School of Life Sciences, Arizona State University, Tempe, AZ, USA.
Institute of Neuroscience and Medicine (INM3), Forschungszentrum Jülich, Jülich, Germany.
Chem Senses. 2021 Jan 1;46. doi: 10.1093/chemse/bjaa081.
In a preregistered, cross-sectional study, we investigated whether olfactory loss is a reliable predictor of COVID-19 using a crowdsourced questionnaire in 23 languages to assess symptoms in individuals self-reporting recent respiratory illness. We quantified changes in chemosensory abilities during the course of the respiratory illness using 0-100 visual analog scales (VAS) for participants reporting a positive (C19+; n = 4148) or negative (C19-; n = 546) COVID-19 laboratory test outcome. Logistic regression models identified univariate and multivariate predictors of COVID-19 status and post-COVID-19 olfactory recovery. Both C19+ and C19- groups exhibited smell loss, but it was significantly larger in C19+ participants (mean ± SD, C19+: -82.5 ± 27.2 points; C19-: -59.8 ± 37.7). Smell loss during illness was the best predictor of COVID-19 in both univariate and multivariate models (ROC AUC = 0.72). Additional variables provide negligible model improvement. VAS ratings of smell loss were more predictive than binary chemosensory yes/no-questions or other cardinal symptoms (e.g., fever). Olfactory recovery within 40 days of respiratory symptom onset was reported for ~50% of participants and was best predicted by time since respiratory symptom onset. We find that quantified smell loss is the best predictor of COVID-19 amongst those with symptoms of respiratory illness. To aid clinicians and contact tracers in identifying individuals with a high likelihood of having COVID-19, we propose a novel 0-10 scale to screen for recent olfactory loss, the ODoR-19. We find that numeric ratings ≤2 indicate high odds of symptomatic COVID-19 (4 < OR < 10). Once independently validated, this tool could be deployed when viral lab tests are impractical or unavailable.
在一项预先注册的横断面研究中,我们使用众包问卷以 23 种语言评估了自我报告近期呼吸道疾病的个体的症状,调查嗅觉丧失是否是 COVID-19 的可靠预测指标。我们使用 0-100 视觉模拟量表(VAS)量化了呼吸道疾病过程中的化学感觉能力变化,对于报告 COVID-19 实验室检测结果阳性(C19+;n=4148)或阴性(C19-;n=546)的参与者。逻辑回归模型确定了 COVID-19 状态和 post-COVID-19 嗅觉恢复的单变量和多变量预测因子。C19+和 C19-组均表现出嗅觉丧失,但 C19+参与者的嗅觉丧失明显更大(平均值±标准差,C19+:-82.5±27.2 分;C19-:-59.8±37.7)。疾病期间的嗅觉丧失是单变量和多变量模型中 COVID-19 的最佳预测因子(ROC AUC=0.72)。其他变量提供了微不足道的模型改进。VAS 评分的嗅觉丧失比二元化学感觉是/否问题或其他基数症状(例如发烧)更具预测性。约 50%的参与者在呼吸道症状发作后 40 天内报告嗅觉恢复,嗅觉恢复最佳预测因素是呼吸道症状发作后的时间。我们发现,定量嗅觉丧失是那些有呼吸道疾病症状的人中 COVID-19 的最佳预测因子。为了帮助临床医生和接触者识别极有可能患有 COVID-19 的个体,我们提出了一种新的 0-10 量表来筛查近期嗅觉丧失,即 ODoR-19。我们发现,数字评分≤2 表示 COVID-19 症状的高可能性(4<OR<10)。一旦独立验证,在病毒实验室检测不切实际或不可用时,该工具可以部署。