Deriving reference values for nerve conduction studies from existing data using mixture model clustering

Clinical Neurophysiology, vol. 132, pp. 1820–1829

Abstract

OBJECTIVE: to obtain locally valid reference values (RVs) from existing nerve conduction study (NCS) data. METHODS: we used age, sex, height and limb temperature-based mixture model clustering (MMC) to identify normal and abnormal measurements on NCS data from two university hospitals. We compared MMC-derived RVs to published data; examined the effect of using different variables; validated MMC-derived RVs using independent data from 26 healthy control subjects and investigated their clinical applicability for the diagnosis of polyneuropathy. RESULTS: MMC-derived RVs were similar to published RVs. Clustering can be achieved using only sex and age as variables. MMC is likely to yield reliable results with fewer abnormal than normal measurements and when the total number of measurements is at least 300. Measurements from healthy controls fell within the 95% MMC-derived prediction interval in 97.4% of cases. CONCLUSIONS: MMC can be used to obtain RVs from existing data, providing a locally valid, accurate reflection of the (ab)normality of an NCS result. SIGNIFICANCE: .

Authors 7

1. Robert H. A. M. Reijntjes Aachen Department of Neurology, Leiden University Medical Center (LUMC)

   Leiden University Medical Center

   Affiliation as printed

   Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands. Electronic address: r.reijntjes@lumc.nl

   Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands

2. Wouter V. Potters

   Amsterdam Neuroscience · Amsterdam University Medical Centers · University of Amsterdam

   Affiliation as printed

   Department of Neurology, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Amsterdam, the Netherlands. Electronic address: w.v.potters@amsterdamumc.nl

   Department of Neurology, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Amsterdam, the Netherlands

3. Fabian I. Kerkhof Aachen Department of Neurology, Leiden University Medical Center (LUMC)

   Leiden University Medical Center

   Affiliation as printed

   Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands. Electronic address: f.i.kerkhof@lumc.nl

   Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands

4. Erik W. van Zwet Aachen Department of Biostatistics, Leiden University Medical Center

   Leiden University Medical Center

   Affiliation as printed

   Department of Biostatistics, Leiden University Medical Center, Leiden, the Netherlands. Electronic address: e.w.van_zwet@lumc.nl

   Department of Biostatistics, Leiden University Medical Center, Leiden, the Netherlands

5. Ineke A. van Rossum Aachen Department of Neurology, Leiden University Medical Center (LUMC)

   Leiden University Medical Center

   Affiliation as printed

   Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands. Electronic address: i.a.van_rossum@lumc.nl

   Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands

6. Camiel Verhamme

   Amsterdam Neuroscience · Amsterdam University Medical Centers · University of Amsterdam

   Affiliation as printed

   Department of Neurology, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Amsterdam, the Netherlands. Electronic address: c.verhamme@amsterdamumc.nl

   Department of Neurology, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Amsterdam, the Netherlands

7. Martijn Rudolf Tannemaat corresponding Aachen Department of Neurology, Leiden University Medical Center (LUMC)

   Leiden University Medical Center

   Affiliation as printed

   Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands. Electronic address: m.r.tannemaat@lumc.nl

   Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands