Tiotropium add-on to inhaled corticosteroids versus addition of long-acting β2-agonists for adults with asthma
Bibliographic record
Abstract
Additional management options, and better use of current options, are needed to help support a large proportion of patients with asthma whose symptoms remain uncontrolled on inhaled corticosteroids (ICS). Here, we aim to review the safety and efficacy of adding tiotropium to ICS compared with adding a long-acting β 2 -agonist (LABA) for adults whose asthma is not well controlled on ICS alone. Adding tiotropium to a background of ICS provides beneficial effects that are comparable with addition of a LABA in terms of lung function measures, exacerbations, asthma control and other endpoints. In addition, tiotropium and LABAs are both well tolerated. Some patients respond to either tiotropium or LABA treatment, but not both, suggesting that there are groups of patients that may respond better to one of these drugs. Currently, tiotropium is recommended as an add-on therapy in patients with severe asthma (Global Initiative for Asthma Steps 4 and 5) whose asthma is uncontrolled despite treatment with ICS/LABA. Tiotropium is also effective in patients with less severe disease and may benefit patients who experience adverse events from LABA treatment or where LABAs are ineffective. Tiotropium is therefore an important therapeutic option in asthma, not only as recommended as an add-on treatment with ICS/LABA, but also as an alternative to the addition of LABA to maintenance therapy with an ICS.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".