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

“布鲁利评分”:用于诊断溃疡性皮肤病变患者溃疡分枝杆菌感染的多变量预测模型的建立,喀麦隆阿科诺林加

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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 <0 (NPV 96.5%; 95%CI 93.0-98.6). The treatment threshold was set at a cut-off ≥4 (PPV 69.0%; 95%CI 49.2-84.7). Patients with intermediate BU probability needed to be tested by PCR. CONCLUSIONS/SIGNIFICANCE: We developed a decisional algorithm based on a clinical score assessing BU probability. The Buruli score still requires further validation before it can be recommended for wide use.

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