High‐dose sublingual immunotherapy in patients with uncontrolled allergic rhinitis sensitized to pollen: a real‐life clinical study
Bibliographic record
Abstract
BACKGROUND: High-dose pollen sublingual immunotherapy (SLIT) is indicated in patients with moderate to severe allergic rhinitis (AR), especially those who are unable to control their disease with pharmacotherapy. We explore the use of high-dose SLIT in patients with severe AR and sensitized to pollen, in real-life clinical practice. We also analyzed the effect on asthma. METHODS: This was a prospective observational study conducted at the Allergy outpatient clinic at Hotel Dieu de France Hospital (HDF), Beirut, Lebanon. The cohort, composed of 118 patients between 7 and 55 years old, was regularly evaluated at inclusion, at 12 months, and at 36 months. Fifty-five percent of AR patients had associated controlled asthma. Patients received a standardized pollen extract (Staloral 300IR). The pollen combination was 1 to 3 pollens, the most commonly used were Parietaria judaica, Cupressaceae, 5 grasses, and Oleaceae. In a previous study, those were the main allergenic pollens correlated to AR in the same population. Global assessment of the effect of SLIT was measured using a rhinitis total symptom score (RTSS), a rhinitis medication consumption score (RMCS), a global asthma score (ASS), and an asthma medication consumption score (AMCS). RESULTS: Using a t test we found that the average scores at inclusion, 12 months, and 36 months, respectively, were as follows: RTSS: 31.32, 16.39 (p < 0.041), and 13.35 (p < 0.041); RMCS: 6.96, 1.96 (p < 0.0162), and 1.61 (p < 0.0162); ASS: 4.62, 1.96 (p < 0.0005), and 1.33 (p < 0.0005); and AMCS: 2.35, 0.78 (p < 0.0005), and 0.7 (p < 0.0005). CONCLUSION: Our study showed favorable results of SLIT to aeroallergens in patients with uncontrolled AR. The effect is also applicable to the subgroup of patients suffering from concomitant, controlled asthma.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".