Rhinosinusitis-Related Quality of Life during Pregnancy
Bibliographic record
Abstract
BACKGROUND: Pregnancy rhinitis manifests as nasal congestion, with resolution of symptoms after delivery. Eighteen to 30% of pregnant patients report symptoms of rhinitis. Pregnancy rhinitis may have an adverse effect on quality of life (QOL) and may cause obstructive sleep apnea (OSA), which in turn may adversely affect the outcome of pregnancy. Previous examinations of the prevalence of pregnancy rhinitis during different stages of pregnancy have been inconclusive. This study aimed to determine rhinosinusitis-specific QOL during different stages of pregnancy. METHODS: A cross-sectional observation study of patients in the second and third trimesters of pregnancy using the 22-item Sino-Nasal Outcome Test (SNOT-22) was conducted in the obstetric clinic at McGill University Health Center in Montreal, Canada. Seventy-six low- risk pregnant patients were included in the study. Thirty-two patients were in the second trimester of pregnancy and 44 patients were in the third trimester. RESULTS: Average item scores for the entire questionnaire were significantly higher (p = 0.041), indicating more severe impairment of QOL, in the third trimester in comparison with the second trimester. A comparison between women with and without preexisting allergic rhinitis, in both the second and the third trimesters, shows significantly higher SNOT-22 scores for the allergic group (p = 0.007). QOL was lower in the third trimester than in nonrhinosinusitis patients (p = 0.011). CONCLUSION: Rhinosinusitis-specific QOL is lower in the third trimester of pregnancy in comparison with the second trimester and also in comparison with nonrhinosinusitis patients. Increased awareness may enhance the QOL of pregnant patients, prevent OSA, and thereby positively influence the outcome of pregnancy.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".