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Revisiting primary neural leprosy: Clinical, serological, molecular, and neurophysiological aspects.

ABSTRACT: Leprosy neuropathy is considered the most common peripheral neuropathy of infectious etiology worldwide, representing a public health problem. Clinical diagnosis of primary neural leprosy (PNL) is challenging, since no skin lesions are found and the slit skin smear bacilloscopy is negative. However, there are still controversial concepts regarding the primary-neural versus pure-neural leprosy definition, which will be explored by using multiple clinical-laboratory analyses in this study.Seventy patients diagnosed with primary neural leprosy from 2014 to 2016 underwent clinical, laboratorial and neurophysiological evaluation. All patients presented an asymmetric neural impairment, with nerve thickening in 58.6%. Electroneuromyography showed a pattern of mononeuropathy in 51.4%. Positivity for ELISA anti-PGL1 was 52.9%, while the qPCR of slit skin smear was 78.6%. The qPCR of nerve biopsies was positive in 60.8%. Patients with multiple mononeuropathy patterns showed lower levels of anti-PGL-1 (p = 0.0006), and higher frequency of neural thickening (p = 0.0008) and sensory symptoms (p = 0.01) than those with mononeuropathy.PNL is not a synonym of pure neural leprosy, as this condition may include a generalized immune response and also a skin involvement, documented by molecular findings. Immunological, molecular, and neurophysiological tools must be implemented for diagnosing primary neural leprosy to achieve effective treatment and reduction of its resultant disabilities that still represent a public health problem in several developing nations. Finally, we propose a algorithm and recommendations for the diagnosis of primary neural leprosy based on the combination of the three clinical-laboratorial tools.

SUBMITTER: Santos DFD

PROVIDER: S-EPMC5720806 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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Revisiting primary neural leprosy: Clinical, serological, molecular, and neurophysiological aspects.

Santos Diogo Fernandes Dos DFD Mendonça Matheus Rocha MR Antunes Douglas Eulálio DE Sabino Elaine Fávaro Pípi EFP Pereira Raquel Campos RC Goulart Luiz Ricardo LR Goulart Isabela Maria Bernardes IMB

PLoS neglected tropical diseases 20171127 11

<h4>Background</h4>Leprosy neuropathy is considered the most common peripheral neuropathy of infectious etiology worldwide, representing a public health problem. Clinical diagnosis of primary neural leprosy (PNL) is challenging, since no skin lesions are found and the slit skin smear bacilloscopy is negative. However, there are still controversial concepts regarding the primary-neural versus pure-neural leprosy definition, which will be explored by using multiple clinical-laboratory analyses in ...[more]

PMID: 29176796

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Project description:BackgroundEarly detection of Mycobacterium leprae is a key strategy for disrupting the transmission chain of leprosy and preventing the potential onset of physical disabilities. Clinical diagnosis is essential, but some of the presented symptoms may go unnoticed, even by specialists. In areas of greater endemicity, serological and molecular tests have been performed and analyzed separately for the follow-up of household contacts, who are at high risk of developing the disease. The accuracy of these tests is still debated, and it is necessary to make them more reliable, especially for the identification of cases of leprosy between contacts. We proposed an integrated analysis of molecular and serological methods using artificial intelligence by the random forest (RF) algorithm to better diagnose and predict new cases of leprosy.MethodsThe study was developed in Governador Valadares, Brazil, a hyperendemic region for leprosy. A longitudinal study was performed, including new cases diagnosed in 2011 and their respective household contacts, who were followed in 2011, 2012, and 2016. All contacts were diligently evaluated by clinicians from Reference Center for Endemic Diseases (CREDEN-PES) before being classified as asymptomatic. Samples of slit skin smears (SSS) from the earlobe of the patients and household contacts were collected for quantitative polymerase chain reaction (qPCR) of 16S rRNA, and peripheral blood samples were collected for ELISA assays to detect LID-1 and ND-O-LID.ResultsThe statistical analysis of the tests revealed sensitivity for anti-LID-1 (63.2%), anti-ND-O-LID (57.9%), qPCR SSS (36.8%), and smear microscopy (30.2%). However, the use of RF allowed for an expressive increase in sensitivity in the diagnosis of multibacillary leprosy (90.5%) and especially paucibacillary leprosy (70.6%). It is important to report that the specificity was 92.5%.ConclusionThe proposed model using RF allows for the diagnosis of leprosy with high sensitivity and specificity and the early identification of new cases among household contacts.

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Dataset Information

Revisiting primary neural leprosy: Clinical, serological, molecular, and neurophysiological aspects.

Publications

Revisiting primary neural leprosy: Clinical, serological, molecular, and neurophysiological aspects.

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