The “Buruli Score”: Development of a Multivariable Prediction Model for Diagnosis of Mycobacterium ulcerans Infection in Individuals with Ulcerative Skin Lesions, Akonolinga, Cameroon

Yolanda K Mueller, Mathieu Bastard, Patrick Nkemenang, Eric Comte, Geneviève Ehounou, Sara Eyangoh, Barbara Rusch, Earnest Njih Tabah, Laurence Toutous Trellu and Jean-Francois Etard

PLOS Neglected Tropical Diseases, 2016, vol. 10, issue 4, 1-12

Abstract: Background: Access to laboratory diagnosis can be a challenge for individuals suspected of Buruli Ulcer (BU). Our objective was to develop a clinical score to assist clinicians working in resource-limited settings for BU diagnosis. Methododology/Principal Findings: Between 2011 and 2013, individuals presenting at Akonolinga District Hospital, Cameroon, were enrolled consecutively. Clinical data were collected prospectively. Based on a latent class model using laboratory test results (ZN, PCR, culture), patients were categorized into high, or low BU likelihood. Variables associated with a high BU likelihood in a multivariate logistic model were included in the Buruli score. Score cut-offs were chosen based on calculated predictive values. Of 325 patients with an ulcerative lesion, 51 (15.7%) had a high BU likelihood. The variables identified for the Buruli score were: characteristic smell (+3 points), yellow color (+2), female gender (+2), undermining (+1), green color (+1), lesion hyposensitivity (+1), pain at rest (-1), size >5cm (-1), locoregional adenopathy (-2), age above 20 up to 40 years (-3), or above 40 (-5). This score had AUC of 0.86 (95%CI 0.82–0.89), indicating good discrimination between infected and non-infected individuals. The cut-off to reasonably exclude BU was set at scores

Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pntd00:0004593

DOI: 10.1371/journal.pntd.0004593

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