Pain drawings as a diagnostic tool for the differentiation between two pain-associated rare diseases (Ehlers-Danlos-Syndrome, Guillain-Barré-Syndrome).
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Authors
Wester, LarissaMücke, Martin
Bender, Tim Theodor Albert
Sellin, Julia
Klawonn, Frank
Conrad, Rupert
Szczypien, Natasza
Issue Date
2020-11-17
Metadata
Show full item recordAbstract
Background: The diagnosis of rare diseases poses a particular challenge to clinicians. This study analyzes whether patients' pain drawings (PDs) help in the differentiation of two pain-associated rare diseases, Ehlers-Danlos Syndrome (EDS) and Guillain-Barré Syndrome (GBS). Method: The study was designed as a prospective, observational, single-center study. The sample comprised 60 patients with EDS (3 male, 52 female, 5 without gender information; 39.2 ± 11.4 years) and 32 patients with GBS (10 male, 20 female, 2 without gender information; 50.5 ± 13.7 years). Patients marked areas afflicted by pain on a sketch of a human body with anterior, posterior, and lateral views. PDs were electronically scanned and processed. Each PD was classified based on the Ružička similarity to the EDS and the GBS averaged image (pain profile) in a leave-one-out cross validation approach. A receiver operating characteristic (ROC) curve was plotted. Results: 60-80% of EDS patients marked the vertebral column with the neck and the tailbone and the knee joints as pain areas, 40-50% the shoulder-region, the elbows and the thumb saddle joint. 60-70% of GBS patients marked the dorsal and plantar side of the feet as pain areas, 40-50% the palmar side of the fingertips, the dorsal side of the left palm and the tailbone. 86% of the EDS patients and 96% of the GBS patients were correctly identified by computing the Ružička similarity. The ROC curve yielded an excellent area under the curve value of 0.95.Citation
Orphanet J Rare Dis. 2020 Nov 17;15(1):323. doi: 10.1186/s13023-020-01542-1.Affiliation
HZI,Helmholtz-Zentrum für Infektionsforschung GmbH, Inhoffenstr. 7,38124 Braunschweig, Germany.Publisher
BMCPubMed ID
33203450Type
ArticleLanguage
enEISSN
1750-1172ae974a485f413a2113503eed53cd6c53
10.1186/s13023-020-01542-1
Scopus Count
The following license files are associated with this item:
- Creative Commons


