Models for predicting the risk of illness in leprosy contacts in Brazil: Leprosy prediction models in Brazilian contacts.
Trop Med Int Health
; 29(8): 680-696, 2024 Aug.
Article
em En
| MEDLINE
| ID: mdl-38961761
ABSTRACT
OBJECTIVE:
This study aims to develop and validate predictive models that assess the risk of leprosy development among contacts, contributing to an enhanced understanding of disease occurrence in this population.METHODS:
A cohort of 600 contacts of people with leprosy treated at the National Reference Center for Leprosy and Health Dermatology at the Federal University of Uberlândia (CREDESH/HC-UFU) was followed up between 2002 and 2022. The database was divided into two parts two-third to construct the disease risk score and one-third to validate this score. Multivariate logistic regression models were used to construct the disease score.RESULTS:
Of the four models constructed, model 3, which included the variables anti-phenolic glycolipid I immunoglobulin M positive, absence of Bacillus Calmette-Guérin vaccine scar and age ≥60 years, was considered the best for identifying a higher risk of illness, with a specificity of 89.2%, a positive predictive value of 60% and an accuracy of 78%.CONCLUSIONS:
Risk prediction models can contribute to the management of leprosy contacts and the systematisation of contact surveillance protocols.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Hanseníase
Limite:
Adolescent
/
Adult
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Aged
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Child
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Child, preschool
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Female
/
Humans
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Male
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Middle aged
País/Região como assunto:
America do sul
/
Brasil
Idioma:
En
Revista:
Trop Med Int Health
Assunto da revista:
MEDICINA TROPICAL
/
SAUDE PUBLICA
Ano de publicação:
2024
Tipo de documento:
Article
País de afiliação:
Brasil