Effect of low salicylate diet on clinical and inflammatory markers in patients with aspirin exacerbated respiratory disease – a randomized crossover trial
Bibliographic record
Abstract
BACKGROUND: Aspirin-exacerbated respiratory disease (AERD) is characterized by eosinophilic rhinosinusitis, nasal polyposis, and bronchial asthma, along with the onset of respiratory reactions after the ingestion of nonsteroidal anti-inflammatory drugs (NSAIDs) or acetylsalicylic acid (ASA). In addition to the therapeutic routines and surgical options available, a low dietary intake of food salicylate has been suggested as adjunctive therapy for this condition. This study aimed to assess the influence of a short-term low salicylate diet on inflammatory markers in patients with AERD and whether that would result in symptomatic improvement. METHODS: Prospective study with randomization to either a high or low salicylate diet for 1 week, followed by cross-over to the other study arm. Participants were asked to record their dietary salicylate for each week of the study. Urinary creatinine, salicylate and leukotriene levels were measured at the time of recruitment, end of week one and end of week two and the SNOT-22 questionnaire was filled out at the same time points. RESULTS: A total of seven participants completed the study. There was no statistical difference in the urinary salicylate and leukotriene levels between the two diets; nevertheless, participants on low salicylate diet reported improved SNOT-22 symptoms scores (p = 0.04), mainly in the rhinologic, ear/facial, and sleep dysfunction symptom domains. In addition, these last two domains outcomes were more significant than the minimal clinically important difference. CONCLUSIONS: A short-term low salicylate diet may not result in biochemical outcomes changes but seems to provide significant symptomatic relief for patients with AERD. TRIAL REGISTRATION: NCT01778465 ( www.clinicaltrials.gov ).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".