A simple scoring system to differentiate between relapse and re-infection in patients with recurrent melioidosis

Background Melioidosis is an important cause of morbidity and mortality in East Asia. Recurrent melioidosis occurs in around 10% of patients following treatment either because of relapse with the same strain or re-infection with a new strain of Burkholderia pseudomallei. Distinguishing between the t...

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Main Authors: Limmathurotsakul, D, Chaowagul, W, Chantratita, N, Wuthiekanun, V, Biaklang, M, Tumapa, S, White, N, Day, N, Peacock, S
Format: Journal article
Language:English
Published: Public Library of Science 2008
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author Limmathurotsakul, D
Chaowagul, W
Chantratita, N
Wuthiekanun, V
Biaklang, M
Tumapa, S
White, N
Day, N
Peacock, S
author_facet Limmathurotsakul, D
Chaowagul, W
Chantratita, N
Wuthiekanun, V
Biaklang, M
Tumapa, S
White, N
Day, N
Peacock, S
author_sort Limmathurotsakul, D
collection OXFORD
description Background Melioidosis is an important cause of morbidity and mortality in East Asia. Recurrent melioidosis occurs in around 10% of patients following treatment either because of relapse with the same strain or re-infection with a new strain of Burkholderia pseudomallei. Distinguishing between the two is important but requires bacterial genotyping. The aim of this study was to develop a simple scoring system to distinguish re-infection from relapse. Methods In a prospective study of 2,804 consecutive adult patients with melioidosis presenting to Sappasithiprasong Hospital, NE Thailand, between1986 and 2005, there were 141 patients with recurrent melioidosis with paired strains available for genotyping. Of these, 92 patients had relapse and 49 patients had re-infection. Variables associated with relapse or re-infection were identified by multivariable logistic regression and used to develop a predictive model. Performance of the scoring system was quantified with respect to discrimination (area under receiver operating characteristic curves, AUC) and categorization (graphically). Bootstrap resampling was used to internally validate the predictors and adjust for over-optimism. Findings Duration of oral antimicrobial treatment, interval between the primary episode and recurrence, season, and renal function at recurrence were independent predictors of relapse or re-infection. A score of <5 correctly identified relapse in 76 of 89 patients (85%), whereas a score ≥5 correctly identified re-infection in 36 of 52 patients (69%). The scoring index had good discriminative power, with a bootstrap bias-corrected AUC of 0.80 (95%CI: 0.73–0.87). Conclusions A simple scoring index to predict the cause of recurrent melioidosis has been developed to provide important bedside information where rapid bacterial genotyping is unavailable.
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spelling oxford-uuid:133d2aea-5556-4157-af53-1670ca0ae5a72022-03-26T10:12:45ZA simple scoring system to differentiate between relapse and re-infection in patients with recurrent melioidosisJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:133d2aea-5556-4157-af53-1670ca0ae5a7EnglishSymplectic Elements at OxfordPublic Library of Science2008Limmathurotsakul, DChaowagul, WChantratita, NWuthiekanun, VBiaklang, MTumapa, SWhite, NDay, NPeacock, SBackground Melioidosis is an important cause of morbidity and mortality in East Asia. Recurrent melioidosis occurs in around 10% of patients following treatment either because of relapse with the same strain or re-infection with a new strain of Burkholderia pseudomallei. Distinguishing between the two is important but requires bacterial genotyping. The aim of this study was to develop a simple scoring system to distinguish re-infection from relapse. Methods In a prospective study of 2,804 consecutive adult patients with melioidosis presenting to Sappasithiprasong Hospital, NE Thailand, between1986 and 2005, there were 141 patients with recurrent melioidosis with paired strains available for genotyping. Of these, 92 patients had relapse and 49 patients had re-infection. Variables associated with relapse or re-infection were identified by multivariable logistic regression and used to develop a predictive model. Performance of the scoring system was quantified with respect to discrimination (area under receiver operating characteristic curves, AUC) and categorization (graphically). Bootstrap resampling was used to internally validate the predictors and adjust for over-optimism. Findings Duration of oral antimicrobial treatment, interval between the primary episode and recurrence, season, and renal function at recurrence were independent predictors of relapse or re-infection. A score of <5 correctly identified relapse in 76 of 89 patients (85%), whereas a score ≥5 correctly identified re-infection in 36 of 52 patients (69%). The scoring index had good discriminative power, with a bootstrap bias-corrected AUC of 0.80 (95%CI: 0.73–0.87). Conclusions A simple scoring index to predict the cause of recurrent melioidosis has been developed to provide important bedside information where rapid bacterial genotyping is unavailable.
spellingShingle Limmathurotsakul, D
Chaowagul, W
Chantratita, N
Wuthiekanun, V
Biaklang, M
Tumapa, S
White, N
Day, N
Peacock, S
A simple scoring system to differentiate between relapse and re-infection in patients with recurrent melioidosis
title A simple scoring system to differentiate between relapse and re-infection in patients with recurrent melioidosis
title_full A simple scoring system to differentiate between relapse and re-infection in patients with recurrent melioidosis
title_fullStr A simple scoring system to differentiate between relapse and re-infection in patients with recurrent melioidosis
title_full_unstemmed A simple scoring system to differentiate between relapse and re-infection in patients with recurrent melioidosis
title_short A simple scoring system to differentiate between relapse and re-infection in patients with recurrent melioidosis
title_sort simple scoring system to differentiate between relapse and re infection in patients with recurrent melioidosis
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