@article{EgenolfAltenschildescheKressetal.2021,
  author    = {Egenolf, Nadine and Altenschildesche, Caren Meyer zu and Kreß, Luisa and Eggermann, Katja and Namer, Barbara and Gross, Franziska and Klitsch, Alexander and Malzacher, Tobias and Kampik, Daniel and Malik, Rayaz A. and Kurth, Ingo and Sommer, Claudia and {\"U}{\c{c}}eyler, Nurcan},
  title     = {Diagnosing small fiber neuropathy in clinical practice: a deep phenotyping study},
  series = {Therapeutic Advances in Neurological Disorders},
  volume    = {14},
  journal   = {Therapeutic Advances in Neurological Disorders},
  issn      = {1756-2864},
  doi       = {10.1177/17562864211004318},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-232019},
  year      = {2021},
  abstract  = {Background and aims: Small fiber neuropathy (SFN) is increasingly suspected in patients with pain of uncertain origin, and making the diagnosis remains a challenge lacking a diagnostic gold standard. Methods: In this case-control study, we prospectively recruited 86 patients with a medical history and clinical phenotype suggestive of SFN. Patients underwent neurological examination, quantitative sensory testing (QST), and distal and proximal skin punch biopsy, and were tested for pain-associated gene loci. Fifty-five of these patients additionally underwent pain-related evoked potentials (PREP), corneal confocal microscopy (CCM), and a quantitative sudomotor axon reflex test (QSART). Results: Abnormal distal intraepidermal nerve fiber density (IENFD) (60/86, 70\%) and neurological examination (53/86, 62\%) most frequently reflected small fiber disease. Adding CCM and/or PREP further increased the number of patients with small fiber impairment to 47/55 (85\%). Genetic testing revealed potentially pathogenic gene variants in 14/86 (16\%) index patients. QST, QSART, and proximal IENFD were of lower impact. Conclusion: We propose to diagnose SFN primarily based on the results of neurological examination and distal IENFD, with more detailed phenotyping in specialized centers.},
  language  = {en}
}