The “Buruli Score”: Development of a Multivariable Prediction Model for Diagnosis of Mycobacterium ulcerans Infection in Individuals with Ulcerative Skin Lesions, Akonolinga, Cameroon
In most Buruli ulcer (BU) endemic areas, laboratory diagnosis is hard to access and comes at a high cost. Clinicians are in need of new tools to assist them in identifying which patients truly require additional work-up and which can be treated directly. We analyzed the clinical data of all patients...
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Public Library of Science
2016
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| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4821558/ |
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pubmed-48215582016-04-22 The “Buruli Score”: Development of a Multivariable Prediction Model for Diagnosis of Mycobacterium ulcerans Infection in Individuals with Ulcerative Skin Lesions, Akonolinga, Cameroon Mueller, Yolanda K. Bastard, Mathieu Nkemenang, Patrick Comte, Eric Ehounou, Geneviève Eyangoh, Sara Rusch, Barbara Tabah, Earnest Njih Trellu, Laurence Toutous Etard, Jean-Francois Research Article In most Buruli ulcer (BU) endemic areas, laboratory diagnosis is hard to access and comes at a high cost. Clinicians are in need of new tools to assist them in identifying which patients truly require additional work-up and which can be treated directly. We analyzed the clinical data of all patients with ulcerative skin lesions that presented to Akonolinga District Hospital in Cameroon and identified which parameters were associated with BU diagnosis. We attributed a certain number of points to each parameter to build a “Buruli score”. Based on score results, clinicians can be advised either to directly treat BU (score ≥4), to look for another diagnosis (score <0) or to do a PCR test (score between 0 and 3). This algorithm was found to have a good performance. Only one out of four patients still needed an additional laboratory test to be classified between BU and non-BU. However, this score still requires validation in another context before it can be recommended elsewhere. Public Library of Science 2016-04-05 /pmc/articles/PMC4821558/ /pubmed/27045293 http://dx.doi.org/10.1371/journal.pntd.0004593 Text en © 2016 Mueller et al http://creativecommons.org/licenses/by/4.0/ 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. |
| repository_type |
Open Access Journal |
| institution_category |
Foreign Institution |
| institution |
US National Center for Biotechnology Information |
| building |
NCBI PubMed |
| collection |
Online Access |
| language |
English |
| format |
Online |
| author |
Mueller, Yolanda K. Bastard, Mathieu Nkemenang, Patrick Comte, Eric Ehounou, Geneviève Eyangoh, Sara Rusch, Barbara Tabah, Earnest Njih Trellu, Laurence Toutous Etard, Jean-Francois |
| spellingShingle |
Mueller, Yolanda K. Bastard, Mathieu Nkemenang, Patrick Comte, Eric Ehounou, Geneviève Eyangoh, Sara Rusch, Barbara Tabah, Earnest Njih Trellu, Laurence Toutous Etard, Jean-Francois The “Buruli Score”: Development of a Multivariable Prediction Model for Diagnosis of Mycobacterium ulcerans Infection in Individuals with Ulcerative Skin Lesions, Akonolinga, Cameroon |
| author_facet |
Mueller, Yolanda K. Bastard, Mathieu Nkemenang, Patrick Comte, Eric Ehounou, Geneviève Eyangoh, Sara Rusch, Barbara Tabah, Earnest Njih Trellu, Laurence Toutous Etard, Jean-Francois |
| author_sort |
Mueller, Yolanda K. |
| title |
The “Buruli Score”: Development of a Multivariable Prediction Model for Diagnosis of Mycobacterium ulcerans Infection in Individuals with Ulcerative Skin Lesions, Akonolinga, Cameroon |
| title_short |
The “Buruli Score”: Development of a Multivariable Prediction Model for Diagnosis of Mycobacterium ulcerans Infection in Individuals with Ulcerative Skin Lesions, Akonolinga, Cameroon |
| title_full |
The “Buruli Score”: Development of a Multivariable Prediction Model for Diagnosis of Mycobacterium ulcerans Infection in Individuals with Ulcerative Skin Lesions, Akonolinga, Cameroon |
| title_fullStr |
The “Buruli Score”: Development of a Multivariable Prediction Model for Diagnosis of Mycobacterium ulcerans Infection in Individuals with Ulcerative Skin Lesions, Akonolinga, Cameroon |
| title_full_unstemmed |
The “Buruli Score”: Development of a Multivariable Prediction Model for Diagnosis of Mycobacterium ulcerans Infection in Individuals with Ulcerative Skin Lesions, Akonolinga, Cameroon |
| title_sort |
“buruli score”: development of a multivariable prediction model for diagnosis of mycobacterium ulcerans infection in individuals with ulcerative skin lesions, akonolinga, cameroon |
| description |
In most Buruli ulcer (BU) endemic areas, laboratory diagnosis is hard to access and comes at a high cost. Clinicians are in need of new tools to assist them in identifying which patients truly require additional work-up and which can be treated directly. We analyzed the clinical data of all patients with ulcerative skin lesions that presented to Akonolinga District Hospital in Cameroon and identified which parameters were associated with BU diagnosis. We attributed a certain number of points to each parameter to build a “Buruli score”. Based on score results, clinicians can be advised either to directly treat BU (score ≥4), to look for another diagnosis (score <0) or to do a PCR test (score between 0 and 3). This algorithm was found to have a good performance. Only one out of four patients still needed an additional laboratory test to be classified between BU and non-BU. However, this score still requires validation in another context before it can be recommended elsewhere. |
| publisher |
Public Library of Science |
| publishDate |
2016 |
| url |
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4821558/ |
| _version_ |
1613562569455304704 |