Prevalence of olfactory dysfunction among postpartum women and impact of SARS-CoV-2 infection during pregnancy
Bibliographic record
Abstract
Olfactory dysfunction resulting from COVID-19 has imparted a lasting impact on olfaction among the general public, including pregnant women contracting SARS-CoV-2 infection. While olfactory dysfunction can impact physical, mental, and psychosocial well-being, there has been little research on olfaction during pregnancy and postpartum, nor the impact of SARS-CoV-2 infection on olfaction while pregnant. Therefore, the primary study aims are to evaluate olfaction in the postpartum period and determine the impact of antecedent SARS-CoV-2 infection. We recruited two cohorts of postpartum women, those with a history of SARS-CoV-2 infection before or during pregnancy (COVID cohort; n = 109) and those without (non-COVID cohort; n = 226), and evaluated their olfaction during the postpartum period by administering the University of Pennsylvania Smell Identification Test. Participants were queried about demographics, past SARS-CoV-2 infections, self-reported sense of smell (both in overall ability to smell and for the presence of qualitative smell issues such as parosmia and phantosmia), and perceived cause of smell loss, if any. We found significantly fewer postpartum women with normosmia capabilities in both COVID (27%) and non-COVID (46%) cohorts compared to normative data for aged-matched (30 to 39 years) women (83%). Women in the non-COVID cohort had significantly higher UPSIT scores and mean subjective olfaction ratings than those in the COVID cohort (95% CI [0.77,2.41] and 95% CI [-0.83,7.34], respectively). This study reflects the largest published cohort of postpartum women evaluated for olfactory function with standardized psychophysical testing. Our findings suggest both postpartum and SARS-CoV-2 infection are associated with diminished smell function.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".