Lessons learnt from assessing and improving accuracy and positive predictive value of the national HIV testing algorithm in Nigeria.

IF 1 Q4 MEDICINE, RESEARCH & EXPERIMENTAL African Journal of Laboratory Medicine Pub Date : 2024-08-28 eCollection Date: 2024-01-01 DOI:10.4102/ajlm.v13i1.2339
Augustine O Mpamugo, Nnaemeka C Iriemenam, Adebobola Bashorun, Olumide O Okunoye, Orji O Bassey, Edewede Onokevbagbe, Tapdiyel Jelpe, Matthias A Alagi, Chidozie Meribe, Rose E Aguolu, Charles E Nzelu, Segun Bello, Babatunde Ezra, Christine A Obioha, Baffa S Ibrahim, Oluwasanmi Adedokun, Akudo Ikpeazu, Chikwe Ihekweazu, Talishiea Croxton, Sylvia B Adebajo, McPaul I J Okoye, Alash'le Abimiku
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Abstract

Background: HIV testing remains an entry point into HIV care and treatment services. In 2007, Nigeria adopted and implemented a two-test rapid HIV testing algorithm of three HIV rapid test kits, following the sequence: Alere Determine (first test), UnigoldTM (second test), and STAT-PAK® as the tie-breaker. Sub-analysis of the 2018 Nigeria HIV/AIDS Indicator and Impact Survey data showed significant discordance between the first and second tests, necessitating an evaluation of the algorithm. This manuscript highlights lessons learnt from that evaluation.

Intervention: A two-phased evaluation method was employed, including abstraction and analysis of retrospective HIV testing data from January 2017 to December 2019 from 24 selected sites supported by the United States President's Emergency Plan for AIDS Relief programme. A prospective evaluation of HIV testing was done among 2895 consecutively enrolled and consented adults, aged 15-64 years, accessing HIV testing services from three selected sites per state across the six geopolitical zones of Nigeria between July 2020 and September 2020. The prospective evaluation was performed both in the field and at the National Reference Laboratory under controlled laboratory conditions. Stakeholder engagements, strategic selection and training of study personnel, and integrated supportive supervision were employed to assure the quality of evaluation procedures and outcomes.

Lessons learnt: The algorithm showed higher sensitivity and specificity in the National Reference Laboratory compared with the field. The approaches to quality assurance were integral to the high-quality study outcomes.

Recommendations: We recommend comparison of testing algorithms under evaluation against a gold standard.

What this study adds: This study provides context-specific considerations in using World Health Organization recommendations to evaluate the Nigerian national HIV rapid testing algorithm.

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从评估和提高尼日利亚国家艾滋病毒检测算法的准确性和阳性预测值中汲取的经验教训。
背景:艾滋病毒检测仍然是艾滋病毒护理和治疗服务的切入点。2007 年,尼日利亚通过并实施了一种由三种艾滋病毒快速检测试剂盒组成的两测艾滋病毒快速检测算法,其顺序为:Alere Determine(第一测)、UnigoldTM(第二测)和 STAT-PAK®:Alere Determine(第一次检测)、UnigoldTM(第二次检测)和STAT-PAK®作为平局者。对 2018 年尼日利亚艾滋病毒/艾滋病指标和影响调查数据的子分析表明,第一次和第二次检测之间存在明显的不一致,因此有必要对该算法进行评估。本手稿重点介绍了从评估中汲取的经验教训:采用了两阶段评估方法,包括从美国总统艾滋病紧急救援计划支持的 24 个选定地点抽取和分析 2017 年 1 月至 2019 年 12 月的回顾性 HIV 检测数据。2020 年 7 月至 2020 年 9 月期间,在尼日利亚 6 个地缘政治区内每个州的 3 个选定地点,对 2895 名连续登记并同意接受艾滋病毒检测服务的 15-64 岁成年人进行了艾滋病毒检测前瞻性评估。前瞻性评估在实地和国家参考实验室的受控实验室条件下进行。为确保评估程序和结果的质量,还采用了利益相关者参与、战略性选择和培训研究人员以及综合支持性监督等方法:与现场相比,国家参考实验室的算法显示出更高的灵敏度和特异性。质量保证方法是高质量研究成果不可或缺的一部分:建议:我们建议将评估中的检测算法与黄金标准进行比较:这项研究提供了在使用世界卫生组织的建议评估尼日利亚国家 HIV 快速检测算法时的具体考虑因素。
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来源期刊
African Journal of Laboratory Medicine
African Journal of Laboratory Medicine MEDICINE, RESEARCH & EXPERIMENTAL-
CiteScore
1.70
自引率
9.10%
发文量
53
审稿时长
12 weeks
期刊介绍: The African Journal of Laboratory Medicine, the official journal of ASLM, focuses on the role of the laboratory and its professionals in the clinical and public healthcare sectors,and is specifically based on an African frame of reference. Emphasis is on all aspects that promote and contribute to the laboratory medicine practices of Africa. This includes, amongst others: laboratories, biomedical scientists and clinicians, medical community, public health officials and policy makers, laboratory systems and policies (translation of laboratory knowledge, practices and technologies in clinical care), interfaces of laboratory with medical science, laboratory-based epidemiology, laboratory investigations, evidence-based effectiveness in real world (actual) settings.
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