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Clinical diagnosis of leprosy in non-endemic area using algorithm / 나학회지
Article in En | WPRIM | ID: wpr-1041646
Responsible library: WPRO
ABSTRACT
Background@#It has been essential that leprosy is included as differential diagnosis for diagnosing leprosy. But in non-endemic area like Korea, this is not enough for leprosy does not dwell in differential diagnosis. @*Objective@#To reach out diagnosis of leprosy as differentiating many diseases that are familiar or are considered by application of algorithm @*Methods@#We have collected review articles, textbooks, booklets, case reports of differential diagnosis of leprosy to classify them according to primary lesions, symptoms, and clinical characteristics. The major and important clues to diagnosis of leprosy were checked using algorithmic trees. @*Results@#1) It is important that leprosy is characterized by no itching sensation, no predilection of immune sites, and usually not monomorphic lesions except LL. 2) Additionally, leprosy does not usually proceed to tumor, generalized erythroderma, or alopecia of the scalp.3) Scales give no differentiating points in TT, BT, and BB lesions. 4) Annular papules and plaques are the most concerning lesions for diagnosing leprosy. 5) Nodules and diffuse infiltration of the eyebrows, ear auricles, and nose are not specific, but peculiar to MB. 6) When we consider diagnosing the skin diseases with myriads of clinical manifestation, such as mycosis fungoides, sarcoidosis, lupus erythematosus, Sweet syndrome, leprosy should be included for differential diagnosis. @*Conclusion@#We have made the decision trees for diagnosing leprosy. But on the other hand, we cannot reach the diagnosis of leprosy without knowledge of major characteristic clues of leprosy. Therefore, as the result highlights the necessity of education of clinical leprosy would increase.
Full text: 1 Database: WPRIM Language: En Journal: Korean Leprosy Bulletin Year: 2023 Document type: Article
Full text: 1 Database: WPRIM Language: En Journal: Korean Leprosy Bulletin Year: 2023 Document type: Article