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SIngle-saMPLE tuberculosis evaluation to facilitate linkage to care: The SIMPLE TB trial

SIngle-saMPLE tuberculosis evaluation to facilitate linkage to care: The SIMPLE TB trial
单样本结核病评估以促进与护理的联系:SIMPLE TB 试验
批准号:
9205264
负责人:
Adithya Cattamanchi
金额:
$64.15万
依托单位国家:
美国
项目类别:
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-01-15 至 2020-12-31

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中文摘要
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英文摘要
 DESCRIPTION (provided by applicant): In high burden countries, many patients with tuberculosis (TB) who present to community health centers are lost to follow-up before TB can be diagnosed or treated, leading to ongoing transmission. A primary reason is that the standard approach of collecting sputum specimens over multiple days for microscopic examination is not only insensitive but also inconvenient and costly for patients. Xpert MTB/RIF (Xpert) is a semi-automated molecular test that identifies 90% of TB cases within 2 hours. Xpert is now recommended as the initial diagnostic test for pulmonary TB but cannot be deployed at community health centers because of cost and infrastructure requirements. To achieve access, utilization and impact on health outcomes, strategies for successful referrals from community health centers to facilities in which Xpert is being deployed are essential. Our overall objective s to assess the effectiveness, implementation and impact of a streamlined, single- sample (SIMPLE) TB diagnostic evaluation strategy. The SIMPLE TB strategy was developed after a theory-informed assessment of provider- and patient-level barriers to TB diagnostic evaluation and through a process of stakeholder engagement. Its components include: 1) Single-sample LED fluorescence microscopy (analysis and reporting of smear results from the initial specimen within two hours); 2) Daily transport of smear-negative sputum samples to Xpert testing sites; 3) SMS-based reporting of Xpert test results to patients and health centers; and 4) Routine feedback of TB evaluation metrics to health center staff. Our central hypothesis is that the SIMPLE TB strategy will increase the number of patients with active TB for whom treatment is initiated. To test this hypothesis, we will conduct a cluster-randomized trial at 20 community health centers in Uganda to determine whether the SIMPLE TB strategy improves TB diagnosis and treatment initiation rates relative to the prevailing standard-of-care (Aim 1). Routine data collected on adults undergoing TB diagnostic evaluation at intervention and control health centers will be used to assess trial outcomes. Concurrently with the clinical trial, we will employ a mixed methods approach to evaluate in detail the process of implementation (Aim 2), focusing on factors that influence the adoption and maintenance of intervention components and faithfulness to our conceptual model. Last, we will perform economic and epidemic modeling to estimate the cost-effectiveness and epidemiological impact (i.e., future TB incidence) of the SIMPLE TB strategy (Aim 3). Relying solely on novel diagnostic technologies without also supporting health system interventions to facilitate their uptake and use is unlikely to result in sustained and meaningful progress in the ongoing fight against TB. The comprehensive research plan will generate the high-quality evidence needed to guide TB policy makers in deciding whether to adopt the SIMPLE TB strategy, and on how best to implement it at other health centers. This research will also lead to a better understanding of the factors and types of interventions associated with successful implementation of novel TB diagnostics in low- income, high TB burden countries.
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PROgression of Tuberculosis infECTion in young children living with and without HIV: the PROTECT study
  • 批准号:
    10641389
  • 项目类别:
  • 资助金额:
    $110.55万
  • 财政年份:
    2023
  • 负责人:
    Adithya Cattamanchi
  • 依托单位:
Partnerships for Research in Implementation Science for Equity in Heart and Lung diseases training program (PRISE-HL T32)
Rapid Research for Diagnostics Development in TB Network (R2D2 TB Network)
Rapid Research for Diagnostics Development in TB Network (R2D2 TB Network)
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