Predictive models for the diagnostic of human visceral leishmaniasis in Brazil.
Background and objectives In Brazil, as in many other affected countries, a large proportion of visceral leishmaniasis (VL) occurs in remote locations and treatment is often performed on basis of clinical suspicion. This study aimed at developing predictive models to help with the clinical managemen...
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ftdoajarticles:oai:doaj.org/article:ff6f4a54d2c7435da1caff1611c62e5e 2023-05-15T15:16:29+02:00 Predictive models for the diagnostic of human visceral leishmaniasis in Brazil. Tália S Machado de Assis Ana Rabello Guilherme L Werneck 2012-01-01T00:00:00Z https://doi.org/10.1371/journal.pntd.0001542 https://doaj.org/article/ff6f4a54d2c7435da1caff1611c62e5e EN eng Public Library of Science (PLoS) https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22389742/pdf/?tool=EBI https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0001542 https://doaj.org/article/ff6f4a54d2c7435da1caff1611c62e5e PLoS Neglected Tropical Diseases, Vol 6, Iss 2, p e1542 (2012) Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 article 2012 ftdoajarticles https://doi.org/10.1371/journal.pntd.0001542 2022-12-31T04:15:30Z Background and objectives In Brazil, as in many other affected countries, a large proportion of visceral leishmaniasis (VL) occurs in remote locations and treatment is often performed on basis of clinical suspicion. This study aimed at developing predictive models to help with the clinical management of VL in patients with suggestive clinical of disease. Methods Cases of VL (n = 213) had the diagnosis confirmed by parasitological method, non-cases (n = 119) presented suggestive clinical presentation of VL but a negative parasitological diagnosis and a firm diagnosis of another disease. The original data set was divided into two samples for generation and validation of the prediction models. Prediction models based on clinical signs and symptoms, results of laboratory exams and results of five different serological tests, were developed by means of logistic regression and classification and regression trees (CART). From these models, clinical-laboratory and diagnostic prediction scores were generated. The area under the receiver operator characteristic curve, sensitivity, specificity, and positive predictive value were used to evaluate the models' performance. Results Based on the variables splenomegaly, presence of cough and leukopenia and on the results of five serological tests it was possible to generate six predictive models using logistic regression, showing sensitivity ranging from 90.1 to 99.0% and specificity ranging from 53.0 to 97.2%. Based on the variables splenomegaly, leukopenia, cough, age and weight loss and on the results of five serological tests six predictive models were generated using CART with sensitivity ranging from 90.1 to 97.2% and specificity ranging from 68.4 to 97.4%. The models composed of clinical-laboratory variables and the rk39 rapid test showed the best performance. Conclusion The predictive models showed to be a potential useful tool to assist healthcare systems and control programs in their strategical choices, contributing to more efficient and more rational allocation of ... Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic PLoS Neglected Tropical Diseases 6 2 e1542 |
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Directory of Open Access Journals: DOAJ Articles |
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English |
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Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
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Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 Tália S Machado de Assis Ana Rabello Guilherme L Werneck Predictive models for the diagnostic of human visceral leishmaniasis in Brazil. |
topic_facet |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
description |
Background and objectives In Brazil, as in many other affected countries, a large proportion of visceral leishmaniasis (VL) occurs in remote locations and treatment is often performed on basis of clinical suspicion. This study aimed at developing predictive models to help with the clinical management of VL in patients with suggestive clinical of disease. Methods Cases of VL (n = 213) had the diagnosis confirmed by parasitological method, non-cases (n = 119) presented suggestive clinical presentation of VL but a negative parasitological diagnosis and a firm diagnosis of another disease. The original data set was divided into two samples for generation and validation of the prediction models. Prediction models based on clinical signs and symptoms, results of laboratory exams and results of five different serological tests, were developed by means of logistic regression and classification and regression trees (CART). From these models, clinical-laboratory and diagnostic prediction scores were generated. The area under the receiver operator characteristic curve, sensitivity, specificity, and positive predictive value were used to evaluate the models' performance. Results Based on the variables splenomegaly, presence of cough and leukopenia and on the results of five serological tests it was possible to generate six predictive models using logistic regression, showing sensitivity ranging from 90.1 to 99.0% and specificity ranging from 53.0 to 97.2%. Based on the variables splenomegaly, leukopenia, cough, age and weight loss and on the results of five serological tests six predictive models were generated using CART with sensitivity ranging from 90.1 to 97.2% and specificity ranging from 68.4 to 97.4%. The models composed of clinical-laboratory variables and the rk39 rapid test showed the best performance. Conclusion The predictive models showed to be a potential useful tool to assist healthcare systems and control programs in their strategical choices, contributing to more efficient and more rational allocation of ... |
format |
Article in Journal/Newspaper |
author |
Tália S Machado de Assis Ana Rabello Guilherme L Werneck |
author_facet |
Tália S Machado de Assis Ana Rabello Guilherme L Werneck |
author_sort |
Tália S Machado de Assis |
title |
Predictive models for the diagnostic of human visceral leishmaniasis in Brazil. |
title_short |
Predictive models for the diagnostic of human visceral leishmaniasis in Brazil. |
title_full |
Predictive models for the diagnostic of human visceral leishmaniasis in Brazil. |
title_fullStr |
Predictive models for the diagnostic of human visceral leishmaniasis in Brazil. |
title_full_unstemmed |
Predictive models for the diagnostic of human visceral leishmaniasis in Brazil. |
title_sort |
predictive models for the diagnostic of human visceral leishmaniasis in brazil. |
publisher |
Public Library of Science (PLoS) |
publishDate |
2012 |
url |
https://doi.org/10.1371/journal.pntd.0001542 https://doaj.org/article/ff6f4a54d2c7435da1caff1611c62e5e |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
PLoS Neglected Tropical Diseases, Vol 6, Iss 2, p e1542 (2012) |
op_relation |
https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22389742/pdf/?tool=EBI https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0001542 https://doaj.org/article/ff6f4a54d2c7435da1caff1611c62e5e |
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https://doi.org/10.1371/journal.pntd.0001542 |
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PLoS Neglected Tropical Diseases |
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