Matched cohort study of therapeutic strategies to prevent preschool wheezing/asthma attacks
Bibliographic record
Abstract
Background: An inhaled corticosteroid (ICS) or leukotriene receptor antagonist (LTRA) may prevent wheezing/asthma attacks in preschoolers with recurrent wheeze when added to short-acting β-agonist (SABA). Objective: The aim of this historical matched cohort study was to assess the effectiveness of these treatments for preventing wheezing/asthma attacks. Methods: Electronic medical records from the Optimum Patient Care Research Database were used to characterize a UK preschool population (1-5 years old) with two or more episodes of wheezing during 1 baseline year before first prescription (index date) of ICS or LTRA, or repeat prescription of SABA. Children initiating ICS or LTRA on the index date were matched 1:4 to those prescribed only SABA for age, sex, year of index prescription, mean baseline SABA dose, baseline attacks, baseline antibiotic prescriptions, and eczema diagnosis. Wheezing/asthma attacks (defined as asthma-related emergency attendance, hospital admission, or acute oral corticosteroid prescription) during 1 outcome year were compared using conditional logistic regression. Results: Matched ICS and SABA cohorts included 990 and 3,960 children, respectively (61% male; mean [SD] age 3.2 [1.3] years), and matched LTRA and SABA cohorts included 259 and 1,036 children, respectively (65% male; mean [SD] age 2.6 [1.2] years). We observed no significant difference between matched cohorts in the odds of a wheezing/asthma attack: ICS vs SABA, OR (95% CI) 1.01 (0.85-1.19) and LTRA vs SABA, OR (95% CI) 1.28 (0.96-1.72). Conclusion: We found no evidence that initiation of ICS or LTRA therapy is associated with fewer attacks during 1 outcome year than SABA alone for a heterogeneous group of preschool children with recurrent wheeze in the real-life clinical setting.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".