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Consensus on the Diagnostic Algorithm for Chronic Nodular Prurigo

Authors: Ortiz de Frutos, Javier; Serra Baldrich, Esther; Tribó Boixareu, María José; Armario Hita, Jose Carlos; Carrascosa Carrillo, José Manuel; Figueras-Nart, Ignasi; Flórez Menéndez, Ángeles; +2 Authors

Consensus on the Diagnostic Algorithm for Chronic Nodular Prurigo

Abstract

Chronic nodular prurigo (CNP) is a chronic dermatological disease characterized by the presence of chronic pruritus and pruritic nodular lesions. The aim of this study was to reach consensus among a group of experts based on a non-systematic literature review and an algorithm for the clinical diagnosis of CNP. The resulting algorithm is structured in 3 blocks: 1) early identification of the patient with a possible diagnosis of CNP; 2) diagnosis and assessment of CNP; and 3) categorization of CNP (identification of the underlying causes or associated comorbidities). We believe that this clinical algorithm can facilitate the correct diagnosis of patients with CNP. Additionally, it raises awareness on the need for a multidisciplinary approach and specific treatment of CNP, steps of paramount importance to make better therapeutic decisions.

Article disponible en castellà: http://hdl.handle.net/10230/71246

Country
Spain
Related Organizations
Keywords

Algorithm, Consensus, Pruritus, Diagnosis, Chronic nodular prurigo, Prurigo nodularis

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
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