Geographical targeting of active case finding for tuberculosis in Pakistan using hotspots identified by artificial intelligence software (SPOT-TB): study protocol for a pragmatic stepped wedge cluster randomised control trial.

IF 3.6 3区 医学 Q1 RESPIRATORY SYSTEM
Syed Mohammad Asad Zaidi, Amna Mahfooz, Abdullah Latif, Nainan Nawaz, Razia Fatima, Fazal Ur Rehman, Tahira Ezra Reza, Faran Emmanuel
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引用次数: 0

Abstract

Introduction: Pakistan has significantly strengthened its capacity for active case finding (ACF) for tuberculosis (TB) that is being implemented at scale in the country. However, yields of ACF have been lower than expected, raising concerns on its effectiveness in the programmatic setting. Distribution of TB in communities is likely to be spatially heterogeneous and targeting of ACF in areas with higher TB prevalence may help improve yields. The primary aim of SPOT-TB is to investigate whether a policy change to use a geographically targeted approach towards ACF supported by an artificial intelligence (AI) software, MATCH-AI, can improve yields in Pakistan.

Methods and analysis: SPOT-TB will use a pragmatic, stepped wedge cluster randomised design. A total of 30 mobile X-ray units and their field teams will be randomised to receive the intervention. Site selection for ACF in the intervention areas will be guided primarily through the use of MATCH-AI software that models subdistrict TB prevalence and identifies potential disease hotspots. Control areas will use existing approaches towards site selection that are based on staff knowledge, experience and analysis of historical data. The primary outcome measure is the difference in bacteriologically confirmed incident TB detected in the intervention relative to control areas. All remaining ACF-related procedures and algorithms will remain unaffected by this trial.

Ethics and dissemination: Ethical approval has been obtained from the Health Services Academy, Islamabad, Pakistan (7-82/IERC-HSA/2022-52) and from the Common Management Unit for TB, HIV and Malaria, Ministry of Health Services, Regulation and Coordination, Islamabad, Pakistan (26-IRB-CMU-2023). Findings from this study will be disseminated through publications in peer-reviewed journals and stakeholder meetings in Pakistan with the implementing partners and public-sector officials. Findings will also be presented at local and international medical and public health conferences.

Trial registration number: NCT06017843.

利用人工智能软件识别的热点地区(SPOT-TB)对巴基斯坦结核病病例进行有针对性的主动发现:实用阶梯式楔形群随机对照试验的研究方案。
导言:巴基斯坦大力加强了结核病(TB)主动病例发现(ACF)的能力,并在全国范围内大规模实施。然而,主动病例发现的收益却低于预期,这引发了人们对其在项目环境中有效性的担忧。结核病在社区中的分布可能具有空间异质性,在结核病发病率较高的地区有针对性地使用 ACF 可能有助于提高产量。SPOT-TB 的主要目的是调查在人工智能(AI)软件 MATCH-AI 的支持下改变政策,采用有地域针对性的 ACF 方法是否能提高巴基斯坦的产量:SPOT-TB 将采用实用的阶梯楔形群组随机设计。共有 30 个移动 X 光室及其现场团队将随机接受干预。在干预地区,ACF 的选址将主要通过使用 MATCH-AI 软件来指导,该软件可模拟分区结核病流行情况并确定潜在的疾病热点。对照地区将使用基于工作人员知识、经验和历史数据分析的现有选址方法。主要结果衡量指标是干预区与对照区经细菌学确诊的结核病发病率的差异。所有其他与 ACF 相关的程序和算法将不受此次试验的影响:已获得巴基斯坦伊斯兰堡卫生服务学院(7-82/IERC-HSA/2022-52)和巴基斯坦伊斯兰堡卫生服务、监管和协调部结核病、艾滋病和疟疾共同管理股(26-IRB-CMU-2023)的伦理批准。将通过在同行评审期刊上发表文章以及在巴基斯坦与执行伙伴和公共部门官员举行利益攸关方会议来传播本研究的结果。研究结果还将在当地和国际医学及公共卫生会议上公布:试验注册号:NCT06017843。
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来源期刊
BMJ Open Respiratory Research
BMJ Open Respiratory Research RESPIRATORY SYSTEM-
CiteScore
6.60
自引率
2.40%
发文量
95
审稿时长
12 weeks
期刊介绍: BMJ Open Respiratory Research is a peer-reviewed, open access journal publishing respiratory and critical care medicine. It is the sister journal to Thorax and co-owned by the British Thoracic Society and BMJ. The journal focuses on robustness of methodology and scientific rigour with less emphasis on novelty or perceived impact. BMJ Open Respiratory Research operates a rapid review process, with continuous publication online, ensuring timely, up-to-date research is available worldwide. The journal publishes review articles and all research study types: Basic science including laboratory based experiments and animal models, Pilot studies or proof of concept, Observational studies, Study protocols, Registries, Clinical trials from phase I to multicentre randomised clinical trials, Systematic reviews and meta-analyses.
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