Persisting chemosensory impairments in 366 healthcare workers following COVID-19: an 11-month follow-up
Bibliographic record
Abstract
Olfactory and gustatory dysfunctions (OD, GD) are prevalent symptoms following COVID-19 and persist in 6%-44% of individuals post-infection. As only few reports have described their prognosis after 6 months, our main objective was to assess the prevalence of OD and GD 11-month post-COVID-19. We also aimed to determine intraclass correlation coefficients (ICC) of chemosensory self-ratings for the follow-up of chemosensory sensitivity. We designed an observational study and distributed an online questionnaire assessing chemosensory function to healthcare workers with a RT-PCR-confirmed SARS-CoV-2 infection 5- and 11-month post-COVID-19. Specifically, we assessed olfaction, gustation, and trigeminal sensitivity (10-point visual analog scale) and function (4-point Likert scale). We further measured clinically relevant OD using the Chemosensory Perception Test, a psychophysical test designed to provide a reliable remote olfactory evaluation. We included a total of 366 participants (mean [SD] age of 44.8 (11.7) years old). They completed the last online questionnaire 10.6 months (0.7) after the onset of COVID-19 symptoms. Of all participants, 307 (83.9%) and 301 (82.2%) individuals retrospectively reported lower olfactory or gustatory sensitivity during the acute phase of COVID-19. At the time of evaluation, 184 (50.3%) and 163 (44.5%) indicated reduced chemosensory sensitivity, 32.2% reported impairment of olfactory function while 24.9% exhibited clinically relevant OD. Olfactory sensitivity had a high test-retest reliability (ICC: 0.818; 95% CI: 0.760-0.860). This study suggests that chemosensory dysfunctions persist in a third of COVID-19 patients 11 months after COVID-19. OD appears to be a common symptom of post-COVID-19 important to consider when treating patients.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".