The Long-Term Loss of Smell and Taste in COVID-19 Patients – A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Introduction: Olfactory symptoms have been reported as particular in COVID-19 patients. Objective: To synthesize and analyze the existing evidence on the monitoring loss of sense of smell and taste in COVID-19 patients, and for how long symptoms persist after the virus is no longer active in the organism. Methods: A search was implemented in PubMed, Embase, Scopus, Science Direct, and Web of Science databases. This systematic review and meta-analysis were conducted according to PRISMA, and the risk of bias was assessed through the Newcastle-Ottawa Scale. The review protocol is registered in PROSPERO. Results: Our systematic review included data from 14 articles with a total of 2143 participants. The most reported sensory symptom of COVID-19 was anosmia, which was detected in 1499 patients, being the only symptom to appear in all studies. Ageusia was detected in 595 patients, dysgeusia in 514 patients, and hyposmia in 209 patients. The studies provided the number of 729 patients with sensory symptoms during the acute COVID-19 infection of 15 days, and 1020 patients with lasting sensory symptoms, presenting sensory dysfunctions after the average latent period of 15 days of the acute COVID-19 infection. Conclusion: Evidence points to the loss or dysfunction of taste and smell as one of the symptoms of COVID-19 persisting for an average time of 15 days, with 44% of COVID-19 patients with persistent symptoms for more than 15 days. Nevertheless, most studies do not perform a follow-up with those patients. Therefore, further research on sensory symptoms and their follow-up is required.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.032 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".