Objective olfactory evaluation of self‐reported loss of smell in a case series of 86 <scp>COVID</scp> ‐19 patients
Bibliographic record
Abstract
OBJECTIVE: To investigate olfactory dysfunction (OD) in patients with mild coronavirus disease 2019 (COVID-19) through patient-reported outcome questionnaires and objective psychophysical testing. METHODS: COVID-19 patients with self-reported sudden-onset OD were recruited. Epidemiological and clinical data were collected. Nasal complaints were evaluated with the sinonasal outcome-22. Subjective olfactory and gustatory status was evaluated with the National Health and Nutrition Examination Survey. Objective OD was evaluated using psychophysical tests. RESULTS: Eighty-six patients completed the study. The most common symptoms were fatigue (72.9%), headache (60.0%), nasal obstruction (58.6%), and postnasal drip (48.6%). Total loss of smell was self-reported by 61.4% of patients. Objective olfactory testings identified 41 anosmic (47.7%), 12 hyposmic (14.0%), and 33 normosmic (38.3%) patients. There was no correlation between the objective test results and subjective reports of nasal obstruction or postnasal drip. CONCLUSION: A significant proportion of COVID-19 patients reporting OD do not have OD on objective testing.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".