A novel integrated molecular and serological analysis method to predict new cases of leprosy amongst household contacts.

Background Early 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 gr...

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Published in:PLOS Neglected Tropical Diseases
Main Authors: Rafael Silva Gama, Márcio Luís Moreira de Souza, Euzenir Nunes Sarno, Milton Ozório de Moraes, Aline Gonçalves, Mariane M A Stefani, Raúl Marcel González Garcia, Lucia Alves de Oliveira Fraga
Format: Article in Journal/Newspaper
Language:English
Published: Public Library of Science (PLoS) 2019
Subjects:
Online Access:https://doi.org/10.1371/journal.pntd.0007400
https://doaj.org/article/8c4b61adf8824a6e83728baba4f43d6b
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spelling ftdoajarticles:oai:doaj.org/article:8c4b61adf8824a6e83728baba4f43d6b 2023-05-15T15:15:29+02:00 A novel integrated molecular and serological analysis method to predict new cases of leprosy amongst household contacts. Rafael Silva Gama Márcio Luís Moreira de Souza Euzenir Nunes Sarno Milton Ozório de Moraes Aline Gonçalves Mariane M A Stefani Raúl Marcel González Garcia Lucia Alves de Oliveira Fraga 2019-06-01T00:00:00Z https://doi.org/10.1371/journal.pntd.0007400 https://doaj.org/article/8c4b61adf8824a6e83728baba4f43d6b EN eng Public Library of Science (PLoS) https://doi.org/10.1371/journal.pntd.0007400 https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0007400 https://doaj.org/article/8c4b61adf8824a6e83728baba4f43d6b PLoS Neglected Tropical Diseases, Vol 13, Iss 6, p e0007400 (2019) Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 article 2019 ftdoajarticles https://doi.org/10.1371/journal.pntd.0007400 2022-12-31T07:46:37Z Background Early 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. Methods The 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. Results The 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%. Conclusion The proposed model using RF allows for the diagnosis of leprosy with high sensitivity and specificity and the early identification of new ... Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic PLOS Neglected Tropical Diseases 13 6 e0007400
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic Arctic medicine. Tropical medicine
RC955-962
Public aspects of medicine
RA1-1270
spellingShingle Arctic medicine. Tropical medicine
RC955-962
Public aspects of medicine
RA1-1270
Rafael Silva Gama
Márcio Luís Moreira de Souza
Euzenir Nunes Sarno
Milton Ozório de Moraes
Aline Gonçalves
Mariane M A Stefani
Raúl Marcel González Garcia
Lucia Alves de Oliveira Fraga
A novel integrated molecular and serological analysis method to predict new cases of leprosy amongst household contacts.
topic_facet Arctic medicine. Tropical medicine
RC955-962
Public aspects of medicine
RA1-1270
description Background Early 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. Methods The 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. Results The 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%. Conclusion The proposed model using RF allows for the diagnosis of leprosy with high sensitivity and specificity and the early identification of new ...
format Article in Journal/Newspaper
author Rafael Silva Gama
Márcio Luís Moreira de Souza
Euzenir Nunes Sarno
Milton Ozório de Moraes
Aline Gonçalves
Mariane M A Stefani
Raúl Marcel González Garcia
Lucia Alves de Oliveira Fraga
author_facet Rafael Silva Gama
Márcio Luís Moreira de Souza
Euzenir Nunes Sarno
Milton Ozório de Moraes
Aline Gonçalves
Mariane M A Stefani
Raúl Marcel González Garcia
Lucia Alves de Oliveira Fraga
author_sort Rafael Silva Gama
title A novel integrated molecular and serological analysis method to predict new cases of leprosy amongst household contacts.
title_short A novel integrated molecular and serological analysis method to predict new cases of leprosy amongst household contacts.
title_full A novel integrated molecular and serological analysis method to predict new cases of leprosy amongst household contacts.
title_fullStr A novel integrated molecular and serological analysis method to predict new cases of leprosy amongst household contacts.
title_full_unstemmed A novel integrated molecular and serological analysis method to predict new cases of leprosy amongst household contacts.
title_sort novel integrated molecular and serological analysis method to predict new cases of leprosy amongst household contacts.
publisher Public Library of Science (PLoS)
publishDate 2019
url https://doi.org/10.1371/journal.pntd.0007400
https://doaj.org/article/8c4b61adf8824a6e83728baba4f43d6b
geographic Arctic
geographic_facet Arctic
genre Arctic
genre_facet Arctic
op_source PLoS Neglected Tropical Diseases, Vol 13, Iss 6, p e0007400 (2019)
op_relation https://doi.org/10.1371/journal.pntd.0007400
https://doaj.org/toc/1935-2727
https://doaj.org/toc/1935-2735
1935-2727
1935-2735
doi:10.1371/journal.pntd.0007400
https://doaj.org/article/8c4b61adf8824a6e83728baba4f43d6b
op_doi https://doi.org/10.1371/journal.pntd.0007400
container_title PLOS Neglected Tropical Diseases
container_volume 13
container_issue 6
container_start_page e0007400
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