A PORTABLE MULTI-MODAL OPTICO-IMPEDANCE SYTEM FOR EARLY WARNING OF PROGRESSION IN STABLE COVID-19 PATIENTS

用于对稳定的 COVID-19 患者病情进展进行早期预警的便携式多模态光阻抗系统

• 批准号: 10188939
• 负责人: Ryan Joseph Halter
• 金额: $ 15.53万
• 依托单位: MULTIVARIATE SYSTEMS, INC.
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2024-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10188939
• 关键词: Accident and Emergency department; Address; Algorithms; Animals; Assisted Living Facilities; Blood Volume; COVID-19; COVID-19 detection; COVID-19 diagnosis; COVID-19 early detection; COVID-19 mortality; COVID-19 patient; Cardiac Output; Cardiovascular system; Chest; Clinic; Clinical; Clinical Trials; Communities; Complex; Computer software; Data; Data Discovery; Data Set; Detection; Deterioration; Development; Device or Instrument Development; Devices; Diagnosis; Diagnostic; Diagnostic tests; Disease; Drops; Equipment and supply inventories; Evaluation; Extravascular Lung Water; Family suidae; Feedback; Fluid Balance; Funding; Goals; Health; Health Personnel; Health care facility; Healthcare; Healthcare Systems; Hemorrhage; Hospitalization; Hospitals; Individual; Instruction; Learning; Legal patent; Long-Term Care; Lower Body Negative Pressure; Lung; Measurement; Medical; Modeling; Monitor; Morbidity - disease rate; Nursing Homes; Optics; Outpatients; Oxygen; Parents; Patient Monitoring; Patient-Focused Outcomes; Patients; Peripheral; Phase; Population; Preparation; Primary Health Care; Prisons; Pulse Oximetry; Resources; Respiratory System; Risk; SARS-CoV-2 infection; Shock; Small Business Technology Transfer Research; Spectrum Analysis; Symptoms; System; Systemic disease; Technology; Time; Water; acute care; algorithm development; cohort; college; commercialization; community living; coronavirus disease; cost; density; electric impedance; electrical impedance tomography; high risk; human study; human subject; improved outcome; light weight; lung volume; mortality; multimodality; non-invasive monitor; pandemic disease; portability; precision medicine; prognostic; programs; prototype; response; scale up; sensor; tissue oxygenation; tomography; transmission process

Project Summary / Abstract: COVID-19, the clinical presentation associated with SARS-CoV-2 infection, has already profoundly impacted healthcare systems globally. Of particular note, communities such as long-term care facilities, assisted living communities, and prisons, are being devastated because of their high density of vulnerable individuals. Nursing home residents, which represent only 0.5% of the US population, account for 25% of COVID-19 deaths. Early detection of COVID-19 progression in these patients is critical to improving outcomes of patients who are in an early stable condition but at risk of deteriorating, but must be balanced with efficient use of primary care resources and adequate protection of healthcare workers. An early alert to progression with a high sensitivity and an acceptable rate of false-negatives would save patient lives, reduce exposure of healthcare workers, and would also facilitate resource-shifting in the face of a surge. The time, money and effort saved by allowing medical resources to be applied more accurately is the essence of precision medicine. During our current STTR efforts, we have developed and evaluated an opto-impedance system capable of integrating and classifying optical, electrical impedance spectroscopy and tomography data to detect change from baseline signatures of early ongoing hemorrhage with high accuracy. This proposal will (1) scale up our hardware inventory, (2) deploy on COVID-positive patients to collect continuous multiplex data and (3) retrain our algorithms using the data to detect associated deterioration due to progression of COVID symptoms. This multivariate approach that has already been demonstrated in other pre-shock models, has the potential to provide critical diagnostic and prognostic feedback in high-risk individuals.

项目概要/摘要： COVID-19是与SARS-CoV-2感染相关的临床表现， 全球医疗保健系统。特别值得注意的是，社区，如长期护理设施，辅助生活， 社区和监狱由于弱势个人的高度密集而遭到破坏。 仅占美国人口0.5%的养老院居民，占COVID-19的25% 死亡早期发现这些患者的COVID-19进展对于改善患者的预后至关重要 处于早期稳定状态但有恶化风险的人，但必须与有效使用 初级保健资源和充分保护保健工作者。早期预警进展， 高灵敏度和可接受的假阴性率将挽救患者的生命， 医疗保健工作者，也将促进资源转移，面对激增。时间，金钱， 节省人力，让医疗资源更精准地运用，才是精准医疗的本质。 在我们目前的STTR工作中，我们开发并评估了一种光阻抗系统， 集成和分类光学、电阻抗谱和断层扫描数据以检测变化 与早期持续出血的基线特征相比具有高准确性。该提案将（1）扩大我们的 硬件库存，（2）部署在COVID阳性患者上以收集连续的多路复用数据，以及（3）重新训练 我们的算法使用数据来检测由于COVID症状进展而导致的相关恶化。这 多变量方法已经在其他冲击前模型中得到证明，有可能 为高风险个体提供关键的诊断和预后反馈。