The COVANOS trial – insight into post-COVID olfactory dysfunction and the role of smell training
Bibliographic record
Abstract
BACKGROUND: Olfactory dysfunction is a cardinal symptom of COVID-19 infection, however, studies assessing long-term olfactory dysfunction are limited and no randomised-controlled trials (RCTs) of early olfactory training have been conducted. METHODOLOGY: We conducted a prospective, multi-centre study consisting of baseline psychophysical measurements of smell and taste function. Eligible participants were further recruited into a 12-week RCT of olfactory training versus control (safety information). Patient-reported outcomes were measured using an electronic survey and BSIT at baseline and 12 weeks. An additional 1-year follow-up was open to all participants. RESULTS: 218 individuals with a sudden loss of sense of smell of at least 4-weeks were recruited. Psychophysical smell loss was observed in only 32.1%; 63 participants were recruited into the RCT. The absolute difference in BSIT improvement after 12 weeks was 0.45 higher in the intervention arm. 76 participants completed 1-year follow-up; 10/19 (52.6%) of participants with an abnormal baseline BSIT test scored below the normal threshold at 1-year, and 24/29 (82.8%) had persistent parosmia. CONCLUSIONS: Early olfactory training may be helpful, although our findings are inconclusive. Notably, a number of individuals who completed the 1-year assessment had persistent smell loss and parosmia at 1-year. As such, both should be considered important entities of long-Covid and further studies to improve management are highly warranted.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".