Identifying patients at risk of post-tuberculosis lung disease using novel cough and adherence predictors

使用新型咳嗽和依从性预测因子识别有结核后肺病风险的患者

• 批准号: 10663732
• 负责人: Sophie Huddart
• 金额: $ 17.44万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-20 至 2028-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10663732
• 关键词: Acoustics; Adherence; Aftercare; Area; Characteristics; Chronic Obstructive Pulmonary Disease; Chronic lung disease; Clinical; Cohort Studies; Coughing; Country; Cross-Sectional Studies; Data; Dedications; Disease; Early Intervention; Early identification; Environment; Evolution; Frequencies; Future; Goals; Impairment; International; Intervention; Life Cycle Stages; Lung; Lung diseases; Machine Learning; Measurement; Measures; Mentored Research Scientist Development Award; Mentorship; Methods; Modeling; Monitor; Monitoring for Recurrence; Morbidity - disease rate; Obstruction; Outcome; Outcome Assessment; Outcomes Research; Output; Patient-Focused Outcomes; Patients; Pattern; Persons; Pharmaceutical Preparations; Predisposition; Prospective, cohort study; Proxy; Pulmonary Function Test/Forced Expiratory Volume 1; Pulmonary Tuberculosis; Recurrence; Research; Research Personnel; Resource-limited setting; Resources; Risk; Risk Factors; Schedule; Site; Spirometry; Testing; Training; Treatment Factor; Treatment outcome; Tuberculosis; United States National Institutes of Health; Visit; Work; behavioral adherence; career; career development; coronavirus disease; design; epidemiologic data; experience; feature selection; health related quality of life; improved; improved outcome; medication compliance; mobile application; mortality; multidisciplinary; novel; novel strategies; outcome prediction; pulmonary function; pulmonary symptom; research and development; respiratory; risk stratification; sound; tool; treatment adherence; treatment duration; tuberculosis treatment

PROJECT ABSTRACT There is increasing recognition that post-tuberculosis (TB) lung disease (PTLD) is common and causes significant morbidity and mortality. However, changes in lung impairment are heterogenous with some patients improving and others worsening after completion of TB treatment. Moreover, spirometry – the standard method of assessing lung function – is not routinely available in high TB burden countries. Thus, to prioritize post-TB patients who may benefit from early interventions, there is an urgent need to better facilitate early identification of patients at risk for developing PTLD. The overall objective of this application is to evaluate novel approaches to facilitate early identification of patients most at risk for PTLD. The central hypothesis is that patient on-treatment (adherence behavior) and novel post- treatment (cough frequency and acoustic features) factors will improve risk stratification of PTLD. The central hypothesis will be tested by pursuing three specific aims: 1) characterize the evolution of lung function post-TB and its impact on health-related quality of life, 2) evaluate cough frequency and acoustic features measured by a novel mobile app as a non-invasive, inexpensive proxy for spirometry, and 3) evaluate adherence and cough feature trajectories as novel predictors of PTLD. The results of this work will provide preliminary data for an NIH R01 application evaluating app-based cough measurement as a monitoring tool for rarer but serious post-TB outcomes including COPD, TB recurrence and mortality. Dr. Huddart’s career goal is to become an independent investigator focused on understanding drivers of poor outcomes among TB patients in order to inform interventions to avert TB-related morbidity and mortality. To support her path to independence, the proposed work will be paired with a dedicated, multidisciplinary mentorship team and training in patient-centered outcomes assessment (Aim 1), machine learning (Aim 2), and dynamic outcome modelling (Aim 3). UCSF is an outstanding environment that is committed to junior investigators with extensive resources for research and career development. Thus, the K01 award will provide Dr. Huddart with the critical mentorship, training, resources and experience to become an international leader in TB outcomes research.

项目摘要 人们越来越认识到结核病 (TB) 后肺病 (PTLD) 很常见并导致 显着的发病率和死亡率。然而，一些患者的肺损伤变化是异质的 完成结核病治疗后，情况有所改善，而另一些情况则恶化。此外，肺活量测定法——标准方法 评估肺功能——在结核病高负担国家并不常规可用。因此，优先考虑结核病后 可能从早期干预中受益的患者，迫切需要更好地促进早期识别 有发生 PTLD 风险的患者。 该应用程序的总体目标是评估促进早期识别患者的新方法 PTLD 的风险最大。中心假设是患者的治疗（依从行为）和新的治疗后 治疗（咳嗽频率和声学特征）因素将改善 PTLD 的风险分层。中央 将通过追求三个具体目标来检验假设：1）表征结核病后肺功能的演变 及其对健康相关生活质量的影响，2）评估咳嗽频率和声学特征 一款新颖的移动应用程序，作为肺活量测定的非侵入性、廉价替代品，以及 3) 评估依从性和咳嗽情况 将特征轨迹作为 PTLD 的新预测因子。这项工作的结果将为 NIH 提供初步数据 R01 应用程序评估基于应用程序的咳嗽测量作为罕见但严重的结核病后监测工具 结局包括慢性阻塞性肺病、结核病复发和死亡率。 赫达特博士的职业目标是成为一名独立调查员，专注于了解贫困的驱动因素 结核病患者的结果，以便为避免结核病相关发病率和死亡率的干预措施提供信息。到 为了支持她的独立之路，拟议的工作将与一位专门的、多学科的 指导团队和以患者为中心的结果评估（目标 1）、机器学习（目标 2）和培训 动态结果建模（目标 3）。加州大学旧金山分校 (UCSF) 拥有致力于培养初级人才的卓越环境 拥有广泛研究和职业发展资源的研究人员。因此，K01奖将提供 Huddart 博士拥有重要的指导、培训、资源和经验，能够成为该领域的国际领导者 结核病结果研究。