Quantitative assessment of olfactory dysfunction accurately detects asymptomatic COVID-19 carriers

Abstract

Background: COVID-19 threatens the global community because a large fraction of infected people are asymptomatic, yet can effectively transmit SARS-CoV-2. Finding and isolating these silent carriers is a crucial step in confining the spread of the disease. A sudden loss of the sense of smell has been self-reported by COVID-19 patients across different countries, consistent with expression of the molecular factors mediating SARS-CoV-2 uptake into human olfactory epithelial supporting cells. However, precise quantification of olfactory loss in asymptomatic COVID-19 carriers is missing to date.

Methods: To quantify olfactory functions in asymptomatic COVID-19 patients, we designed an olfactory-action meter that determines detectability indices at different odor concentrations and an olfactory matching accuracy score using monomolecular odors. The optimization of test parameters allowed us to reliably and accurately assess olfactory deficits in a patient within 20 minutes.

Findings: Measurement of detection indices at low concentrations revealed a 50% reduction in asymptomatic COVID-19 carriers. Further, patients with better detection scores showed significantly reduced olfactory matching accuracies compared to normal healthy subjects. Our quantification of olfactory loss, considering all parameters, identified 82% of the asymptomatic SARS-CoV-2 carriers with olfactory deficits. However, on subjective evaluation, only 15% of the patients noticed a compromised ability to smell.

Interpretation: Compromised olfactory fitness can serve as a strong basis for identifying asymptomatic COVID-19 patients. Detailed design specifications and protocols provided here should enable the development of a sensitive, fast, and economical screening strategy that can be administered to large populations to prevent the rapid spread of COVID-19.

Funding: This work was supported by the DBT - Wellcome Trust India Alliance intermediate grant (IA/I/14/1/501,306 to N.A.) and UGC NET Fellowship (A.B.). All the funding sources played no roles in the study.

Fig. 1

Optimization of olfactory function testing parameters for COVID-19 patients. A. Schematic representation of the olfactory-action meter. To ensure the utmost safety for usage in COVID-19 isolation wards, HEPA-filtered air was pumped in the instrument. The filtered air was bifurcated into eleven streams (into ten mini mass flow controllers (MFCs) and to the main MFC) using a manifold. The volumetric airflow was controlled using these MFCs by a custom-written software in LabWindows (National Instruments). The output from the main MFC was bifurcated into ten channels, which were controlled by using a battery of solenoid valves (one for each odor channel). The solenoid valves allowed us to have precise control over the clean air delivery timing. During the preloading phase (3.2 s), the air in each channel passes through the odor bottle and is mixed with a stream of clean air before entering in the odor nozzle. A suction (−450 millibar) placed outside the exit of the nozzle diverts air through a series of three 0.2 µm filters (one Whatman Uniflow and two HEPA filters) into the exhaust (activated carbon filter). The output towards the vacuum was guarded by 0.2 µm PES filter (Whatman Uniflow). To administer the test, suction is switched off and the odorized air travels through the odor delivery unit into the nose of the patients. All subjects are required to wear a surgical mask and the entire odor delivery unit is replaced for each test to avoid cross-contamination. Four layers of filters made from surgical mask grade material are placed along the length of the odor delivery unit to avoid instrument contamination. Further, a separating wall ensures that the patient doesn't come in physical contact with the instrument. 1. Air Pump (5 L/min). 2. 0.2 µm HEPA filter. 3. Air filter. 4. Manifold. 5. Main Mass flow controller (200 uccm). 6. Mini Mass flow controller (for each odor line, 20–200 uccm). 7. Solenoid valves. 8. Odor box containing ten odor bottles. 9. Glass odor nozzle. 10. Filter made from surgical mask material. 11. T joint (Replaceable odor delivery unit consists of 10, 11 and 13). 12. Separating wall. 13. 0.2 µm PES filter (Whatman uniflow). 14. Electromagnetic valve. 15. Vacuum pump (−450 mbar). 16. Carbon filter (60 cm in length). B. Ten odorants of varying physical properties were selected for the olfactory function test. The kinetics of the odor pulses were measured for all 10 odorants using a miniPID (Aurora Scientific). The use of vacuum during the preloading phase guaranteed precise delivery of odors with minimum delay (100 – 200 ms onset time) and allowed us to present subjects with a sharp odor pulse. Depending on the physicochemical properties of each odor, the amplitude and the rise time varied across different odors (PID amplitudes, Two-way ANOVA, F [9,40] = 18.49, p<0.0001). Traces were averaged across five trials. Data is represented as mean±SEM. C. Detection thresholds shown by normal healthy subjects for all ten odorants. Healthy subjects could detect eight out of ten odors at the second-lowest value of 16.6 (% v/v) concentration. For the enantiomer pair of limonene, the detection threshold was found to be 23.1 (% v/v) concentration. The line within the box plot indicates the median detection value for the healthy subjects across different odorants. The whiskers indicate the highest detection thresholds observed in the healthy subjects for different odorants (n = 37 subjects).

Fig. 2

Asymptomatic COVID-19 patients show severely compromised olfactory detection abilities. A. Reduced olfactory detectability in asymptomatic COVID-19 patients for all odorants tested. Detectability index was measured by calculating the fraction of odors the subjects could detect at a given concentration. For all odorants tested, healthy subjects display higher detectability indices than asymptomatic COVID-19 patients. Two-way ANOVA: for Hexanal, F (1, 260) = 20.72, p<0.0001, for Isoamyl acetate, F (1, 265) = 68.21, p<0.0001, for Octanal, F (1, 258) = 52.74, p<0.0001, for 1,4-Cineole, F (1, 257) = 26.2, p<0.0001, for (+)-Limonene, F (1, 258) = 20.62, p<0.0001, for (-)-Limonene, F (1, 260) = 26.84, p<0.0001, for Acetophenone, F (1, 260) = 31.64, p<0.0001, for (-)-Carvone, F (1, 259) = 30.82, p<0.0001, for Ethyl butyrate, F (1, 259) = 45.22, p<0.0001, for Eugenol, F (1, 261) = 28.45, p<0.0001. Data is represented as mean±SEM. B. Quantification of olfactory loss. Shown are the pooled detectability scores for all odorants for healthy subjects and asymptomatic patients (Two-way ANOVA, F (1, 200) = 82.8, p<0.0001). Data is represented as mean±SEM. C. Majority of asymptomatic COVID-19 patients (>80%) show olfactory dysfunctions. Shown are the comparison between median percentage detection scores recorded for healthy subjects and asymptomatic patients at three concentration levels. Asymptomatic patients showed 72%, 81% and 81% reduction in the scores compared to normal healthy subjects. D. Detectability at 50% (v/v) concentration and with a neat dose of pure odorants. On measuring the detectability at 50% (v/v) concentration, we observed that healthy subjects showed an average detection of 96% at 50% (v/v) concentration. However, when measured in the patient cohort, we observed greatly impaired detection of 61%. (Two-tailed t-test, p<0.0001, t = 5.8, df=69). Patients who were unable to detect at 50% (v/v) were then tested with a neat dose of pure odorants. For pure odorants, these patients showed a high detection of 82%. Data is represented as mean±SEM. E. Receiver operating characteristic (ROC) analysis for predicting olfactory dysfunction using detection indices measured for different concentrations of various odorants in asymptomatic COVID-19 patients. ROC analysis shows an AUC of 0.86, specificity of 0.81 and sensitivity of 0.81 for prediction based on detection indices measured from healthy subjects and asymptomatic COVID-19 patients. Values for Area Under Curve (AUC), Sensitivity (SE), Specificity (SP), Positive Predictive Value (PPV), Negative Predictive Value (NPV) are shown in the figure. 95% confidence interval bound is marked by the gray shaded area.

Fig. 3

Reduced olfactory matching accuracies shown by asymptomatic COVID-19 patients. A. Precise odor delivery in an olfactory matching paradigm. For odor matching measurements, odor pairs were selected from the pool of detected odorants for each patient. One odor pair had a difference in the voltage amplitudes (Hexanal vs. Acetophenone) while the other odor pair had similar voltage amplitudes (Isoamyl acetate vs. 1,4-Cineole). For the olfactory matching paradigm, the odor delivery was for 4 s with an Inter-stimulus interval (ISI) of 5 s. For “same” odorant trials, an ISI of 5 s was sufficient to saturate the vapor phase in the odor bottles and the voltage amplitude of the second odorant matched with the first odorant. Representative traces of “same” and “different” trials are averaged over 4–5 trials and illustrated. Data is represented as mean±SEM. B. Normalized odor matching accuracies. The odor matching accuracies were normalized to the mean accuracy shown by normal healthy subjects. COVID-19 patients showed significantly reduced odor matching accuracies compared to the normal healthy subjects (Two-tailed t-test, p = 0.015, t = 2.5, df=54). Data is represented as mean±SEM.

Fig. 4

Quantification of olfaction identifies asymptomatic COVID-19 carriers. A. Asymptomatic COVID-19 patient population with olfactory deficits. To quantify the percentage patient population with olfactory deficits, we compared their detectability indices at 9.1%, 16.6% 23.1% and 50% (v/v) concentrations and the normalized matching accuracies with that of shown by normal healthy subjects. If patients showed deficiency in detectability indices for all four concentrations tested or showed deficiency in detectability indices for two or more out of the four concentrations as well as in olfactory matching accuracy, they were classified as “with olfactory deficits”. This criterion resulted in 82% of the asymptomatic patients with olfactory dysfunctions. B. Majority of the healthy subjects are without any olfactory deficits. The criterion set to classify subjects with or without olfactory deficits was applied to the normal healthy subject cohort. Even with strict criteria set, 87% of the healthy subject population did not show any olfactory deficits. C. Olfactory function scores reflecting the olfactory loss in COVID-19 patients. To establish a robust readout reflecting olfactory deficits, we calculated their olfactory function score by averaging detectability indices and normalized olfactory matching performance index shown by the individual patient. Asymptomatic COVID-19 patients showed significantly reduced olfactory function scores compared to normal healthy subjects (median for normal subjects=0.8, and median for patients=0.44, Two-tailed unpaired t-test, p<0.0001, t = 6.4, df=68). D. ROC analysis for predicting olfactory deficits based on olfactory function scores measured for healthy subjects and asymptomatic COVID-19 patients. ROC analysis shows an AUC of 0.83, specificity of 92% and sensitivity of 73% for the classifier based on olfactory function scores in detecting subjects with olfactory dysfunctions. Values for AUC, Sensitivity (SE), Specificity (SP), Positive Predictive Value (PPV), Negative Predictive Value (NPV) are shown in the figure. 95% confidence interval bound is marked by the gray shaded area.