Self-Rated Smell Ability Enables Highly Specific Predictors of COVID-19 Status: A Case-Control Study in Israel

Abstract

Background: Clinical diagnosis of coronavirus disease 2019 (COVID-19) is essential to the detection and prevention of COVID-19. Sudden onset of loss of taste and smell is a hallmark of COVID-19, and optimal ways for including these symptoms in the screening of patients and distinguishing COVID-19 from other acute viral diseases should be established.

Methods: We performed a case-control study of patients who were polymerase chain reaction-tested for COVID-19 (112 positive and 112 negative participants), recruited during the first wave (March 2020-May 2020) of the COVID-19 pandemic in Israel. Patients reported their symptoms and medical history by phone and rated their olfactory and gustatory abilities before and during their illness on a 1-10 scale.

Results: Changes in smell and taste occurred in 68% (95% CI, 60%-76%) and 72% (95% CI, 64%-80%) of positive patients, with odds ratios of 24 (range, 11-53) and 12 (range, 6-23), respectively. The ability to smell was decreased by 0.5 ± 1.5 in negatives and by 4.5 ± 3.6 in positives. A penalized logistic regression classifier based on 5 symptoms had 66% sensitivity, 97% specificity, and an area under the receiver operating characteristics curve (AUC) of 0.83 on a holdout set. A classifier based on degree of smell change was almost as good, with 66% sensitivity, 97% specificity, and 0.81 AUC. The predictive positive value of this classifier was 0.68, and the negative predictive value was 0.97.

Conclusions: Self-reported quantitative olfactory changes, either alone or combined with other symptoms, provide a specific tool for clinical diagnosis of COVID-19. A simple calculator for prioritizing COVID-19 laboratory testing is presented here.

Keywords: COVID-19; classifier; prediction; smell loss; taste loss.

Graphical abstract

Figure 1.

Flowchart of patient selection for the case–control study. Abbreviations: COVID-19, coronavirus disease 2019; RT-PCR, reverse transcription polymerase chain reaction.

Figure 2.

Smell, taste, and taste modality changes during disease. A, The pie chart presents the prevalence of smell and taste changes in positive and negative patients, occurring together or separately. Numbers indicate the percentage of COVID-19 positives and negatives reporting taste or smell loss (blue and green, respectively), both taste and smell loss (turquoise), or neither (seashell). B, The prevalence of the 4 taste modalities in COVID-19-positive and -negative patients. COVID-19 positives are represented in purple, and COVID-19 negatives are represented in orange. Abbreviation: COVID-19, coronavirus disease 2019.

Figure 3.

Degree of taste, smell, and nose blockage in COVID-19 positives and negatives. A, Histogram showing the change in rating during the illness minus the rating before the illness for taste, smell, and nose blockage. No change is coded 0, and the highest change is 9. COVID-19 positives are represented in purple, and COVID-19 negatives are represented in orange. B, Table of mean ± SD for COVID-19 positives and negatives in general and for those reporting changes of taste or smell. Scores for taste, smell, and nose blockage were evaluated on a 1–10 scale. P values for the difference in the magnitude of change between COVID-19 positives and negatives were calculated using a 2-sided t test. Abbreviation: COVID-19, coronavirus disease 2019.

Figure 4.

Descriptor selection process for classifiers. A, The flowchart depicts the total symptoms selected for the classifiers. Upon limiting the number of descriptors for the classifiers and excluding chemosensory symptoms as described, Classifier 1 was created. Different combinations of symptoms established better classifiers than Classifier 1, with those using quantitative questions exhibiting better performance than those using binary ones. The classifier using “smell” and “taste” as separate descriptors, rather than “smell or taste” as a single joint descriptor, showed better performance. The “basic” + smell only descriptor outperformed the “basic” + taste only descriptor, resulting in Classifier 2. Finally, the smell only descriptor was tested alone without all other “Basic” symptoms, resulting in Classifier 3. B, The graph illustrates ROC curves for the classifiers considered, and the table shows the statistical parameters for the ROC curves. For the quantitative descriptors, the coefficients correspond to a descriptor scaled to the 0–1 range. ^aIncludes all symptoms in question 23, excluding “no symptoms,” coding “other” to “fatigue” and “dizziness,” and grouping eye symptoms. ^bIncludes taste, smell, and nose blockage. Abbreviations: AUC, area under the curve; ROC, receiver operating characteristics.