| Literature DB >> 26124748 |
Aaron I Vinik1, Marie-Laure Nevoret2, Carolina Casellini1.
Abstract
Sudorimetry technology has evolved dramatically, as a rapid, non-invasive, robust, and accurate biomarker for small fibers that can easily be integrated into clinical practice. Though skin biopsy with quantitation of intraepidermal nerve fiber density is still currently recognized as the gold standard, sudorimetry may yield diagnostic information not only on autonomic dysfunction but also enhance the assessment of the small somatosensory nerves, disease detection, progression, and response to therapy. Sudorimetry can be assessed using Sudoscan™, which measures electrochemical skin conductance (ESC) of hands and feet. It is based on different electrochemical principles (reverse iontophoresis and chronoamperometry) to measure sudomotor function than prior technologies, affording it a much more practical and precise performance profile for routine clinical use with potential as a research tool. Small nerve fiber dysfunction has been found to occur early in metabolic syndrome and diabetes and may also be the only neurological manifestation in small fiber neuropathies, beneath the detection limits of traditional nerve function tests. Test results are robust, accomplished within minutes, require little technical training and no calculations, since established norms have been provided for the effects of age, gender, and ethnicity. Sudomotor testing has been greatly under-utilized in the past, restricted to specialized centers capable of handling the technically demanding and expensive technology. Yet, evaluation of autonomic and somatic nerve function has been shown to be one of the best estimates of cardiovascular risk. Evaluation of sweating has the appeal of quantifiable non-invasive determination of the integrity of the peripheral autonomic nervous system, and can now be accomplished rapidly at point of care clinics with the determination of ESC, allowing intervention for morbid complications prior to permanent structural nerve damage. We review here sudomotor function testing technology, the research evidence accumulated supporting the clinical utility of measuring ESC, the medical applications of sudorimetry now available to physicians with this device, and clinical vignettes illustrating its use in the clinical decision-making process.Entities:
Keywords: autonomic neuropathy; peripheral neuropathy; small nerve fiber; sudomotor; sudorimetry
Year: 2015 PMID: 26124748 PMCID: PMC4463960 DOI: 10.3389/fendo.2015.00094
Source DB: PubMed Journal: Front Endocrinol (Lausanne) ISSN: 1664-2392 Impact factor: 5.555
Figure 1Fibers of the peripheral nervous system: note the afferent and efferent connections among the small Aδ and C fibers (.
Figure 2Electrochemical skin conductance of feet receiver–operator characteristic (ROC) curve to reflect diabetic neuropathy. Area under the curve = 0.8755, p < 0.0001 (34).
Diagnostic efficiency of feet and hands electrochemical skin conductance to reflect diabetic neuropathy (Neurologic Impairment Score – lower limbs) (.
| Criterion | Sensitivity | Specificity | +LR | −LR | +PV | −PV | |
|---|---|---|---|---|---|---|---|
| Hands ESC | 64 | 78.33 | 85.71 | 5.48 | 0.25 | 61.04 | 93.26 |
| Feet ESC | 77 | 78.34 | 92.38 | 10.28 | 0.23 | 74.6 | 93.72 |
| Total NIS-LL | 1.5 | 76.67 | 85.71 | 5.37 | 0.27 | 95.83 | 46.15 |
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ESC, electrochemical skin conductance; +LR, positive likelihood ratio; −LR, negative likelihood ratio; NIS–LL, Neurologic Impairment Score–Lower Legs; +PV, positive predictive value; −PV, negative predictive value.
Spearman’s ρ ranked correlations of feet ESC with clinical, somatic, and autonomic measures of neuropathy in 48 patients with type 2 diabetes (.
| Feet ESC | Spearman ρ | ||
|---|---|---|---|
| DM duration | Feet ESC | −0.4904 | 0.0005 |
| Neurologic symptom score (NSS) | Feet ESC | −0.4437 | 0.0016 |
| Sensory score | Feet ESC | −0.6313 | <0.0001 |
| Motor score | Feet ESC | −0.5499 | <0.0001 |
| Total neuropathy score (TNS) | Feet ESC | −0.5851 | <0.0001 |
| Total NIS-LL motor | Feet ESC | −0.6687 | <0.0001 |
| Total NIS-LL sensory | Feet ESC | −0.6672 | <0.0001 |
| Total NIS-LL score | Feet ESC | −0.6160 | <0.0001 |
| Expiration/inspiration ratio (E/I) | Feet ESC | 0.4858 | 0.0005 |
| Valsalva ratio | Feet ESC | 0.3182 | 0.0275 |
| Deep breathing total spectral power (TSP) | Feet ESC | 0.4745 | 0.0008 |
| Deep breathing sdNN | Feet ESC | 0.4252 | 0.0029 |
| Deep breathing rmsSD | Feet ESC | 0.3778 | 0.0088 |
| Valsalva TSP | Feet ESC | 0.4320 | 0.0024 |
| Valsalva sdNN | Feet ESC | 0.3708 | 0.0103 |
| Valsalva rmsSD | Feet ESC | 0.3026 | 0.0387 |
| Great toe vibration detection | Feet ESC | −0.5003 | 0.0004 |
| Great toe pressure (monofilament) | Feet ESC | −0.6250 | <0.0001 |
| Great toe cold perception | Feet ESC | −0.4625 | 0.0012 |
| Great toe warm perception | Feet ESC | −0.4857 | 0.0006 |
| Great toe symptomatic pain | Feet ESC | −0.4397 | 0.0022 |
| Great toe mechanical pain | Feet ESC | −0.3508 | 0.0168 |
| Peroneal ankle amplitude (Amp) | Feet ESC | 0.4889 | 0.0005 |
| Peroneal below fibula Amp | Feet ESC | 0.5867 | <0.0001 |
| Peroneal below fibula conduction velocity (CV) | Feet ESC | 0.4724 | 0.0008 |
| Peroneal above fibula Amp | Feet ESC | 0.5496 | <0.0001 |
| Peroneal above fibula CV | Feet ESC | 0.4381 | 0.0021 |
| Sural Amp | Feet ESC | 0.5234 | 0.0043 |
| Sural CV | Feet ESC | 0.5503 | 0.0024 |
| Urine albumin/creatinine ratio | Feet ESC | −0.3724 | 0.0196 |
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DM, diabetes mellitus; ESC, electrochemical skin conductance; NIS-LL, neuropathy impairment score of lower legs; NRS, numeric rating score; rmsSD, root mean square of the difference of successive .
Figure 3Receiver operating characteristics (ROC) curves for feet ESC and skin biopsy using abnormal Utah Early Neuropathy Score (UENS) as the gold standard. Area under the curve (AUC) for ESC feet and intraepidermal nerve fiber density (IENFD) were similar (0.761, 0.752, respectively) (9).
Feet ESC diagnostic accuracy vs. established clinical tools.
| Study | Diagnostic variable | Comparison | Sensitivity (%) | Specificity (%) | PPV (%) | NPV (%) |
|---|---|---|---|---|---|---|
| Casellini ( | DPN | NIS-LL | 78 | 92 | 74 | 93 |
| Smith ( | Distal symmetric polyneuropathy | UENS | 77 | 67 | 59 | 83 |
| Yajnik ( | DPN | VPT | 73 | 62 | N/A | N/A |
| Eranki ( | DPN | VPT | 82 | 55 | N/A | N/A |
| Calvet ( | CAN – diabetes | CARTs | 83 | 63 | N/A | N/A |
| Ozaki ( | Diabetic kidney disease | eGFR, ACR | 94 | 78 | 81 | 93 |
ACR, albumin creatinine ratio; CAN, cardiac autonomic neuropathy; CARTs, cardiac autonomic reflex tests; DPN, diabetic peripheral neuropathy; eGFR, estimated glomerular filtration rate; NIS-LL, Neuropathy Impairment Score – Lower Limbs; PPV, positive predictive value; NPV, negative predictive value; UENS, Utah Early Neuropathy Score; VPT, vibration perception threshold.
Effects of age and gender on ESC measurements in 609 normal subjects.
| Age (years) | |||||||
|---|---|---|---|---|---|---|---|
| Overall | 21–30 | 31–40 | 41–50 | 51–60 | 61–70 | 71–80 | |
| ( | ( | ( | ( | ( | ( | ( | |
| Mean ± SD | 74.0 ± 8.7 | 74.7 ± 9.6 | 75.9 ± 8.8 | 74.0 ± 8.4 | 73.8 ± 8.3 | 71.1 ± 10.1 | 71.0 ± 9.6 |
| Median | 75.0 | 75.0 | 77.0 | 74.5 | 75.0 | 70.3 | 71.5 |
| 80th percentile interval | 61.5–85.0 | 62.6–86.2 | 62.6–87.0 | 62.0–85.0 | 62.0–85.0 | 58.9–83.6 | 55.9–81.4 |
| Mean ± SD | 82.8 ± 5.8 | 83.9 ± 5.8 | 84.2 ± 4.8 | 83.1 ± 5.2 | 82.7 ± 5.6 | 82.2 ± 4.2 | 75.5 ± 9.3 |
| Median | 83.5 | 84.5 | 85.0 | 84.5 | 83.0 | 83.0 | 79.0 |
| 80th percentile interval | 76.0–89.0 | 79.1–90.0 | 77.1–89.5 | 76.5–89.0 | 75.5–89.5 | 76.7–86.5 | 65.1–86.7 |
| ( | ( | ( | ( | ( | ( | ( | |
| Mean ± SD | 74.9 ± 9.6 | 76.0 ± 10.1 | 77.4 ± 6.6 | 75.2 ± 10.7 | 75.8 ± 7.7 | 72.3 ± 11.6 | 66.2 ± 10.0 |
| Median | 76.5 | 77.5 | 78.3 | 78.0 | 76.3 | 75.0 | 68.0 |
| 80th percentile interval | 62.5–86.5 | 63.0–87.5 | 69.1–85.6 | 61.1–87.9 | 66.7–86.4 | 56.1–85.6 | 52.5–78.3 |
| Mean ± SD | 81.5 ± 7.0 | 81.7 ± 7.6 | 81.2 ± 5.6 | 81.0 ± 7.1 | 84.0 ± 5.7 | 81.5 ± 4.4 | 76.0 ± 9.4 |
| Median | 82.5 | 82.5 | 81.0 | 83.0 | 84.5 | 81.8 | 79.3 |
| 80th percentile interval | 73.0–89.5 | 73.8–90.5 | 75.0–88.2 | 71.3–89.3 | 76.1–90.0 | 76.7–86.2 | 67.5–83.5 |
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Electrochemical skin conductance (ESC) zones for normal sudomotor function (green), moderate sudomotor dysfunction (yellow), and severe sudomotor dysfunction (red) as defined by racial background.
| Race | Hands ESC red zone | Hands ESC yellow zone | Hands ESC green zone | redFeet ESC red zone | Feet ESC yellow zone | Feet ESC green zone |
|---|---|---|---|---|---|---|
| Caucasian | 0–40 | 40–60 | 60–100 | 0–50 | 50–70 | 70–100 |
| African-American Ancestry | 0–30 | 30–50 | 50–100 | 0–40 | 40–60 | 60–100 |
| Asian, Indian | 0–40 | 40–60 | 60–100 | 0–40 | 40–60 | 60–100 |
All numeric values in micoSiemens (μS).
Data from Casellini, Gordon Smith, and Freedman (.
Change between baseline and 12-month follow-up in weight, waist, VO.
| Without follow-up of training level ( | Low weekly activity | High weekly activity | |||||
|---|---|---|---|---|---|---|---|
| Mean | SD | Mean | SD | Mean | SD | ||
| Change in weight (kg) | −0.9 | 3.4 | −1.6 | 4.0 | −3.3 | 4.8 | NS |
| Change in waist (cm) | −2.1 | 4.7 | −2.4 | 4.5 | −3.6 | 5.9 | NS |
| Change in estimated VO2max (METs) | +0.5 | 0.9 | +0.8 | 0.9 | +1.1 | 1.2 | NS |
| Change in hand ESC (μS) | +5.0 | 8.4 | +3.0 | 9.4 | +8.4 | 12.3 | 0.043 |
| Change in foot ESC (μS) | +5.6 | 8.9 | +4.9 | 8.9 | +10.8 | 12.8 | 0.024 |
| Change in ESC risk score (%) | −5.1 | 5.3 | −4.7 | 6.4 | −8.5 | 6.8 | 0.027 |
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Figure 4(A) ESC report dated October 19, 2012. (B) ESC report dated March 6, 2014.
Figure 5(A) ESC report dated February 19, 2013. (B) ESC report dated March 6, 2014.