Longitudinal At Home Smell Testing to Detect Infection by SARS-CoV-2

纵向家庭气味测试检测 SARS-CoV-2 感染

基本信息

批准号：
10321005
负责人：
MARK W ALBERS
金额：
$ 43.66万
依托单位：
MASSACHUSETTS GENERAL HOSPITAL
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-12-21 至 2024-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10321005
关键词：
2019-nCoV Age Algorithms Alzheimer disease detection Anosmia Area Under Curve Argentine Biological Assay COVID diagnosis COVID-19 associated anosmia COVID-19 pandemic COVID-19 patient COVID-19 test Cellular Phone Clinic Clinical Computers Data Development Disease Electronic Health Record Elements Employee Evaluation General Hospitals Health Personnel Health Professional Home Hospitals Individual Infection Influenza International Label Lung diseases Maryland Massachusetts Molecular Molecular Diagnosis Monitor Odors Olfactory dysfunction Online Systems Participant Patient Self-Report Patients Performance Persons PhenX Toolkit Phenotype Pilot Projects Population Population Heterogeneity Predictive Value Probability Prognosis Quarantine Rehabilitation therapy Research Risk Risk Estimate SARS-CoV-2 infection Safety Schools Self Administration Sensitivity and Specificity Signal Transduction Site Smell Perception Students Symptoms Syndrome Tablets Taste Perception Testing Time Universities Update Virus Woman Work algorithm development base coronavirus disease experience infection risk influenza infection innovation new technology respiratory screening smell test social health determinants software development undergraduate student university student vector transmission

项目摘要

Abstract: Self-report of sudden loss of smell or taste substantially increases the odds of being infected with SARS-CoV-2 (10 – 37-fold). However, self-report of smell function is an unreliable predictor of smell loss. Based on our experience developing smell tests with personalized algorithms for asymptomatic detection of Alzheimer's disease, we created a self-administered easy to use “at home” 5-minute objective smell test to uncover alterations in smell function unbeknownst to many individuals, and confer increased risk of infection by SARS- CoV-2. Our new smell test consists of a physical smell card containing peel and sniff odor labels and a web- based application. The disposable smell card reduces the risk that the smell test serves as a vector of transmission to other patients, research staff, and to health care workers. Each participant accesses the web- based app on their own smartphone, tablet, or computer. In our pilot studies, we validated each participant's COVID status by extracting results of clinical SARS-CoV-2 RT PCR assays from electronic health records. The smell test provides better area under the curve for SARS-CoV-2 infection (0.83 – 0.85) in both US and Argentinian symptomatic patients (ages 19 - 87) than symptom tracking alone (0.66). We are expanding the smell test from one smell card with three odors to 6 smell cards, each with 3 different odors (18 odors total). Having six different versions of the smell card will afford longitudinal screening several times per week and provide data to construct personalized thresholds for changes in olfactory function - each person serving as their own control and monitoring for diminishment of their expected performance based on their personal trajectory rather than being based on population norms. Here we propose to develop a native app to conduct longitudinal COVID Smell Test (Aim 1), collect data on asymptomatic health care workers, symptomatic patients, and undergraduates (Aim 2) and develop algorithms for the longitudinal smell test for personalized thresholds, differentiate smell loss from COVID relative to influenza, and assess risk of developing pulmonary disease in COVID infected patients (Aim 3). The Longitudinal COVID Smell Test is accessible, affordable, and readily scalable. Effective screening with the COVID smell test will better inform students and employees if they should not report to school or work, and seek an evaluation by a healthcare professional and molecular testing at an early, often asymptomatic, stage of the disease.

抽象的：自我报告突然失去嗅觉或味觉会大大增加感染 SARS-CoV-2 的几率（10 – 37 倍）然而，根据我们的研究，嗅觉功能的自我报告是不可靠的预测指标。拥有使用个性化算法开发气味测试以无症状检测阿尔茨海默病的经验为了发现疾病，我们创建了一种易于“在家”使用的自我管理的 5 分钟客观气味测试来发现许多人都不知道嗅觉功能的改变，并增加了感染 SARS 的风险我们的新气味测试包括包含果皮和嗅气味标签的物理气味卡和网络- 一次性气味卡降低了气味测试作为媒介的风险。传播给其他患者、研究人员和医护人员。每个参与者都访问网络。在我们的试点研究中，我们验证了每个参与者的应用程序。通过从电子健康记录中提取临床 SARS-CoV-2 RT PCR 检测结果来了解 COVID 状态。气味测试为美国和美国的 SARS-CoV-2 感染提供了更好的曲线下面积 (0.83 – 0.85) 阿根廷有症状的患者（19 - 87 岁）比单独的症状跟踪 (0.66) 更大。气味测试从一张具有三种气味的气味卡到六张气味卡，每张气味卡有3种不同的气味（总共18种气味）。拥有六种不同版本的气味卡可以每周进行几次纵向筛查，并且提供数据来构建嗅觉功能变化的个性化阈值——每个人都充当他们根据自己的个人情况自行控制和监控预期绩效的下降轨迹而不是基于人口规范在这里，我们建议开发一个本机应用程序来进行。纵向新冠气味测试（目标 1），收集无症状医护人员、有症状的数据患者和本科生（目标 2）并开发用于个性化气味纵向测试的算法阈值，区分新冠病毒和流感引起的嗅觉丧失，并评估患上肺结核的风险 COVID 感染患者的疾病（目标 3）。易于扩展，使用新冠病毒气味测试进行有效筛查将更好地为学生和员工提供信息。他们不应到学校或工作单位报到，并寻求医疗保健专业人员和分子的评估在疾病的早期（通常是无症状的）阶段进行检测。