The clinical impact of single inhaler therapy in asthma
Bibliographic record
Abstract
BACKGROUND: Low-dose budesonide/formoterol combination used in the SMART fashion with symptom-reactive supplemental dosing has been reported to reduce asthma exacerbations as compared to the use of budesonide alone or to lower doses of budesonide/formoterol without supplemental dosing. OBJECTIVE: We undertook to review the non-exacerbation outcomes of SMART therapy and to assess the patient education implications of this treatment strategy. MATERIALS & METHODS: Systematic review. RESULTS: Patients treated with this strategy appear to be under-treated in that the majority fail to achieve guideline-defined control standards. The SMART strategy has not been tested against equivalent or higher doses of budesonide/formoterol given in symptom-prevention fashion. Existing educational strategies that focus on recognition of poor disease control may not be applicable with SMART therapy and the use of action plans has not been clarified with this symptom-reactive strategy. There is some evidence from that the current clinical use of SMART therapy may be contaminated frequently by the concurrent prescription of short-acting bronchodilators. There is no information on long-term outcomes with a symptom-reactive ICS/LABA strategy but the use of the strategy for one year has been associated with rising sputum and airway biopsy eosinophil counts. CONCLUSION: Despite fewer severe exacerbations with SMART therapy as compared to ICS monotherapy or lower dose ICS/LABA therapy, the strategy produces poor day-to-day control of symptoms and is associated with increasing inflammation. CLINICAL RELEVANCE: The symptom-reactive strategy described as SMART therapy is associated with poor symptom control of asthma.
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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 | 0.008 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".