Taste loss as a distinct symptom of COVID-19: a systematic review and meta-analysis

Abstract

Chemosensory scientists have been skeptical that reports of COVID-19 taste loss are genuine, in part because before COVID-19 taste loss was rare and often confused with smell loss. Therefore, to establish the predicted prevalence rate of taste loss in COVID-19 patients, we conducted a systematic review and meta-analysis of 376 papers published in 2020-2021, with 235 meeting all inclusion criteria. Drawing on previous studies and guided by early meta-analyses, we explored how methodological differences (direct vs. self-report measures) may affect these estimates. We hypothesized that direct measures of taste are at least as sensitive as those obtained by self-report and that the preponderance of evidence confirms taste loss is a symptom of COVID-19. The meta-analysis showed that, among 138,015 COVID-19-positive patients, 36.62% reported taste dysfunction (95% confidence interval: 33.02%-40.39%), and the prevalence estimates were slightly but not significantly higher from studies using direct (n = 15) versus self-report (n = 220) methodologies (Q = 1.73, df = 1, P = 0.1889). Generally, males reported lower rates of taste loss than did females, and taste loss was highest among middle-aged adults. Thus, taste loss is likely a bona fide symptom of COVID-19, meriting further research into the most appropriate direct methods to measure it and its underlying mechanisms.

Keywords: COVID-19; ageusia; coronavirus; gustatory dysfunction; taste loss.

Figure 1.

CONSORT flow diagram demonstrating the article selection process for this systematic review and meta-analysis.

Figure 2.

Orchard plot of taste loss and COVID-19, following the guidelines outlined by Nakagawa et al. (2020). The point estimate of the pooled prevalence (trunk) is represented by the bold turquoise or pink dot. The confidence interval of the pooled prevalence estimate (branch) is represented by the bold black line, and the prediction interval (twig) is represented by the thin black line. Individual prevalence estimates from each study are represented by the scattered colored points (slightly transparent circles, called fruits). Each fruit is scaled by the precision of the point estimate of prevalence for each study (i.e. inverse of the standard error).