SCENTinel 1.0: Development of a Rapid Test to Screen for Smell Loss

Commercially available smell tests are primarily used in research or in-depth clinical evaluations and are too costly and time-consuming for population surveillance in health emergencies like COVID-19. To address this need, we developed the SCENTinel 1.0 test, which rapidly evaluates 3 olfactory functions: detection, intensity, and identification. We tested whether self-administering the SCENTinel 1.0 test discriminates between individuals with self-reported smell loss and those with average smell ability (normosmic individuals) and provides performance comparable to the validated and standardized NIH Toolbox Odor Identification Test in normosmic individuals. Using Bayesian linear models and prognostic classification algorithms, we compared the SCENTinel 1.0 performance of a group of self-reported anosmic individuals (N = 111, 47 +/- 13 years old, F = 71%) and normosmic individuals (N = 154, 47 +/- 14 years old, F = 74%) as well as individuals reporting other smell disorders (such as hyposmia or parosmia; N = 42, 55 +/- 10 years old, F = 67%). Ninety-four percent of normosmic individuals met our SCENTinel 1.0 accuracy criteria compared with only 10% of anosmic individuals and 64% of individuals with other smell disorders. Overall performance on SCENTinel 1.0 predicted belonging to the normosmic group better than identification or detection alone (vs. anosmic: AUC = 0.95, specificity = 0.94). Odor intensity provided the best single-feature predictor to classify normosmic individuals. Among normosmic individuals, 92% met the accuracy criteria at both SCENTinel 1.0 and the NIH Toolbox Odor Identification Test. SCENTinel 1.0 is a practical test able to discriminate individuals with smell loss and will likely be useful in many clinical situations, including COVID-19 symptom screening.

Automated summary

The SCENTinel 1.0 test, which evaluates three olfactory functions rapidly, demonstrates a high accuracy in discriminating individuals with smell loss. It shows potential for practical clinical applications, including COVID-19 symptom screening.