尼日利亚埃多州、巴耶尔萨州和拉各斯州PEPFAR合作伙伴使用的艾滋病毒风险评估工具的敏感性和特异性

Eale E. Kris, Nwafor S. Uchenna, Carole Metekoua, Mary P. Selvaggio, Ladi-Akinyemi Babatunde O
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引用次数: 0

摘要

导论:尽管艾滋病毒检测是获得艾滋病毒治疗的关键筛查和切入点,但全球艾滋病毒项目因资源有限而紧张,这需要一种实用且具有成本效益的筛查和检测客户策略。筛查工具正变得越来越普遍,因为它们在预测和优先考虑最有可能检测出艾滋病毒阳性的客户方面具有效率和成本效益的优势。方法:本研究评估了PEPFAR合作伙伴在尼日利亚埃多州、巴耶尔萨州和拉各斯州使用的风险评估工具(RAT),以确定该工具识别HIV阳性的敏感性和特异性。评估有目的地选择了20个最便利的卫生设施。惩罚逻辑回归模型也用于确定预测真阳性的具体问题。结果与结论:结果表明,3个州使用的RAT准确性较差,灵敏度仅为54%,这意味着RAT正确识别了54%的HIV感染者,但未能识别46%的HIV感染者。RAT的特异性(77%)表明,它正确地识别出了77%没有感染艾滋病毒的人,但它也错误地识别出了23%没有感染艾滋病毒的人。惩罚逻辑回归模型表明,报告在过去6个月内发生无保护措施性行为的客户占艾滋病毒检测呈阳性的客户的51%。同样,报告有阴道或尿道分泌物的占11%,而结核病诊断或症状占艾滋病毒检测呈阳性的客户的8%。这三个问题对可能呈阳性的客户产生了最高的预测值。
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Sensitivity and Specificity of the HIV Risk Assessment Tool Used by PEPFAR Partners in Edo, Bayelsa and Lagos States, Nigeria
INTRODUCTION: Although HIV testing is a critical screening and entry point for accessing HIV treatment, HIV programs worldwide are strained by limited resources which require a practical and cost-effective strategy for screening and testing clients. Screening tools are becoming increasingly common given their presumed advantage of efficiency and cost-effectiveness in predicting and prioritizing clients who are most at risk of testing HIV positive. METHOD: This study assessed a Risk Assessment Tool (RAT) used by PEPFAR partners in Edo, Bayelsa, and Lagos states of Nigeria to determine the tool’s sensitivity and specificity for identifying HIV positivity. The assessment purposively selected the 20 most convenient health facilities. A penalized logistic regression model was also used to identify specific questions that predict True Positive. RESULT & CONCLUSION: The results indicate that the RAT used in the 3 states had poor accuracy, with a sensitivity of only 54%, meaning the RAT correctly identified 54% of the people who have HIV but failed to identify 46% of people who have HIV. The RAT’s specificity (77%) indicated that it correctly identified 77% of people who do not have HIV, but it also erroneously identified 23% of people as having HIV when they did not. The penalized logistic regression model demonstrated that clients who reported having unprotected sex in the previous 6 months accounted for 51% of those who tested positive to HIV. Likewise, those who reported having vaginal or urethral discharge accounted for 11%, while tuberculosis diagnosis or symptoms accounted for 8% of clients who tested positive to HIV. These three questions yielded the highest predictive values of clients who were likely to test positive.
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