The impact of a medical food containing gammalinolenic and eicosapentaenoic acids on asthma management and the quality of life of adult asthma patients
Bibliographic record
Abstract
BACKGROUND: Leukotriene synthesis inhibitors and receptor antagonists are efficacious for the treatment of asthma. Diets containing the fatty acids gammalinolenic acid (GLA) and eicosapentaenoic acid (EPA) decrease leukotriene synthesis; however, their impact on asthma management and quality of life (QOL) has not been evaluated in asthmatic subjects. OBJECTIVE: To evaluate asthma management and the QOL of asthmatic adult subjects consuming a medical food emulsion containing GLA and EPA. RESEARCH DESIGN AND METHODS: Trial 1 was a randomized, prospective, double-blind, placebo-controlled, parallel group trial in atopic subjects with mild-to-moderate asthma (n = 35 evaluable) consuming a low dose (0.75 g GLA + 0.5 g EPA), high dose (1.13 g GLA + 0.75 g EPA) or placebo emulsion daily. Subjects were questioned about their asthma management using a non-validated questionnaire after 2 and 4 weeks. Blood leukotrienes were measured at baseline and after 4 weeks. Trial 2 was an open-label study (n = 65 evaluable) where subjects consumed the low-dose medical food emulsion, EFF1009, daily. QOL and asthma management were measured using the validated Mini Asthma Quality of Life (MiniAQLQ) and the Asthma Control (ACQ) questionnaires, respectively, administered at baseline and after 4 weeks. RESULTS: In Trial 1, leukotriene biosynthesis decreased (p < 0.05). Self-reported asthma status and bronchodilator use improved in subjects consuming low- and high-dose emulsion between week 2 and week 4 (p < 0.01), but not compared to placebo (p > 0.1). In Trial 2, mean +/- standard error total MiniAQLQ and ACQ scores improved by 1.5 +/- 0.2 and 1.0 +/- 0.1, respectively (p < 0.001). Subdomain scores from MiniAQLQ improved and rescue bronchodilator use decreased (p < 0.001). CONCLUSION: The inclusion of the medical food EFF1009 in asthma management regimens can improve patient quality of life and decrease reliance on rescue medication.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".