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Clinical, Bacteriologic, and Geographic Stratification of Melioidosis Emerges from the Sri Lankan National Surveillance Program
Melioidosis, a potentially fatal tropical infection, is said to be underdiagnosed in low-income countries. An increase in melioidosis cases in Sri Lanka allowed us to analyze the relationship among clinical outcome, bacteriology, epidemiology, and geography in the first 108 laboratory-confirmed case...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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The American Society of Tropical Medicine and Hygiene
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5929190/ https://www.ncbi.nlm.nih.gov/pubmed/29313474 http://dx.doi.org/10.4269/ajtmh.17-0441 |
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author | Sathkumara, Harindra D. Merritt, Adam J. Corea, Enoka M. Krishnananthasivam, Shivankari Natesan, Mohan Inglis, Timothy J. J. De Silva, Aruna Dharshan |
author_facet | Sathkumara, Harindra D. Merritt, Adam J. Corea, Enoka M. Krishnananthasivam, Shivankari Natesan, Mohan Inglis, Timothy J. J. De Silva, Aruna Dharshan |
author_sort | Sathkumara, Harindra D. |
collection | PubMed |
description | Melioidosis, a potentially fatal tropical infection, is said to be underdiagnosed in low-income countries. An increase in melioidosis cases in Sri Lanka allowed us to analyze the relationship among clinical outcome, bacteriology, epidemiology, and geography in the first 108 laboratory-confirmed cases of melioidosis from a nationwide surveillance program. The additional 76 cases of laboratory-confirmed melioidosis confirmed further associations between Burkholderia pseudomallei multilocus sequence typing (MLST) and infection phenotype; ST1137/unifocal bacteremic infection (χ(2) = 3.86, P < 0.05), ST1136/multifocal infection without bacteremia (χ(2) = 15.8, P < 0.001), and ST1132/unifocal nonbacteremic infection (χ(2) = 6.34, P = 0.02). ST1137 infections were predominantly seen in the Western Province, whereas ST1132, 1135, and 1136 infections predominated in the Northwestern Province. Early participating centers in the surveillance program had a lower melioidosis-associated mortality than later participants (χ(2) = 3.99, P < 0.05). The based upon related sequence types (eBURST) algorithm, a MLST clustering method that infers founding genotypes and patterns of descent for related isolates and clonal complexes in an unrooted tree, showed uneven distribution of sequence types (STs). There was spatial clustering of the commonest STs (ST1132, 1136, and 1137) in the Western, Northwestern, and Central provinces. The recent increase in melioidosis in Sri Lanka uncovered by laboratory-enhanced surveillance is likely to be the result of a combination of improved laboratory detection, increased clinician awareness, recruitment of clinical centers, and small outbreaks. Further development of the surveillance program into a national genotyping-supported melioidosis registry will improve melioidosis diagnosis, treatment, and prevention where underdiagnosis and mortality rates remain high. |
format | Online Article Text |
id | pubmed-5929190 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | The American Society of Tropical Medicine and Hygiene |
record_format | MEDLINE/PubMed |
spelling | pubmed-59291902018-05-08 Clinical, Bacteriologic, and Geographic Stratification of Melioidosis Emerges from the Sri Lankan National Surveillance Program Sathkumara, Harindra D. Merritt, Adam J. Corea, Enoka M. Krishnananthasivam, Shivankari Natesan, Mohan Inglis, Timothy J. J. De Silva, Aruna Dharshan Am J Trop Med Hyg Articles Melioidosis, a potentially fatal tropical infection, is said to be underdiagnosed in low-income countries. An increase in melioidosis cases in Sri Lanka allowed us to analyze the relationship among clinical outcome, bacteriology, epidemiology, and geography in the first 108 laboratory-confirmed cases of melioidosis from a nationwide surveillance program. The additional 76 cases of laboratory-confirmed melioidosis confirmed further associations between Burkholderia pseudomallei multilocus sequence typing (MLST) and infection phenotype; ST1137/unifocal bacteremic infection (χ(2) = 3.86, P < 0.05), ST1136/multifocal infection without bacteremia (χ(2) = 15.8, P < 0.001), and ST1132/unifocal nonbacteremic infection (χ(2) = 6.34, P = 0.02). ST1137 infections were predominantly seen in the Western Province, whereas ST1132, 1135, and 1136 infections predominated in the Northwestern Province. Early participating centers in the surveillance program had a lower melioidosis-associated mortality than later participants (χ(2) = 3.99, P < 0.05). The based upon related sequence types (eBURST) algorithm, a MLST clustering method that infers founding genotypes and patterns of descent for related isolates and clonal complexes in an unrooted tree, showed uneven distribution of sequence types (STs). There was spatial clustering of the commonest STs (ST1132, 1136, and 1137) in the Western, Northwestern, and Central provinces. The recent increase in melioidosis in Sri Lanka uncovered by laboratory-enhanced surveillance is likely to be the result of a combination of improved laboratory detection, increased clinician awareness, recruitment of clinical centers, and small outbreaks. Further development of the surveillance program into a national genotyping-supported melioidosis registry will improve melioidosis diagnosis, treatment, and prevention where underdiagnosis and mortality rates remain high. The American Society of Tropical Medicine and Hygiene 2018-02 2018-01-08 /pmc/articles/PMC5929190/ /pubmed/29313474 http://dx.doi.org/10.4269/ajtmh.17-0441 Text en © The American Society of Tropical Medicine and Hygiene This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Articles Sathkumara, Harindra D. Merritt, Adam J. Corea, Enoka M. Krishnananthasivam, Shivankari Natesan, Mohan Inglis, Timothy J. J. De Silva, Aruna Dharshan Clinical, Bacteriologic, and Geographic Stratification of Melioidosis Emerges from the Sri Lankan National Surveillance Program |
title | Clinical, Bacteriologic, and Geographic Stratification of Melioidosis Emerges from the Sri Lankan National Surveillance Program |
title_full | Clinical, Bacteriologic, and Geographic Stratification of Melioidosis Emerges from the Sri Lankan National Surveillance Program |
title_fullStr | Clinical, Bacteriologic, and Geographic Stratification of Melioidosis Emerges from the Sri Lankan National Surveillance Program |
title_full_unstemmed | Clinical, Bacteriologic, and Geographic Stratification of Melioidosis Emerges from the Sri Lankan National Surveillance Program |
title_short | Clinical, Bacteriologic, and Geographic Stratification of Melioidosis Emerges from the Sri Lankan National Surveillance Program |
title_sort | clinical, bacteriologic, and geographic stratification of melioidosis emerges from the sri lankan national surveillance program |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5929190/ https://www.ncbi.nlm.nih.gov/pubmed/29313474 http://dx.doi.org/10.4269/ajtmh.17-0441 |
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