Comparative nasal airflow with loratadine-pseudoephedrine and fluticasone nasal spray for allergic rhinitis
Bibliographic record
Abstract
BACKGROUND: Although it is known that oral antihistamine-pseudoephedrine combination tablets have a faster onset than intranasal corticosteroid sprays in the treatment of allergic rhinitis after the first dose, the magnitude of change has not been measured in a comparative manner. Furthermore, the sensation of sprayed liquid in the nose may lead patients to mistakenly believe that intranasal steroid sprays work instantly. OBJECTIVE: To evaluate, numerically, nasal airflow changes provided by a single dose of loratadine-pseudoephedrine tablet (LP) and fluticasone propionate nasal spray (FP) in participants experiencing allergic rhinitis symptoms, including nasal congestion. METHODS: This single-center, double-blinded, placebo-controlled, crossover study evaluated objective nasal airflow changes in patients with a documented sensitivity to ragweed pollen. Participants were randomized to receive 1 of 4 treatment sequences, and their peak nasal inspiratory flow (PNIF) was measured in a span of 4 hours after pollen exposure in an environmental exposure unit. RESULTS: Average change in PNIF was 31% with LP in the course of the study, significantly greater than with placebo and FP (12% and 15%, respectively; P < .001). Nevertheless, FP did not produce a significant change compared with its placebo. At hour one post-dose, LP had a clinically significant 31% increase in PNIF, whereas FP only yielded an 8.6% increase (P < .001). Measurable nasal airflow improvements are associated with the opening of nasal passages, allowing congested patients to breathe more freely. CONCLUSION: A single dose of LP quickly and significantly (P < .001) improved nasal airflow after ragweed pollen challenge in an environmental exposure unit. Comparatively, FP did not display this same benefit. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03443843.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".