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. 2020 Nov 1;361(2):216–225. doi: 10.1016/j.amjms.2020.09.017

The Association of “Loss of Smell” to COVID-19: A Systematic Review and Meta-Analysis

Muhammad Aziz 1, Hemant Goyal 2,, Hossein Haghbin 1, Wade M Lee-Smith 3, Mahesh Gajendran 4, Abhilash Perisetti 5
PMCID: PMC7604015  PMID: 33349441

Abstract

Background

The presence of olfactory dysfunction or “loss of smell” has been reported as an atypical symptom in patients with coronavirus disease 2019 (COVID-19). We performed a systematic review and meta-analysis of the available literature to evaluate the prevalence of “loss of smell” in COVID-19 as well as its utility for prognosticating the disease severity.

Methods

An exhaustive search of the PubMed/Medline, Embase, Web of Science, Cochrane Library, LitCovid NIH, and WHO COVID-19 database was conducted through August 6th, 2020. All studies reporting the prevalence of “loss of smell” (anosmia and/or hyposmia/microsmia) in laboratory-confirmed COVID-19 patients were included. Pooled prevalence for cases (positive COVID-19 through reverse transcriptase (RT-PCR) and/or serology IgG/IgM) and controls (negative RT-PCR and/or serology) was compared, and the odds ratio (OR), 95% confidence interval (CI) and the p-value were calculated. A p-value of <0.05 was considered statistically significant.

Results

A total of 51 studies with 11074 confirmed COVID-19 patients were included. Of these, 21 studies used a control group with 3425 patients. The symptom of “loss of smell” (OR: 14.7, CI: 8.9–24.3) was significantly higher in the COVID-19 group when compared to the control group. Seven studies comparing severe COVID-19 patients with- and without “loss of smell” demonstrated favorable prognosis for patients with “loss of smell” (OR: 0.36, CI 0.27–0.48).

Conclusions

Olfactory dysfunction or “loss of smell” is a prevalent symptom in COVID-19 patients. Moreover, COVID-19 patients with “loss of smell” appear to have a milder course of the disease.

Keywords: COVID-19, Olfactory dysfunction, Loss of smell, SARS-CoV-2, Coronavirus

Introduction

The pandemic coronavirus disease-2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2).1 The pandemic has resulted in significant economic and healthcare burden. Along with the pulmonary symptoms, the disease is also associated with neurological manifestations such as headache, impaired consciousness, altered gait/ataxia, seizures, diarrhea, nausea/vomiting, loss of smell, and altered taste/dysgeusia.2, 3, 4 The disease severity is associated with laboratory abnormalities such as low albumin, elevated interleukin 6, increased alanine/aspartate aminotransferase, increased total bilirubin, increased procalcitonin, increased C-reactive protein (CRP), etc.4, 5, 6, 7, 8

The “loss of smell” is an atypical symptom of COVID-19 and has been reported with varying prevalence in literature. Further, it has been observed that loss of smell is usually associated with milder form of disease compared to severe disease.2 We performed a systematic review and meta-analysis of available studies to evaluate the prevalence of “loss of smell” in COVID-19 and its utility as a prognostic indicator.

Methods

Search Strategy

A systematic search of the PubMed/Medline, Embase, Web of Science, Cochrane Library, LitCovid NIH, and WHO COVID-19 databases through August 6th, 2020, was conducted. The author (W.L.S.) created the initial search strategy using the vocabulary for “COVID-19” and “smell,” which was cross-checked by another reviewer (M.A.). We highlight an example search strategy using EMBASE in Supplementary table 1. Two independent reviewers (M.A. and H.H.) performed the initial screening and data extraction from the articles. Any discrepancy in article screening or data extraction was resolved through mutual discussion.

Inclusion and exclusion criteria

Only articles reporting the laboratory confirmed COVID-19 patients and “loss of smell” were included. Articles were excluded if they had <10 cases of interest. Articles with suspected cases of COVID-19 without a definitive laboratory diagnosis were also excluded. An adherence to “Preferred Reporting Items for Systematic Reviews and Meta-Analyses” (PRISMA) guidelines was observed.

Study Definition

Severe disease is defined as the presence of either respiratory distress (i.e., rate >30/min, PaO2/FiO2 <300, and/or SpO2 <93%), need for hospitalization, and/or death. Given the heterogeneity in defining the “loss of smell” across studies, we included the concepts of “anosmia (complete loss of smell)” and “hyposmia/microsmia (diminished or partial loss of smell)” collectively as “loss of smell”. Positive COVID-19 cases are defined as patients with laboratory confirmed COVID-19 (through reverse transcriptase polymerase chain reaction (RT-PCR) and/or serological evidence of COVID-19 through IgG/IgM). Controls are defined as patients with negative RT-PCR and/or serological testing.

Statistical measures and synthesis of results

The pooled prevalence of cases (COVID-19) and controls (non-COVID-19) were compared using the DerSimonian-Laird/Random-effect meta-analysis, and outcomes were reported using forest plots, proportions with 95% confidence interval (CI), odds ratio (OR) with 95% CI, p-value (<0.05 was considered statistically significant) and I2 heterogeneity (>50% considered substantial heterogeneity).9, 10, 11 Meta-analysis was conducted using comprehensive meta-analysis (BioStat, Englewood, New Jersey, USA) and Open Meta Analyst (CEBM, University of Oxford, Oxford, United Kingdom).

Risk of bias

Publication bias was assessed using a funnel plot and Egger's regression analysis. If significant publication bias was suspected, we utilized the “trim-and-fill” method and Fail-Safe N test. The presence of bias in the individual study was assessed using the Quality in Prognostic Studies (QUIPS) tool.12

Results

A total of 51 studies were included based on the search strategy mentioned previously (Fig. 1 ). Publication bias based on prevalence for “loss of smell” was noted based on visual assessment of the funnel plot and Egger's regression analysis (p = 0.01). We then used the “trim-and-fill” method to create adjusted funnel plot that did not significantly differ from the original funnel plot (Supplementary Fig. 1). The Fail-Safe N test was 504 with an alpha of 0.05. This signifies that 504 studies with effect size zero will be needed to nullify the effect noted for the current analysis. Using the QUIPS tool, only seven studies were considered low risk. The other remaining studies either did not account for confounders in their statistical analyses or outcome/prognostic factors were not adequately assessed (Table 1 ).

Figure 1.

Fig 1:

PRISMA flow diagram.

Table 1.

The Quality in Prognostic Studies (QUIPS) table for risk of bias

Study, year Participation (The study sample represents population of interest on key characteristics?) Attrition (The proportion of study sample providing outcome data is adequate?) Prognostic factor measurement (Prognostic factor is adequately measured in study subjects?) Outcome measurement (The outcome of interest is adequately measured in study subjects?) Study confounders (Potential confounders are accounted for?) Statistical analysis? (Statistical analysis appropriately designed for the study?)
Abalo-Lojo Yes Yes No Partly No No
Aggrawal Yes Partly No Partly No Yes
Altin Yes Yes Yes Yes No Yes
Beltran-Corbellini Yes Yes Yes Yes Yes Yes
Brandstetter Yes Yes Yes Yes No Yes
Carigan Yes Yes Yes Yes Yes Yes
Chiesa-Estomba Yes Yes No Yes No No
Chiesa-Estomba 2 Yes No No Yes No Yes
D'Ascanio Yes Yes Yes Partly Partly Yes
Dawson Yes Yes Yes Yes No Yes
Dell'Era Yes Yes No Yes Yes Yes
Giacomelli Yes Yes No Yes No No
Gorzkowski Yes Yes No Partly No Yes
Guner Yes Yes No Partly No Yes
Haehner Yes Partly Yes Yes No No
Hintschich Yes Partly Yes Yes No Yes
Hornus Yes Yes Yes Partly No No
Izquierdo-Domínguez Yes Yes Yes Yes Yes Yes
Jalessi Yes Yes No Yes Yes Yes
Kai Chua Yes Yes Yes Yes No No
Kempker Yes Partly Yes Yes No No
Kim Yes Partly No Partly No No
Klopfenstein Yes Yes No Partly No Partly
Lechien (1) Yes Yes No Partly Yes Partly
Lechien (2) Yes Yes Partly Partly Yes Yes
Lechien (3) Yes Yes No Partly Yes Yes
Lechien (4) Yes Yes No Partly Partly Partly
Lee Yes No Yes Yes Yes Yes
Liang Yes Yes No Partly No Yes
Magnavita Yes Yes Yes Yes No Yes
Mao Yes Yes No Partly Partly Partly
Martin-Sanz Yes Yes Yes Yes No Yes
Mishra Yes Yes No Partly No No
Moein Yes Yes Yes Yes Yes Partly
Noh Yes Yes No Partly No Yes
Paderno (1) Yes No No Partly Yes Yes
Paderno (2) Yes Yes No Partly Yes Yes
Parente-Arias Yes Yes No Partly No Yes
Patel Yes No No Partly Partly No
Petrocelli Yes No No Partly No Yes
Qiu Yes Yes No Partly Partly Yes
Romero-Sanchez Yes Yes No Partly Yes No
Sakalli Yes Yes No Partly Yes Yes
Sayin Yes Partly Yes Yes Yes Yes
Tostmann Yes Yes Yes Yes Partly Partly
Tsivgoulis Yes Partly Yes Yes Yes No
Vaira (1) Yes Yes No Partly No Partly
Vaira (2) Yes Yes No Partly No Yes
Yan (1) Yes Yes Yes Yes Yes Yes
Yan (2) Yes Yes No Partly Yes Yes
Zayet Yes Yes Yes Yes Yes Yes

A total of 11074 COVID-19 patients (mean age 46.7 ± 10.4 years and males 46.9%) were included in the final analysis (Table 2).2 , 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62 The overall prevalence of “loss of smell” in COVID-19 patients was 52.0% (CI: 42.5%-61.6%, I2 = 99.4%) (Fig. 2 ). A total of 21 studies compared these symptoms in COVID-19 patients (n = 2196) and controls (n = 3425). 13 , 14 , 18 , 19 , 21 , 25 , 27 , 28 , 34, 35, 36, 37 , 39 , 40 , 45 , 47, 48, 49 , 59 , 60 , 62 “Loss of smell” was associated significantly more in the COVID-19 group compared to non-COVID-19 group (OR: 14.7, CI: 8.9–24.3, p < 0.001, I2 =  83.2%) (Fig. 3 ). Among COVID-19 patients, the odds of patients with severe disease and “loss of smell” were significantly lower when compared to patients with severe disease and without “loss of smell” (OR: 0.36, CI 0.27–0.48, p < 0.01, I2 = 27.4% (Fig. 4 ).2 , 21 , 32 , 37 , 52 , 54 , 57

Table 2.

Study characteristics, baseline demographics and prevalence of “loss of smell” in COVID and control group (N: No. of patients)

Study, year Country Center (single, dual, multi) Study Period Type of study Total Patients, non COVID group, N Total Patients, COVID group, N Mean age, COVID group (years) Male gender, COVID group (%) “Loss of smell” in COVID group, N (%) “Loss of smell” in non COVID group, N (%)
Abalo-Lojo, 2020 Spain Single Cohort 131 50.4 56 (42.6%) 77 (58.8%)
Aggrawal, 2020 USA Single Mar 1-Apr 4 Cohort 16 65.5 12 (75.0%) 3 (18.8%)
Altin, 2020 Turkey Dual Mar 25-Apr 20 Cohort 40 81 54.2 50 (61.7%) 0 (0%)
Beltran-Corbellini, 2020 Spain Dual Mar 23-Mar 25 Case-control 40 79 48 (60.8%) 25 (31.6%) 4 (10.0%)
Brandstetter, 2020 Germany Single Cohort 170 31 30 (14.9%) 16 (51.6%) 4 (2.4%)
Carigan, 2020 Canada Single Mar 10- Mar 23 Case-control 134 134 57.1 69 (51.5%) 6 (4.5%)
Chiesa-Estomba (1), 2020 South America (multiple countries) Multi Cross-sectional 542 34 218 (40.2%) 444 (819%)
Chiesa-Estomba (2), 2020 Europe (multiple countries) Multi Cohort 1231 41 970 (78.8%)
D'Ascanio, 2020 Italy Single Febr 1-Apr 24 Case-control 25 43 58.1 26 (60.5%)
Dawson, 2020 USA Single Mar-Apr Cohort 48 42 48 (53.3%) 18 (42.9%) 1 (2.1%)
Dell'Era, 2020 Italy Single Mar 10- Mar 30 Cross-sectional 355 50 192 (54.1%) 237 (66.8%)
Giacomelli, 2020 Italy Single Cross-sectional 59 60 40 (67.8%) 14 (23.7%)
Gorzkowski, 2020 France Single Mar 1- Mar 31 Cross-sectional 229 39.7 82 (35.8%) 140 (61.1%)
Guner, 2020 Turkey Single Mar 10-Apr 10 Cohort 222 50.6 132 (59.5%) 19 (8.6%)
Haehner, 2020 Germany Single Cross-sectional 466 34 15 (44.1%) 21 (61.7%) 47 (10.1%)
Hintschich, 2020 Germany Single Cohort 30 41 37 13 (31.7%) 22 (53.7%) 8 (26.7%)
Hornus, 2020 Germany Single Cross-sectional 45 45 56 38 (84.4%) 12 (26.7%)
Izquierdo-Domínguez, 2020 Spain Multi Mar 21-Apr 18 Cross-sectional 143 846 56.8 454 (53.6%) 43 (30.1%)
Jalessi, 2020 Iran Single Feb-Mar Cohort 92 52.9 62 (67.4%) 22 (23.9%)
Kai Chua, 2020 Singapore Single Mar 23-Apr 4 Cohort 686 31 7 (22.6%) 22 (3.2%)
Kempker, 2020 USA Single Cohort 232 51 10 (19.6%) 48 (94.1%) 27 (11.6%)
Kim, 2020 Korea Single Mar 12-16 Cross-sectional 172 26 66 (38.4%) 68 (39.5%)
Klopfenstein, 2020 France Single March 1-Mar 17 Cohort 114 54 (47.4%)
Lechien (1), 2020 18 European hospitals Multi Cross-sectional 417 357 (85.6%)
Lechien (2), 2020 Belgium Single Cross-sectional 86 41.7 30 (34.9) 53 (61.6%)
Lechien (3), 2020 12 European hospitals Multi Mar 22-Apr 10 Cross-sectional 1420 39.2 997 (70.2%)
Lechien (4), 2020 Belgium Single Mar 20-Apr 16 Cross-sectional 47 58.8 22 (46.8%) 13 (27.6%)
Lee, 2020 Canada Single Mar 16-Apr 15 Cross-sectional 71 56 38 23 (41.1%) 31 (55.4%) 3 (4.2%)
Liang, 2020 China Single Mar 16-Apr 12 Cohort 86 25.5 44 (51.2%) 34 (39.5%)
Magnavita, 2020 Italy Multi Mar 27-Apr 30 Cross-sectional 513 82 35 (42.7%) 4 (0.8%)
Mao, 2020 China Multi Jan 16 -Feb 19 Cohort 214 11 (5.1%)
Martin-Sanz, 2020 Spain Single Mar 1-Apr7 Case-control 140 215 44 (20.5%) 138 (64.1%) 30 (24.8%)
Mishra, 2020 India Single Cross-sectional 74 74 43 (58.1%) 11 (14.8%) 1 (1.4%)
Moein, 2020 Iran Single March 21 - Apr 5 Case-control 60 60 46.6 40 (66.7%) 59 (98.3%) 11 (18.3%)
Noh, 2020 Korea Single NR Cohort 199 38 69 (34.7%) 52 (26.1%)
Paderno (1), 2020 Italy Single Mar 27-Apr 1 Cohort 151 45 56 (37.1%) 126 (83.4%)
Paderno (2), 2020 Italy Single Mar 27-Apr 1 Cross-sectional 508 55 284 (55.9%) 283 (55.7%)
Parente-Arias, 2020 Spain Single Mar 3-Mar 24 Cohort 151 53 (35.1%) 75 (49.7%)
Patel, 2020 UK Single Mar 1-Apr 1 Cross-sectional 141 45.6 83 (58.8%) 80 (56.7%)
Petrocelli, 2020 Italy Single Apr 16-May 2 Cohort 300 43.6 75 (25.0%) 184 (61.3%)
Qiu, 2020 China, France, Germany Multi Mar 15-Apr 5 Cohort 394 154 (40.9%)
Romero-Sanchez, 2020 Spain Dual Mar 1-Apr 1 Cohort 841 66.4 473 (56.2%) 41 (64.1%)
Sakalli, 2020 Turkey Single Cross-sectional 172 37.8 84 (48.8%) 18 (10.4%)
Sayin, 2020 Turkey Single Cross-sectional 64 64 37.8 25 (39.1%) 41 (64.1%) 13 (20.3%)
Tostmann, 2020 Netherlands Single Mar 10 -Mar 29 Cross-sectional 190 79 37 (46.8%) 7 (3.7%)
Tsivgoulis, 2020 Greece Single Mar 19- Apr 8 Case-control 22 22 55 6 (54.5%) 17 (77.3%) 8 (36.4%)
Vaira (1), 2020 Italy Single Mar 31 - Apr 6 Cross-sectional 72 60 (83.3%)
Vaira (2), 2020 Italy Mutli Cohort 345 48.5 146 (42.3%) 241 (69.9%)
Yan (1), 2020 USA Single Mar 3 -Mar 29 Cross-sectional 203 59 29 (49.2%) 40 (67.8%) 33 (16.3%)
Yan (2), 2020 USA Single Mar 3 - Apr 8 Cohort 128 75 (59.6%)
Zayet, 2020 France Single Feb 26-Mar 14 Cohort 54 70 50.4 29 (41.4%) 37 (54.2%) 9 (16.7%)

Figure 2.

Fig 2:

Forest plot demonstrating overall prevalence of “loss of smell” in COVID-19 patients.

Figure 3.

Fig 3:

Forest plot comparing prevalence in COVID-19 vs control group for “loss of smell”.

Figure 4.

Fig 4:

Forest plot comparing severe cases in COVID-19 group presenting with “loss of smell” to patients without “loss of smell”.

Discussion

We summarized the overall prevalence of “loss of smell” for COVID-19 patients and compared with control patients i.e. those without laboratory confirmation of COVID-19 from the same study period. The overall prevalence of “loss of smell” was significantly higher for the COVID-19 group compared to control group. In addition, “loss of smell” had a lower association with severe COVID-19 compared to COVID-19 patients without “loss of smell”.

Olfactory and gustatory changes are one of the most underreported symptoms in COVID-19 and can sometimes be only presenting symptoms in these patients.3 As demonstrated in our study, “loss of smell” was associated with somewhat favorable prognosis of the disease and hence careful screening should be undertaken to identify potential patients with COVID-19. These patients should undergo testing to rule out COVID-19. This will help in preventing the spread of the virus

We noted significant variations in the reporting of symptoms (i.e., dysosmia/anosmia/hyposmia/microsmia) in the studies. Mao et al. noted “loss of smell” in 5.1% of their cohort, while Moein et al. noted that roughly 98% of patients had “loss of smell”.2 , 18 Earlier studies such as by Mao et al. relied on the retrospective data collection and questionnaire based survey. As the olfactory symptoms became well-recognized, the newer studies might have assessed these patients specifically for these symptoms, resulting in a higher prevalence of olfactory symptoms. Further, only few studies objectively evaluated the “loss of smell” using validated tools.18 , 20 , 25 , 35 , 42 , 44 , 60 , 61 The objective methods used in literature to assess “loss of smell” included: “Sniffin Sticks test”, “The University of Pennsylvania Smell Identification Test (UPSIT)”, “Quick Smell Identification Test (Q-SIT)”, and “Connecticut Chemosensory Clinical Research Center Test (CCCRC test)”. We feel that the actual prevalence of olfactory symptoms could be much higher than what is reported as we have combined data from relatively older studies as well. Our results should be interpreted as such keeping in mind this important limitation.

Only 7 studies compared the disease severity in patients with “loss of smell” versus those without “loss of smell”. Although our results are limited due to the very small sample size, “loss of smell” was characterized by the less severe disease compared to those without this symptom. This finding is noteworthy and needs to be further explored in more extensive studies. The limitation of our analysis is the observational nature of the studies with significant variations in the reporting of symptoms and follow-up. A temporospatial association of the disease severity and the symptom was not possible. However, our study is novel as we performed a pooled analysis combining the statistical power and further compared and demonstrated the prevalence in the control group.

In conclusion, we demonstrate here that alteration in smell is prevalent in COVID-19 and should be included as one of the essential symptoms to screen the population. Further larger studies are urgently needed to evaluate the utility of olfactory dysfunction in patients with COVID-19, as demonstrated in our study. Therefore, alteration in the sense of smell should be added as a screening question to identify not only the symptomatic disease but also possible healthy (or presumed asymptomatic) carriers of the disease.

Author contributions

Conception and design: Muhammad Aziz, Hemant Goyal, Literature search: Wade M. Lee-Smith, First draft: Muhammad Aziz, Critical revision and editing: All authors, Final approval: All authors.

Footnotes

Conflict of Interest and Ethical statement: The authors have no commercial associations or sources of support that might pose a conflict of interest.

Source of funding: None.

Supplementary material associated with this article can be found in the online version at https://doi.org/10.1016/j.amjms.2020.09.017.

Appendix. SUPPLEMENTARY MATERIALS

Supplementary Figure 1: Funnel plot signifying visible asymmetry in studies evaluating “loss of smell” as outcome.

mmc1_lrg.jpg (100.1KB, jpg)
mmc2.docx (20.5KB, docx)

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Figure 1: Funnel plot signifying visible asymmetry in studies evaluating “loss of smell” as outcome.

mmc1_lrg.jpg (100.1KB, jpg)
mmc2.docx (20.5KB, docx)

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