Clinical remission and small airway improvements after one-year FF/UMEC/VI
Bibliographic record
Abstract
Rationale: Single-inhaler triple therapy significantly improves lung function (FEV1), asthma control and exacerbations. The mechanism by which this occurs at the level of the small-airways, is not well-understood. We investigated CT and MRI markers and clinical measures consistent with clinical remission (Perez-De Llano; AJRCCM 2024) after 1-year FF/UMEC/VI in 15 participants with moderate-severe asthma who had been poorly controlled on ICS/LABA. Methods & Results: Participants consented to baseline, 6-week and an optional open-extension 1-year visit, step-up to fluticasone-furoate/umeclidinium/vilanterol (200/62.5/25µg), CT, spirometry, oscillometry, 129Xe MRI and the asthma-control questionnaire (ACQ-5) at each visit. Exacerbations and OCS use were documented via the electronic health record. CT airway measurements included total airway count (TAC), lumen area (LA), and mucus-score. 129Xe MRI ventilation defect percent (VDP) was quantified (Kirby; Acad Radiol 2012). Of 28 participants who completed baseline and 6-week visits, 15 returned at 1-year. Significantly improved pre-bronchodilator VDP (P=.02) and FEV1 (P=.008) at 6-weeks persisted at 1-year. Airway mucus-score (P=.01), LA (P=.03) and TAC (P=.03) significantly improved at 1-year whilst 48 mucus-plugs at baseline resolved (83%) and 15 new plugs were identified resulting in a 57% decrease (25 vs. 58) in plugs. Two- (no OCS or exacerbations), 3-(2domain+ACQ-5≤0.75 control), 3-(2domain+FEV1 improved 200ml) and 4-domain remission was observed in 11/73%, 7/47%, 11/73%, and 7/47% participants. Conclusions: 1-year FF/UMEC/VI (200/62.5/25µg) resulted in improved airway mucus, LA, TAC and VDP and 4-domain clinical remission in 7/15 evaluated participants.
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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) | 0.000 | 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 | 0.001 | 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".