly myelinated Aδ and unmyelinated C nerve fibers. These fibers build up to 80–90% of the peripheral nerves and are responsible for temperature and pain sensations, and autonomic functions [1].
Although there are many causes of small fiber neuropathy, about 30% to 50% of cases are idiopathic [2, 3]. Diabetes and glucose intolerance are the most important secondary causes of small fiber neuropathy, representing up to a third of all cases [3, 4]. Diabetic neuropathy is diagnosed late—in the pre-ulcer stage—due to the lack of early screening and readily available biomarkers. The disease often begins with damage to small nerve fibers, leading to disrupted sensory processing of temperature and pain, as well as potentially impairing sweating and local blood flow in peripheral tissues. Subsequently, large nerve fibers may be affected, which may signal the onset of foot ulceration [5].
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Standard nerve conduction studies can examine large, myelinated nerve fiber dysfunction, but they cannot detect small fiber affection, so small fiber function should be examined with tests that specifically assess small thinly or unmyelinated Aδ and C fiber types [6]. The density of nerve fibers within the epidermis can be measured in a distal leg skin biopsy with immunohistochemical staining, and this test is the gold standard for diagnosing small fiber neuropathy [7, 8]. However, it is an invasive test, and the staining process is somewhat complicated and requires a well-equipped pathology lab, besides the limited availability and the expensive cost of the staining kits.
Evaluation of the cutaneous silent period (CSP), a spinal reflex mediated by small sensory fibers from primarily Aδ fibers, has been considered as a promising electrophysiological test to reliably assess small fiber function in diabetic patients [9]. The cutaneous silent period is the period produced by the exteroceptive electromyographic (EMG) suppression of voluntarily contracting muscles by stimulating a cutaneous sensory nerve or mixed nerve (mixed silent period) located in the same or neighboring dermatome. Sympathetic skin response (SSR) is another electrophysiological test that detects electrodermal activity across the skin; it evaluates sudomotor function by recording sympathetic cholinergic fiber activation [10]. SSR can be abnormal in diseases affecting mainly the unmyelinated C fibers and may have a role in diagnosis in early stages of diabetic neuropathy [11, 12]. However, it tests a complex polysynaptic pathway and is not confined only to the postganglionic fibers. Yet, both CSP and SSR have the advantage of being easily performed using a standard electromyography (EMG) device, without requiring any specialized or additional equipment [9, 13].
The aim of this study is to assess small fiber dysfunction using the cutaneous silent period sympathetic skin response tests in Egyptian patients with diabetic small fiber neuropathy and compare results with clinical, neuropathy severity, and quality of life measures.
Methods
This case–control observational study was carried out on patients presenting with diabetic small fiber neuropathy attending the outpatient clinic at the Department of Neuropsychiatry and Center of Neurology and Psychiatry, Tanta University Hospitals, in the period from September 2022 to June 2023.
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We included patients older than 18 years diagnosed with diabetes mellitus by laboratory investigations according to the American Diabetic Association [14] and World Health Organization [15] including any of the following: HbA1C, fasting blood sugar, and 2-h postprandial blood sugar, and/or antidiabetic medication. Also we recruited patients presented with SFN [16, 17] including (a) typical clinical symptoms of SFN such as burning or sharp pain in toes and feet, and on clinical examination: loss of small fiber modalities (pinprick and temperature), hyperalgesia, allodynia, and/or autonomic signs, (b) reduced intraepidermal nerve fiber density (IENFD) in distal leg skin punch biopsy, and (c) normal routine nerve conduction studies.
We excluded patients with other conditions that could cause neuropathy (such as chemotherapy, alcohol intake, established vitamin B12 deficiency, established hereditary neuropathy “or first-degree family members”, active malignancy, chronic advanced liver or kidney diseases thought to cause neuropathy and history of bariatric surgery), and patients with central causes of neuropathic pain and somatosensory and/or sudomotor affection (such as stroke and central neurodegenerative disorders).
Subjects were classified into 3 groups, each of 15 subjects. Group I includes diabetic patients with pure small fiber neuropathy (SFN), diagnosed by the forementioned criteria. Group II: a control group of diabetic patients with mixed small and large fiber neuropathy (MFN), diagnosed with the forementioned criteria in addition to abnormal standard nerve conduction studies. Finally, group III with another control group of healthy subjects matching patients’ age and gender.
Anthropometric measures were recorded, including body weight in kilograms, height in centimeters, and waist circumference measured in centimeters at the top of the iliac crest. In addition, systolic (SBP) and diastolic (DBP) blood pressure in mmHg were measured. Serum lipid profile and HbA1C were performed, and metabolic syndrome was diagnosed if 3 of the 5 following criteria were met: (1) SBP ≥ 130 mmHg and/or DBP ≥ 85 mmHg or drug therapy; (2) Waist circumference > 93.5 cm (men) or > 92 cm (women); (3) Triglycerides ≥ 150 mg/dL or drug therapy (fibrates); (4) HDL-C < 40 mg/dL males, or < 50 mg/dL in females or drug therapy (statins); (5) HbA1c ≥ 5.7% or drug therapy [18, 19].
Somatosensory affection was evaluated using the Utah Early Neuropathy Scale (UENS) and Douleur Neuropathique en 4 (DN4) questionnaire, where UENS ≥ 4 and DN4 ≥ 3 are considered abnormal [20‐22]. Severity measures included the 11-point numeric pain scale (NRS) [23] to assess neuropathic pain severity, the Toronto Clinical Neuropathy Score (TCNS) [24] to assess the neuropathy severity, and the Arabic version of the EuroQol-5 Dimensions, 5 Levels (EQ-5D-5L) index value [25] to assess the quality of life.
A 3 mm punch biopsy was taken 10 cm proximal to the lateral malleolus. The specimen was fixed in 10% neutral formalin for at least 24 h, embedded in paraffin, and sectioned into 10-micron slices. After deparaffinization and antigen retrieval in citrate buffer pH 6 solution, immunoperoxidase staining was performed. Sections were incubated overnight with primary antibody solution containing diluted polyclonal antibody against protein gene product 9.5 antibody “1:1000” (UCHL1/PGP9.5 Polyclonal Antibody from BIOSS Antibodies Inc., Massachusetts, USA), followed by secondary biotinylated goat antirabbit antibody, and the signal was amplified using streptavidin–HRP (Elabscience®, Houston, USA). 3,3′-diaminobenzidine chromogen solution (Elabscience®, Houston, Texas, USA) was then applied. Sections were counterstained, cover-slipped, and imaged at 40X magnification using the built-in Leica ICC50 camera. Intraepidermal nerve fibers (IENF) were counted in at least 2 sections, where the highest count was recorded, owing to the thickness of the specimens, except if there was only one IENF, we used an average in three sections. Nerve fiber density was calculated using ImageJ software (Figs. 1, 2, 3).
Fig. 1
Decreased IENFD in distal leg skin biopsy in a patient with diabetic small fiber neuropathy: 2 IENFs are crossing the basement membrane
Decreased IENFD in distal leg skin biopsy in a case of diabetic mixed fiber neuropathy. 1 IENF is crossing basement membrane “brown arrow”, also non-crossing IENs are seen “red arrows”
Normal IENFD in distal leg skin biopsy: 3 IENFs are crossing the basement membrane “brown arrows”, 1 is more than half epidermal width “orange arrow” and 2 small IENF that is not crossing basement membrane “red arrows”
Standard nerve conduction studies and cutaneous silent period were performed using the DEYMED TruTrace® EMG device (DEYMED Diagnostic, Hronov, Czech Republic). Sensory and motor NCS were performed using surface recording electrodes to assess large nerve fibers. For motor conduction studies, high-frequency filter was set at 5 kHz, and no low-frequency filter was used. Sweep was adjusted when needed from 2 to 5 ms/division and sensitivity from 2 to 5 mV/division. For sensory conduction studies, the high frequency filter was at 2 kHz, and no low frequency filter was used. Sweep was adjusted when needed from 1 to 2 ms/division and sensitivity from 10 to 20 μV/division. The right ulnar, left tibial, left superficial peroneal, right deep peroneal, and right sural nerves were evaluated for amplitude, latency and conduction velocity, in addition to right ulnar and left tibial F wave latencies. Large nerve fiber involvement was confirmed when two or more nerves were abnormal in at least one of the following parameters: amplitude, conduction velocity, distal motor latency, or F-wave latency, with one of those nerves necessarily being the sural nerve [26]. If any parameter of the scanned nerves was abnormal (above the 97th percentile of the control group for latencies or below the 3rd percentile for amplitudes), and the right sural nerve SNAP and CV were normal, the left sural nerve was also assessed, but neither case showed any abnormality.
In addition, the cutaneous silent period (CSP) test was conducted to assess Aδ nerve fibers (Fig. 4). The silent period was obtained within a transient suppression of the EMG voluntary activity that occurred in response to the antidromic electrical stimulation of both the left median and the right sural nerves while recording from the left abductor pollicis longus and the right tibialis anterior muscles, respectively. The onset latency (OL) was recorded at the beginning of muscle activity suppression, and the second–late end latency was recorded at the start of new muscle activity. The difference between the two latencies indicated the duration of CSP. The low-frequency filter was set at 50 Hz, and high-frequency filter at 5 kHz. Sensitivity was adjusted when needed from 500 to 1500 μV per division. Sweep was adjusted at 100 ms per division, with a time-base of 1 s. Stimulus intensity ranged from 15 to 100 mA according to the individual sensory threshold (intensity used was 15-fold this threshold). Two to four responses were recorded.
Fig. 4
Cutaneous silent period in patient with diabetic small fiber neuropathy (A), diabetic mixed fiber neuropathy (B), and normal subjects (C)
Finally, the sympathetic skin response (SSR) test was done (Fig. 5). We performed bilateral simultaneous two channels hand-to-hand and foot-to-foot stimulation by stimulating median and tibial nerves on one side and recording from the other side. In hand stimulation, the recording electrodes were applied to the palms of either hand, the reference electrodes were applied to the dorsum of either hand, and the ground electrode was applied to the forearm of the stimulated side. In foot stimulation, the recording electrodes were applied to the soles of either foot, the reference electrodes were applied to the dorsum of either foot, and the ground electrode was applied to the foreleg of the stimulated side. The sensitivity was adjusted as needed from 200 to 3000 μV/div, and the filters were set at 0.2 Hz and 15 Hz for the low- and high-frequency filters, respectively. Stimulation was applied at randomized intervals of variable intensity (8–60 mA and duration up to 500 ms) to prevent any habituation effects. SSR was evaluated for presence and peak-to-peak average amplitude. An absent response was considered when at least one lower limb response was absent [10, 27, 28].
Fig. 5
Sympathetic skin response in patient with diabetic small fiber neuropathy (A), diabetic mixed fiber neuropathy (B), and normal subjects (C)
The collected data were organized, tabulated, and statistically analyzed using MedCalc version 20.104 created by MedCalc Software Ltd, Belgium. Descriptive statistics: Data were expressed as numbers and percentages for numerical values: The Shapiro–Wilk test, Q–Q plots, and graphical histograms were performed to assess normal distribution: For parametric variables, the range, mean, and standard deviations (SD) were calculated. The one-way ANOVA (F) test was used to compare different means of the 3 studied groups, and pairwise comparisons were done when needed by applying the post hoc Tukey–Kramer test. If the means of two groups were compared, the independent samples (t) test was used. For non-parametric variables, median and interquartile range percentiles (IQR) were calculated. The Kruskal–Wallis (H) test was used to compare different ranks of the 3 studied groups, and pairwise comparisons were done when needed. If the means of two groups were compared, the Mann–Whitney test (U) was used. For categorical variables, the number and percentage were calculated and differences between subcategories were tested by chi-square (χ2) test. When chi-square was not appropriate, the Monte Carlo exact test (MCET) was used. Correlation between continuous data sets was done using Spearman’s correlation (rs), and between a categorical and continuous data using point biserial correlation (rp). For all statistical tests done, the threshold of significance was fixed at 5% level (p value). Receiver operating characteristic (ROC) curve was done to assess the sensitivity, specificity, and cutoff values for different tests. The EQ-5D-5L index value was calculated automatically using an online platform based on R software, found at: fragla.shinyapps.io/shiny-Eq. 5d/.
Results
Age was adjusted and so did not significantly vary among the studied groups. Patients in group II had slightly higher mean ages. Also, no significant gender variation was found, where in all groups, female gender was more predominant. Among the mentioned anthropometric measures, no significant difference was found between the studied groups regarding weight, height, and body mass index (BMI), while waist circumference was significantly higher in group II in relation to group III, and both systolic and diastolic blood pressure measurements were significantly higher in groups I and II in relation to group III. The duration of diabetes mellitus was significantly higher in group II. Most of the patient groups I and II were diagnosed with metabolic syndrome, with no statistically significant difference between the two groups. Also, no significant difference was found between the two groups regarding either metformin or insulin intake, while blood pressure medication intake was found to be higher among patients in group II. There was a statistically significant difference regarding IENFD among studied groups and between each group and the other, where median IENFD was the lowest in group II, followed by group I, and both were significantly lower than that of group III (Table 1).
Table 1
Demographic, anthropometric, and clinical data of the studied groups
Variable
Group I (Pure SFN)
Group II (Mixed)
Group III (Normal)
p
Age (years)
44.27 ± 12.98
50.27 ± 6.65
47.07 ± 8.66
0.255
Gender (Female)
11 (73.3%)
10 (66.7%)
13 (86.7%)
0.565
Weight (kg)
88.21 ± 17.26
94.27 ± 18.34
86.35 ± 15.99
0.427
Height (m)
1.62 ± 0.10
1.63 ± 0.09
1.62 ± 0.06
0.968
BMI (kg/m2)
33.58 ± 5.17
35.93 ± 8.04
32.86 ± 5.59
0.397
Waist Circ. (cm)
103.82 ± 14.69
113.97 ± 15.85
98.28 ± 13.60
0.019*
p1 = 0.155
p2 = 0.563
p3 = 0.015*
Systolic BP (mmHg)
130.8 ± 12.07
133.13 ± 12.35
115.47 ± 10.61
< 0.001*
p1 = 0.849
p2 = 0.002*
p3 < 0.001*
Diastolic BP (mmHg)
83.00 ± 9.56
79.67 ± 10.10
69.73 ± 9.47
0.002*
p1 = 0.617
p2 = 0.020*
p3 < 0.001*
DM duration (years)
7 (3–10)
15 (6–21)
0.026*
Metabolic syndrome
10 (71.4%)
13 (86.7%)
0.580
Metformin intake
7 (46.7%)
11(73.3%)
0.136
Insulin Intake
6 (40%)
8 (53.3%)
0.464
BP medication
2 (16.7%)
8 (66.7%)
0.020*
IENFD
3.94 (2.74–5.06)
0.98 (0.9–1.85)
10.75 (8.17–13.59)
< 0.001*
p1 = 0.003*
p2 = 0.002*
p3 < 0.001*
Data are presented as mean ± SD, median (IQR), and number (percentage)
BMI Body mass index, Circ. Circumference, BP Blood pressure, DM Diabetes Mellitus, IENFD Intraepidermal Nerve Fiber Density, p1: I versus II; p2: I versus III; p3: II versus III
Among the studied clinical scales, there were significant differences between the studied groups and each group and the other regarding total DN4 score, UENS and TCNS, where higher scores were found in group II patients, followed by group I. The severity of neuropathy categorized by TCNS showed that group II mostly had severe neuropathy (66.7%), while group 2 mainly had mild neuropathy (53.3%) and TCNS failed to diagnose neuropathy in 13.3% of patients in this group. Quality of life assessment measured by EQ-5D-5L showed a significant difference in the index score between groups I and III, and groups II and III, with no significant difference between the first two groups (Table 2).
Table 2
Clinical somatosensory and quality of life assessment scales of the studied groups
Variable
Group I (Pure SFN)
Group II (Mixed)
Group III (Normal)
p
NRS
5 (3–8)
4 (3–8)
0.917
DN4
4 (4–5)
6 (6–7)
1 (0–1)
< 0.001*
p1 = 0.018*
p2 = 0.001*
p3 < 0.001*
UENS
8 (5–9)
18(11–21)
0 (0–0)
< 0.001*
p1 = 0.012*
p2 = 0.001*
p3 < 0.001*
TCNS
8 (7–10)
12 (11–16)
1 (1–2)
< 0.001*
p1 = 0.012*
p2 = 0.001*
p3 < 0.001*
TCNS Class
< 0.001*
p1 < 0.001*
No neuropathy
2 (13.3%)
0
15 (100%)
p2 < 0.001*
Mild
8 (53.3%)
1 (6.7%)
0
p3 < 0.001*
Moderate
5 (33.3%)
4 (26.7%)
0
Severe
0
10 (66.7%)
0
EQ-5D-5L Index
0.587 (0.277–0.726)
0.400 (-0.086–0.726)
0.819 (0.765–0.892)
< 0.001*
p1 = 0.400
p2 = 0.003*
p3 < 0.001*
Data are presented as median (IQR), and number (percentage)
NRS 11-numeric pain rating scale, DN4 Douleur Neuropathique 4, UENS Utah Early Neuropathy Scale, TCNS Toronto Clinical Neuropathy Score, EQ-5D-5L EuroQOL 5 Dimensions 5 Levels; p1: I versus II; p2: I versus III; p3: II versus III
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HbA1c levels were significantly different between groups I and III, and groups II and III, while no significant difference was found between the first two groups, although higher levels were found in group I. Of the lipid profile, only serum triglyceride levels were significantly higher in group II in relation to group III, with no significant difference between patients’ groups I and II (Table 3).
Table 3
Laboratory findings in the studied groups
Variable
Group I (Pure SFN)
Group II (Mixed)
Group III (Normal)
p
HbA1c
8.4 (6.5–10.2)
7.7 (6.3–8.325)
5.4 (5.1–5.8)
< 0.001*
p1 = 0.412
p2 < 0.001*
p3 = 0.001*
Total Cholesterol
185 (173–224)
195.5 (139.5–245.5)
187 (166–203)
0.672
LDL-C
130.38 ± 47.71
118.43 ± 45.80
106.09 ± 25.28
0.294
HDL-C
49 (43.25–55.5)
44 (40.75–55.25)
52 (40–61)
0.566
Triglycerides
117 (90–177)
166 (134.5–200.75)
124 (95–156)
0.034*
p1 = 0.060
p2 = 0.592
p3 = 0.012*
Data are presented as mean ± SD and median (IQR)
HbA1C Glycosylated Hemoglobin, LDL-C Low Density Lipoprotein Cholesterol, HDL-C High Density Lipoprotein Cholesterol, TGs Triglycerides, p1: I versus II; p2: I versus III; p3: II versus III
Onset latency (OL) of left median CSP was significantly delayed in group II in relation to either group I or group III, with no statistically significant difference between groups I and III, while OL of right sural CSP was significantly delayed in both groups I and II, each in relation to group III, with no statistically significant difference between group I and II. The right sural CSP duration was also significantly lower in group II in relation to either group I or group III, with no statistically significant difference between groups I and III (Table 4).
Table 4
CSP and SSR in the studied groups
Variable
Group I (Pure SFN)
Group II (Mixed)
Group III (Normal)
p
CSP-M OL (ms)
83.7(72.8–89.9)
96.5(86.85–108.575)
76(70.5–81.4)
< 0.001*
p1 = 0.023*
p2 = 0.058
p3 < 0.001*
CSP-M Duration (ms)
48.9(45–57.4)
46.5(38.8–54.2)
43.4(35.7–49.6)
0.107
CSP-S OL (ms)
120.2(108.35–125.2)
126.4(112.8–141.9)
109.3(103.1–113.2)
0.007*
p1 = 0.409
p2 = 0.013*
p3 = 0.008*
CSP-S Duration (ms)
38.7(25.9–51.2)
0(0–24.95)
44.1(36.4–54.3)
< 0.001*
p1 = 0.001*
p2 = 0.570
p3 < 0.001*
CSP-S Absence
2 (13.3%)
10 (66.7%)
0 (0%)
< 0.001*
SSR-H aAmp. (μv)
1877.6 (1548.7–3372.1)
1376.1 (459.6–2088.5)
3216 (1931.4–4272.5)
0.007*
p1 = 0.064
p2 = 0.191
p3 = 0.002*
SSR-F aAmp. (μv)
594.4 (157.5–1537.3)
0 (0–430.3)
641 (383.7–956)
< 0.001*
p1 = 0.002*
p2 = 0.801
p3 = 0.001*
SSR-Absence
4 (26.7%)
10 (66.7%)
0 (0%)
< 0.001*
Data are presented as median (IQR), and number (percentage)
CSP Cutaneous Silent Period, M Median nerve stimulation, OL Onset Latency, S Sural nerve stimulation, ms Milliseconds, SSR Sympathetic Skin Response, aAmp: Average Amplitude, μV Microvolt, H Hand-to-hand stimulation, F Foot-to-foot stimulation p1: I versus II; p2: I versus III; p3: II versus III
Except for CSP duration after left median nerve stimulation, all CSP and SSR parameters significantly correlated with nearly all the clinical and severity measures and IENFD (Table 5).
Table 5
Correlation between CSP and SSR parameters and clinical, severity, and QOL scales, and IEFND
Variable
NRS
TCNS
UENS
EQ-5D-5L
IEFND
CSP-M OL
0.451 (0.002*)
0.500 (0.001*)
0.498 (< 0.001*)
− 0.468 (0.001*)
− 0.580 (< 0.001*)
CSP-M Duration
− 0.006 (0.970)
0.232 (0.125)
0.144 (0.344)
0.051 (0.738)
− 0.119 (0.438)
CSP-S OL
0.534 (0.001*)
0.404 (0.020*)
0.500 (0.003*)
-0.361 (0.039*)
− 0.438 (0.011*)
CSP-S Duration
− 0.328 (0.028*)
− 0.567 (< 0.001*)
− 0.588 (< 0.001*)
0.292 (0.052)
0.605 (< 0.001*)
SSR-H aAmp (μv)
− 0.376 (0.011)
− 0.468 (0.001*)
− 0.541 (< 0.001*)
0.293 (0.051)
0.549 (< 0.001*)
SSR-F aAmp (μv)
− 0.318 (0.033*)
− 0.512 (< 0.001*)
− 0.520 (0.001*)
0.366 (0.016*)
0.577 (< 0.001*)
SSR Absence
0.372 (0.012*)
0.611 (< 0.001*)
0.618 (< 0.001*)
− 0.445 (0.002*)
− 0.552 (< 0.001*)
Data are presented as spearman (rs) or point biserial (rp) correlation coefficient (p value)
NRS 11-point numeric pain scale, TCNS Toronto clinical neuropathy scale, EQ-5D-5L EuroQOL 5 Dimensions 5 Levels, IENFD Intraepidermal nerve fiber density, CSP Cutaneous Silent Period, M Median nerve stimulation, OL Onset Latency; S: Sural nerve stimulation, SSR Sympathetic Skin Response, aAmp Average Amplitude, μV Microvolt, H Hand-to-hand stimulation, F Foot-to-foot stimulation
In all studied subjects, CSP-M-OL correlated negatively, and CSP-S correlated positively with SSR amplitudes and SSR absence, while CSP-S-OL correlated only with SSR amplitude in the upper limb (Table 6). However, no significant correlation was found between CSP latencies and SSR, either in amplitudes or absence in group I patients (Table 7).
Table 6
Correlation between SSR amplitudes and CSP among all studied subjects
Variable
CSP-M OL (ms)
CSP-S OL (ms)
CSP-S Duration (ms)
SSR-H aAmp. (μv)
0.451 (0.002*)
0.500 (0.001*)
0.498 (< 0.001*)
SSR-F aAmp. (μv)
− 0.006 (0.970)
0.232 (0.125)
0.144 (0.344)
SSR Absence
0.534 (0.001*)
0.404 (0.020*)
0.500 (0.003*)
Data are presented as spearman (rs) or point biserial (rp) correlation coefficient (p value)
CSP Cutaneous Silent Period M Median nerve stimulation, OL Onset Latency, S Sural nerve stimulation, SSR Sympathetic Skin Response, aAmp Average Amplitude, μV Microvolt, H Hand-to-hand stimulation, F Foot-to-foot stimulation
Table 7
Correlation between SSR amplitudes and CSP in group I patients
Variable
CSP-M OL (ms)
CSP-S OL (ms)
CSP-S Duration (ms)
SSR-H aAmp. (μv)
− 0.335 (0.223)
− 0.256 (0.399)
0.463 (0.082)
SSR-F aAmp. (μv)
− 0.117 (0.677)
− 0.152 (0.621)
− 0.091 (0.746)
SSR Absence
0.146 (0.604)
− 0.291 (0.335)
0.032 (0.909)
Data are presented as spearman (rs) or point biserial (rp) correlation coefficient (p value)
CSP Cutaneous Silent Period, M Median nerve stimulation, OL Onset Latency, S Sural nerve stimulation, SSR Sympathetic Skin Response, aAmp Average Amplitude, μV Microvolt, H Hand-to-hand stimulation, F Foot-to-foot stimulation
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The diagnostic performance varied when assessing the sensitivity and specificity of CSP and SSR in diagnosing diabetic pure SFN; CSP latencies and CSP-S duration were all of fair to good specificity and poor sensitivity, and SSR absence and lower limb amplitude were very specific, but with poor sensitivity (Fig. 6). However, on combining the sensitivities of CSP onset latencies with each of SSR amplitudes and absence, the sensitivity improved (Table 8).
Fig. 6
ROC curve of CSP and SSR in diagnosing diabetic pure small fiber neuropathy. CSP-M OL > 81.4 ms had a 60% sensitivity and an 80% specificity. CSP-S OL > 114.7 ms and CSP-S duration ≤ 30.2 had 69.2% and 40% sensitivity, respectively, and each had an 86.7% specificity. SSR-H aAmp. ≤ 1877.6 μV had a 53.3% sensitivity and an 80% specificity. SSR-F aAmp. ≤ 162.8 and SSR absence had 33% and 26.7% sensitivity, respectively, and both had a 100% specificity. CSP Cutaneous Silent Period, M Median nerve stimulation, OL Onset Latency, S Sural nerve stimulation, SSR Sympathetic Skin Response; aAmp Average Amplitude, μV Microvolt, H Hand-to-hand stimulation, F Foot-to-foot stimulation
CSP Cutaneous Silent Period, M Median nerve stimulation, OL Onset Latency, S Sural nerve stimulation: Duration, SSR Sympathetic Skin Response, aAmp: Average Amplitude, μV: Microvolt
*If either test is positive
**If both tests are positive
Discussion
Due to the lack of early routine and reliable screening tools, many cases of diabetic neuropathy are diagnosed late, and at this later stage, it may not be very helpful as early as detecting in the stage of small fiber affection, as these fibers have been proposed to have a better regenerative capacity and can modify the degenerative behavior of diabetic peripheral neuropathy (DPN) when early approached [5, 29, 30].
In the current study, both age and gender distributions were adjusted, with no statistically significant difference among the three groups. Female predominance was observed among all our study groups, and that was similar to previous reports; even so, some reports considered the female gender as a risk factor for developing neuropathy in diabetic patients [31, 32]. Mean age was slightly higher in MFN patients. Previous reports suggested that older age may be associated with the incidence and/or severity of neuropathy in diabetic patients [33, 34].
Regarding anthropometric measures, no significant differences were found among the study groups in each of the body weight, height, and body mass index (BMI). Previous studies reported similar results [31, 35]. However, waist circumference was significantly larger in patients with MFN in relation to healthy subjects, with no difference between SFN and healthy groups. In fact, previous studies concluded that waist circumference may be a better index for predicting the risk of neuropathy than BMI in diabetic patients [36, 37]. Some other trending data suggested that increased waist circumference “central obesity” may be significantly associated with neuropathy, even in normoglycemic patients [38‐40].
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Several clinical scales were used to initially evaluate patients with diabetic SFN. Among these scales is the Douleur Neuropathique en 4 “DN4” questionnaire. It is a useful tool that can help to screen for neuropathic pain, which is a common symptom of SFN [41]. The DN4 questionnaire has been well validated in a number of studies and has a high sensitivity and specificity for detecting neuropathic pain in patients with either central neuropathic pain or polyneuropathies [22, 42], A total score of 3 or more indicates a high probability of neuropathic pain [41]. The DN4 median total scores were significantly higher in MFN patients than SFN ones. However, NRS median scores were higher in SFN patients than MFN ones, with no statistically significant difference. The DN4 aims to evaluate the attributes of neuropathic pain, such as burning, coldness, and electric shock, as well as the accompanying symptoms in the affected region, including tingling, pins and needles sensation, numbness, and itching, and it does not evaluate pain severity, unlike the simple, yet subjective NRS. [23, 43].
Some reports have suggested that SFN is more likely to cause neuropathic pain than MFN, and that the pain is more severe and widespread in SFN than in MFN [44]. This may be because SFN affects the small nerve fibers that are responsible for transmitting pain signals to the brain, while MFN affects both small and large fibers that may modulate or inhibit pain perception [45, 46]. Moreover, SFN may induce central sensitization and altered descending pathways that may amplify and maintain neuropathic pain. However, other studies have reported that the severity of neuropathic pain is not related to the type of nerve fiber damage, but rather to the degree of nerve fiber loss and dysfunction. Therefore, patients with MFN may also experience severe neuropathic pain if they have significant loss of both small and large nerve fibers [6, 47].
Intraepidermal nerve fiber density (IENFD) in distal punch skin biopsy is considered the gold standard for diagnosing small fiber neuropathy [48]. Undoubtedly, median IENFD was significantly lower in both SFN and MFN patients. Yet, IENFD was significantly lower in MFN than SFN patients. This could raise the attention to the continuous injurious process to the small fibers as the process of neuropathy advances in diabetic patients even after the affection of the larger nerve fibers. Although, age was slightly higher in MFN patients and eventually we could predict lower IENFD in these patients. However, damage of small fibers could be monitored at least by assessing neuropathic pain severity, and we observed in both SFN and MFN patients that NRS did not significantly differ. Galosi and colleagues [49] reported that neuropathic pain frequency did not differ between SFN and MFN; furthermore, they interestingly found that neuropathic pain was also reported in pure large fiber neuropathy, and they explained that there may be nociceptive nerve terminals that are affected and cannot even be detected by the gold standard IEFND. Perhaps there may be pain sensitization that could take place in dorsal root ganglion neurons, or even centrally [50‐52].
When evaluating the neuropathic pain severity, the 11-point numeric pain rating scale (NRS) may be a useful tool, and add to the wider picture of neuropathic pain evaluation by the DN4 [53, 54], however it may be influenced by other factors, such as mood, cognition, or expectations, that may affect the patient’s perception and reporting of pain, and may not reflect the patient’s satisfaction or quality of life [43]. Therefore, we implemented the EuroQoL-5D-5L (EQ-5D-5L) index utility scores to evaluate the quality of life in the studied patients.
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In this study, median EQ-5D-5L utility scores were significantly lower (meaning poorer quality of life) in SFN “0.587 (IQR 0.277–0.726)” and MFN “0.400 (IQR − 0.086–0.726)” patients, each in relation to healthy subjects “0.819 (IQR 0.765–0.892)”, with no statistically significant differences between SFN and MFN patients. EQ-5D-5L is a useful tool that can assess quality of life in patients with SFN, as the somatosensory and/or autonomic symptoms may affect patients’ physical, psychological, and social functioning [3, 55]. However, there is limited evidence on the use of EQ-5D-5L in patients with SFN. Gibbons and colleagues [56] compared the health-related quality of life of patients with neuropathic and non-neuropathic postural tachycardia syndrome (POTS), a condition that may be associated with SFN. The study found that patients with neuropathic POTS, defined by abnormal intra-epidermal nerve fiber density (IENFD) and abnormal small fiber and sudomotor function, had lower EQ-5D-5L utility scores “0.68 ± 0.19” than patients with non-neuropathic POTS “0.78 ± 0.16”, suggesting that the EQ-5D-5L may be able to detect differences in quality of life between patients with SFN and those without.
Clinical evaluation of SFN cannot only include assessment of neuropathic pain. The physical examination findings predominantly include reduced sensitivity to pinprick and temperature, the presence of allodynia, and occasionally diminished vibratory feeling. In certain instances, it is possible that there may be an absence of remarkable physical examination findings [41, 57]. In the current study, we used UENS to initially assess the somatosensory affection; it is is a clinical scale that was developed to assess the severity and distribution of sensory loss in patients with early diabetic SFN, with high interrater reliability, sensitivity, and specificity. In our study, we used a cutoff value of 4 or more to initially evaluate and stratify diabetic patients with SFN and later confirm the diagnosis by assessing the IENFD. This cutoff value was previously described with high sensitivity (82.9–92%) for detecting SFN [20, 58].
In the current study, the median UENS total scores in SFN patients were 8 (5–9) compared to 18 (11–21) in MFN patients, with a statistically significant difference. This was nearly similar to Zilliox and colleagues [58] study, in which patients with impaired glucose tolerance and SFN had mean UENS scores of 6.25 ± 1.10, compared to 14.13 ± 1.86 when larger nerve fibers were affected. Additionally, total UENS scores correlated strongly with all of our severity assessment measures, positively with NRS and TCNS, and negatively with EQ-5D-5L and IENFD. Singleton and colleagues [59] reported that UENS can be used to monitor progression in diabetic SFN, and follow-up scores can be utilized as endpoints for cases of SFN in clinical trials.
Glycosylated hemoglobin (HbA1c), plays an important role in the development and progression of diabetic neuropathy [60]. Chronic hyperglycemia induces metabolic and vascular changes that injure peripheral nerves. Elevated HbA1c causes intracellular accumulation of sorbitol via the polyol pathway, depletion of nerve myoinositol, and oxidative stress [61]. HbA1c provides an estimate of average blood glucose levels over the previous 2–3 months. In the current study, median HbA1c was higher in SFN patients in relation to MFN patients, with no statistically significant difference. Although SFN may be very painful to the diabetic patient, it is considered as a “milder” or an “early” neuropathy, before progression to MFN [6], while diabetes duration was significantly higher in MFN patients with a median of 15 years in relation to a median of 7 years in SFN patients. In fact, mean HbA1c over a longitudinal period may be a better marker for both the development and severity of diabetic neuropathy. A reported HbA1c of 6.5–7.1% over a 3-year follow-up as a cutoff value can be used for discrimination between diabetic patients with DPN and without, and there is a controversial role of increased HbA1c variability as an indicator for DPN [60, 62].
Similarly, the serum levels of the lipid profile tests may be dynamic to an extent; patients may be already on treatment, and longitudinal follow-up to the degree of control under treatment may reveal significant risk to neuropathy development and its severity [35]. Thus, when evaluating their possible risk, it is better to describe the state of metabolic syndrome (MetS). MetS diagnosis was made when 3 of the 5 criteria were met, with special consideration to waist circumference measure adjustment for the Egyptian population [18]. This did not include the exclusive diagnosis of diabetes mellitus or impaired glucose intolerance if other criteria were met.
Metabolic syndrome (MetS) was reported to be associated with peripheral neuropathy “cryptogenic sensory peripheral neuropathy” independent of the glycemic state [63], suggesting that these other MetS components may at least contribute in a similar way to impaired glycemic status, especially type II diabetes mellitus [64]. Obesity is believed to be the primary contributing factor in MetS and leads to an elevated reservoir of long-chain fatty acids that can cross the blood-nerve barrier, thereby causing neuroinflammation. The occurrence of oxidative stress in neurons initiates a series of subsequent pro-inflammatory cytokines and chemokines, leading to the production of oxidized cholesterol [65]. Also, dyslipidemia can exert an influence on neuronal and Schwann cell damage, hence contributing to the development of neuropathy associated with MetS, through its possible effects on mitochondria, altering its axonal transport, in addition to the production of reactive oxygen species resulting in the oxidation of more low-density lipoproteins, hence causing further damage to the mitochondrial membrane [66, 67].
In addition to routine nerve conduction studies, subjects were evaluated by the CSP and SSR, both of which are easy electrophysiological tests that can be performed easily in any EMG lab. CSP represents a transient inhibition of voluntary muscle contraction on EMG in response to painful stimulation of sensory or mixed nerves [9]. CSP was first described in 1973 [68], it has mostly been investigated in relation to the hand muscles following electrical stimulation of the digital nerves, and alternative stimulation paradigms and recording locations have also been employed in research [69].
The CSP is primarily mediated by slow-conducting, A-delta-type nociceptive fibers, and it may be viewed as a component of a broader nocifensive response, which also includes the withdrawal flexor reflex. While electrical stimulation could elicit both inhibitory and excitatory responses, it appears that CSP tends to be more prominent in distal muscles, whilst the muscle’s withdrawal reflex is more prevalent in proximal muscles. Hence, the primary purpose of the CSP appears to be the facilitation of swift limb withdrawal from a potentially harmful stimulus. This is achieved by the selective suppression of muscles involved in reaching and gripping, such as those in the hand, while concurrently enabling the activation of proximal muscles responsible for limb retraction [69, 70].
In the current study, CSP was recorded from the relative muscle after stimulating each of the left median nerve in the upper limb and the right sural nerve in the lower limb. Onset latencies (OL), especially of lower limbs, were significantly delayed, and CSP duration on stimulation sural nerve (CSP-S) was significantly shorter in patients’ groups. The results were in concordance with previous research that studied either CSP in the upper limb alone or both upper and lower limbs, interpreting the results of onset latencies and duration [71‐73].
However, results were in contrast to what Koytak and colleagues [74] who found significant differences in the lower limb only. CSP-M OL in suspected SFN patients was lower than in SFN patients in our study (67.24 ± 12.71 versus 83.7 “72.8–89.9”), and also in the control group (61.39 ± 10.92 versus 76 “70.5–81.4”). In their study, CSP-S-OL was significantly delayed in SFN patients (101.58 ± 14.52) in relation to controls (93.46 ± 11.24), and both latencies were not delayed as much as what we reported in the current study, both in SFN patients (120.2 “108.35–125.2”) and in controls (109.3 “103.1–113.2”). They also reported significantly shorter CSP-S in SFN patients (39.26 ± 12.40) in relation to controls (62.32 ± 15.41). Normative data may differ from lab to lab, and among different populations. Although more patients and controls were studied, they did not use a confirmatory test for SFN, as the IENFD in distal leg skin biopsy.
In the current study, CSP-M OL, and CSP-S OL were correlated positively, and CSP-S negatively with neuropathic pain and neuropathy symptoms severity, and inversely correlated with IENFD. Also, the CSP latencies, especially in the upper limb, were correlated negatively with poorer quality of life assessed by EQ-5D-5L. In contrast, Truini and colleagues [75] did not find an association between CSP parameters and pain intensity. Only 30% of their studied patients were diabetic, and the rest were diagnosed with sensory neuropathy of other etiologies. Neuropathic pain in diabetes may be of different pathophysiological characters, with involved complex central and peripheral mechanisms [5]. Despite the fact that CSP is considered as an acute nocifensive protective reflex and can remain intact on top of the chronic neuropathic pain [76], pain response may be delayed than usual, depending on the function of Aδ nerve fibers pathway.
The SSR was first described in 1984 [77], it assesses the sympathetic efferent pathway mediating sweating. The SSR is elicited by various internal or external stimuli which activate the reflex arcs of the sympathetic nervous system to produce measurable potential changes in the skin [10, 78]. In the current study, SSR amplitudes were significantly lower in MFN patients in relation to healthy subjects in both upper and lower limbs, and in relation to SFN patients in the lower limb. SSR response was considered absent when at least one lower limb response was absent. It was mainly absent in MFN patients (66.7%), and in 26.7% of patients with SFN, and present in all healthy subjects. We did not study SSR latencies as SSR amplitudes are of greater significance than latencies in assessing sweat production [79], Koytak and colleagues [74] have found a significantly lower SSR amplitudes in the lower limbs, but not the upper limbs, in patients with suspected SFN. Though, they did not use a confirmatory test for SFN. However, Lin and colleagues [10] found that SSR amplitudes were significantly lower in diabetic patients with confirmed SFN.
The CSP latencies, especially in the upper limb, were correlated negatively with SSR amplitude and positively with SSR absence. Lower limb CSP results were not as significant as upper limb ones. This could further suggest a potential relation between sudomotor and somatosensory symptoms in diabetic patients; perhaps it may be looked at as a “continuum” of symptoms that arise from subsequent affection of nerve fibers. However, in patients with pure SFN, no significant correlation was found between CSP and SSR, similarly to what Kamel and colleagues [71] and Thaisetthawatkul and colleagues [80] had found, suggesting that earlier in diabetic neuropathy, there may be a predilection for either Aδ pain or C sudomotor nerve fibers, so we should be cautious when we screen for both symptoms, and their clinical evaluation should be performed separately.
Conclusion
Cutaneous silent period (CSP) and SSR are easily conducted electrophysiological tests that may detect small fiber affection in diabetic patients, and they might have the potential to monitor neuropathy severity and progression, still with poor sensitivity and eventually cannot be used as initial screening tests for those patients, but this sensitivity improved on combining the sensitivities of CSP onset latencies with that of SSR amplitudes and absence. We should study more diabetic patients with pure SFN to confirm our findings, especially with different age groups. However, skin biopsy staining kits for intraepidermal nerve fibers are expensive and not universally available due to various supply chain issues, and this already posed a financial constraint on the sample size, besides a delay in our study timeframe.
Somatosensory and sudomotor symptoms in diabetic neuropathy can coexist; still, there was no obvious correlation between both symptoms, and suspected diabetic patients with small fiber affection should be screened for both.
The UENS may be a better clinical scale than the TCNS to evaluate the somatosensory symptoms of diabetic small fiber neuropathy. Also, the Arabic version of EQ-5D-5L questionnaire can be used to assess the quality of life in patients with diabetic small and mixed-fiber neuropathy. Besides UENS, it is important to establish sensitive and more objective small fiber biomarkers to monitor disease progression for any future longitudinal diabetic or non-diabetic small fiber neuropathy clinical treatment trials.
Acknowledgements
We are deeply grateful to our patients and their families for their continuing support throughout this study. We would also like to thank Mohamed Kassem, the pathology lab technician for his diligent efforts in preparing and staining the skin biopsy slides, and Mohamed Elsherif, professor of pathology in Tanta University, for his vital assistance with analyzing the skin biopsy results.
Declarations
Ethics approval and consent to participate
The study protocol was approved by the Research Ethics Committee, Faculty of Medicine, Tanta University, Egypt, IRB0010038 (approval code: 34059/8/20). Participation was voluntary and all contributors received detailed information about the aims of this research work and an informed written consent was obtained prior to the commencement of the study.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
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Wer insgesamt zuversichtlicher aufs Leben blickt, trägt ein geringeres Risiko, später einmal an Demenz zu erkranken als pessimistischere Zeitgenossen. Dafür sprechen zumindest Ergebnisse einer Längsschnittdatenanalyse aus den USA. Ob mehr Optimismus allerdings tatsächlich einer Demenz vorbeugt, bleibt unklar.
Eine hochdosierte Influenza-Vakzine geht mit einer verzögerten Demenzdiagnose einher. Darauf deutet eine Auswertung von US-Gesundheitsdaten hin. Besonders auffällig sind die Effekte in den ersten Monaten nach der Impfung.
Intensive Senkung eines erhöhten Blutdrucks kann nach einer intrazerebralen Blutung die funktionelle Erholung verbessern – mutmaßlich über eine Reduktion der Hämatomausdehnung. Offenbar hängt das aber vom Ausgangsvolumen ab, wie eine Analyse ergeben hat.
Da schmeckt das Rinderfilet gleich doppelt so gut: Fleisch beugt einer aktuellen Studie zufolge einer Demenz vor. Allerdings gilt das nur für ApoE4-Träger. Diese haben sich im Laufe der Evolution offenbar an einen hohen Fleischkonsum angepasst – und brauchen ihre Steak-Rationen.
