A multidisciplinary clinic for children with severe asthma: Clinical outcomes and healthcare utilization
Bibliographic record
Abstract
Background: Children with problematic severe asthma experience significant burden. A novel multidisciplinary clinic aims to improve lung function and decrease healthcare utilization associated with severe asthma. Objective: To examine clinical outcomes and healthcare utilization of children with problematic severe asthma managed in a multidisciplinary clinic rather than a standard asthma clinic. Methods : A quasi-experimental, retrospective study examined the Intensive Management of Asthma Clinic (IMAC)(n=45) and standard asthma clinic (n=113) at a tertiary care children's hospital. Data collected from 24 months pre/post time 0 (IMAC enrollment, or met criteria for severe asthma) included: FEV1, and oral steroid courses. The number of clinic visits, emergency department (ED) visits, and hospitalizations were extracted from administrative databases. Linear mixed effects models for repeated measures analyzed changes over time. Results: Lung function improved over time for children cared for in both settings (ΔFEV1=3%, p<0.01). There was an additional improvement in lung function in children in the IMAC compared to the standard clinic (ΔFEV1=5%, p=0.01). There was no significant difference in oral steroid courses. IMAC patients had, on average, 0.2 more clinic visits (p<0.01) and 0.1 less ED visits (p<0.01) than patients in the standard asthma clinic. Over time, hospitalizations decreased by 0.03 regardless of clinic (p<0.01). Conclusion: A multidisciplinary clinic reduces ED visits, and improves lung function of children with problematic severe asthma. Additional clinic visits for IMAC patients are offset by a subsequent decrease in emergency visits for asthma exacerbations.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".