Clinical Features

Nunzi, Enrico; Massone, Cesare; Noto, Salvatore

doi:10.1007/978-88-470-2376-5_10

Cited by 5 publications

(6 citation statements)

References 3 publications

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“…This chronic infectious condition, caused by Mycobacterium leprae, can affect the cells lining blood and lymph vessels, sensory, motor and autonomic nerves, eyes, bones, and the upper respiratory tract [27,28]. Exploring the epidemiology of this disease unveils the complex dynamics underlying its occurrence [9]. In addition to the medical complexities, individuals diagnosed with leprosy endure social discrimination, face social exclusion, suffer from a diminished quality of life and often struggle with permanent disfigurement [29].…”

Section: Leprosymentioning

confidence: 99%

“…Despite its high incidence in some regions, estimates show that only 5% of people exposed to the leprosy pathogen are actually infected, and only 20% of them develop the disease [9]. Even people who do not develop the disease, because they have innate immunity, may experience a period in which the bacillus is released through the upper respiratory tract, which is the most common route of transmission [10,11].…”

Section: Introductionmentioning

confidence: 99%

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Artificial Intelligence on Diagnostic Aid of Leprosy: A Systematic Literature Review

Fernandes,

Teles,

Fernandes

et al. 2023

JCM

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Leprosy is a neglected tropical disease that can cause physical injury and mental disability. Diagnosis is primarily clinical, but can be inconclusive due to the absence of initial symptoms and similarity to other dermatological diseases. Artificial intelligence (AI) techniques have been used in dermatology, assisting clinical procedures and diagnostics. In particular, AI-supported solutions have been proposed in the literature to aid in the diagnosis of leprosy, and this Systematic Literature Review (SLR) aims to characterize the state of the art. This SLR followed the preferred reporting items for systematic reviews and meta-analyses (PRISMA) framework and was conducted in the following databases: ACM Digital Library, IEEE Digital Library, ISI Web of Science, Scopus, and PubMed. Potentially relevant research articles were retrieved. The researchers applied criteria to select the studies, assess their quality, and perform the data extraction process. Moreover, 1659 studies were retrieved, of which 21 were included in the review after selection. Most of the studies used images of skin lesions, classical machine learning algorithms, and multi-class classification tasks to develop models to diagnose dermatological diseases. Most of the reviewed articles did not target leprosy as the study’s primary objective but rather the classification of different skin diseases (among them, leprosy). Although AI-supported leprosy diagnosis is constantly evolving, research in this area is still in its early stage, then studies are required to make AI solutions mature enough to be transformed into clinical practice. Expanding research efforts on leprosy diagnosis, coupled with the advocacy of open science in leveraging AI for diagnostic support, can yield robust and influential outcomes.

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Section: Leprosymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence on Diagnostic Aid of Leprosy: A Systematic Literature Review

Fernandes,

Teles,

Fernandes

et al. 2023

JCM

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“…However, late diagnosis and treatment of leprosy can result in permanent disabilities associated with social stigma and economic hardships. 1 The disease has two main forms: paucibacillary (PB) and multibacillary (MB). This classification is based on clinical manifestations and skin smear results.…”

Section: Introductionmentioning

confidence: 99%

Detailed case analysis of leprosy patients from 2015–2019 in Sri Lanka: Does data quality require improvement?

Ferdinando,

Magodaratna,

Chandraratne

et al. 2024

LEPROSY

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Sri Lanka is among the 16 countries with the highest leprosy burden. There have been no reviews of the globally reported data from Sri Lanka and data quality has not been ascertained. Methods We conducted a detailed analysis of cases in the leprosy databases available at the Anti-Leprosy Campaign (ALC). Details of all reported cases of leprosy from 2015 to 2019 were analysed by a panel of experts. In the event of discrepancies or missing data, additional information and new datasheets were obtained from ALC through personal communication.Results The total number of leprosy cases reported over the period (2015-2019) was 9294, and the average annual number of cases was within the range of 1749-2002. Regarding the accuracy and validity of the key indicators, the major indicators were within the range of other parallel data sources, with the exception of 2015. However, when analysing the datasets, a clear observation was that databases were created using different terminology, and there were no standard data entry guidelines available throughout this time period, which may have affected the completeness of the data, thus affecting data quality. Digit preferences, duplicates, and outliers, which were mainly confined to a few years, were observed.

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“…Although the application of multidrug therapy (MDT) has reduced cases of leprosy worldwide, every year there are reports of disease recurrence events in patients who completed MDT, which may be due to the persistence of the bacillus in the tissues [18,19]. The growth of surviving bacilli, or those in the latent phase within the SCs, can occur even some years after the termination of MDT [18,20].…”

Section: Introductionmentioning

confidence: 99%

Mycobacterium leprae’s Infective Capacity Is Associated with Activation of Genes Involved in PGL-I Biosynthesis in a Schwann Cells Infection Model

Chavarro-Portillo

Soto

Guerrero

2023

IJMS

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Peripheral nerves and Schwann cells (SCs) are privileged and protected sites for initial colonization, survival, and spread of leprosy bacillus. Mycobacterium leprae strains that survive multidrug therapy show a metabolic inactivation that subsequently induces the recurrence of typical clinical manifestations of leprosy. Furthermore, the role of the cell wall phenolic glycolipid I (PGL-I) in the M. leprae internalization in SCs and the pathogenicity of M. leprae have been extensively known. This study assessed the infectivity in SCs of recurrent and non-recurrent M. leprae and their possible correlation with the genes involved in the PGL-I biosynthesis. The initial infectivity of non-recurrent strains in SCs was greater (27%) than a recurrent strain (6.5%). In addition, as the trials progressed, the infectivity of the recurrent and non-recurrent strains increased 2.5- and 2.0-fold, respectively; however, the maximum infectivity was displayed by non-recurrent strains at 12 days post-infection. On the other hand, qRT-PCR experiments showed that the transcription of key genes involved in PGL-I biosynthesis in non-recurrent strains was higher and faster (Day 3) than observed in the recurrent strain (Day 7). Thus, the results indicate that the capacity of PGL-I production is diminished in the recurrent strain, possibly affecting the infective capacity of these strains previously subjected to multidrug therapy. The present work opens the need to address more extensive and in-depth studies of the analysis of markers in the clinical isolates that indicate a possible future recurrence.

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Clinical Features

Cited by 5 publications

References 3 publications

Artificial Intelligence on Diagnostic Aid of Leprosy: A Systematic Literature Review

Artificial Intelligence on Diagnostic Aid of Leprosy: A Systematic Literature Review

Detailed case analysis of leprosy patients from 2015–2019 in Sri Lanka: Does data quality require improvement?

Mycobacterium leprae’s Infective Capacity Is Associated with Activation of Genes Involved in PGL-I Biosynthesis in a Schwann Cells Infection Model

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