Nerve Conduction Study (NCS)

Understanding the uses of Nerve Conduction Studies, QSART, IENFD, and SmartSKAN in the diagnosis of peripheral neuropathies

‘Peripheral neuropathy’ is an umbrella term that can designate a number of different conditions. These conditions may involve a single or several nerves, and may involve different types of nerves: motor, sensory, or autonomic. Nerves can also be classified by size: large (myelinated) or small/thin (unmyelinated).

No single test used in the diagnosis of neuropathies is 100% sensistive to detect all neuropathies. Different tests will be abnormal depending on which nerve or which type of nerve is involved.

Nerve Conduction Study (NCS):

NCS only measures large (myelinated) nerve function.

In a group of patients with painful neuropathy NCS was abnormal (diagnostic) in only 47 out of 92 (Novak 2001). In a second study of patients with painful neuropathy NCS was abnormal in 60 of 117 patients (Periquet 1999).

In a group of 318 diabetic patients with healed or ongoing foot ulcers, NCS was mildly abnormal in 70 patients and significant in 30 patients(Kiziltan 2007).

In a meta-analysis of tools to detect large-fiber neuropathy in diabetic patients, the authors found that abnormal vibration and monofilament tests are most predictive of a large fiber neuropathy (Kanji 2010).

Quantitative Sudomotor Axon Reflex Test (QSART):

This is a measure of the post-ganglionic sympathetic cholinergic nerve axons to the sweat glands. It measures autonomic function. These are often but not always affected similarly to small sensory nerve fibers. In the early stages of small fiber neuropathy, QSART may still be normal because some sensory nerves may be affected even earlier than the sympathetic nerves.

In the study of 92 patients with painful neuropathy, QSART was abnormal in 67 (72.8%) of patients (Novak 2001).

In a group of 56 patients with painful neuropathy, QSART was abnormal in 85% of large-patients with large fiber neuropathy but abnormal in only 69% of patients with small fiber neuropathy (Killian 2011).

In a group of 15 patients with clinically suspected small fiber sensory neuropathy, QSART was abnormal in 80% of patients (Tobin 1999).

Finally, Peltier studied neuropathy in impaired glucose tolerance patients and found that QSART had intraclass correlation coefficients (ICCs) of 0.52, meaning that if the test was performed twice on the same individual at 2 different times, it only correlated 52 out of 100 times with itself (Peltier 1999).

Intra-Epidermal Nerve Fiber Density (IENFD):

This is currently the gold standard for diagnosing small fiber neuropathy since it counts the number of small sensory nerves per mm of skin.

The sensitivity, however, is reported to be ‘about 88%’; therefore at least 12% of patients with small fiber neuropathy will have normal IENFD (Tavee 2009).

SmartSKAN:

SmartSKAN measures sympathetic nerves to the sweat glands of the palms and soles. Technologically and physiologically, there are a few differences from QSART, however.

Similarly to QSART, SmartSKAN is a screening tool for autonomic neuropathy. But because the sympathetic nerves will be damaged in parallel (though slightly slower than) small sensory nerve fibers, SmartSKAN can detect most small fiber neuropathies early.

According to Vinik et al., SmartSKAN sensitivity and specificity to measure diabetic neuropathy were 78% and 85-92%. The cut-off points for these values were 64μS for the hands and 77μS for the feet. In other words, any SmartSKAN value below 77 for the feet was considered diagnostic for diabetic neuropathy.

For screening of autonomic neuropathy, Calvet et al. calculated that SmartSKAN had a sensitivity of 83% and specifity of 63%. These values were based on a CAN risk score cut-off value of <40% calculated by the SmartSKAN device.

In contrast to QSART, SmartSKAN has a very high test/retest reliability. Correlation coefficients are 0.85 for the hands and 0.93 for the feet; i.e. the test will yield identical results 93 out of 100 times when performed twice on the same patient, even using different machines.