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Record W4403836510 · doi:10.1001/jama.2024.22700

Inhaled Reliever Therapies for Asthma

2024· review· en· W4403836510 on OpenAlexaff
Daniel Rayner, Dario Ferri, Gordon H Guyatt, Paul M. O’Byrne, Romina Brignardello‐Petersen, Farid Foroutan, Bradley E. Chipps, Kaharu Sumino, Tamara T. Perry, Sharmilee M. Nyenhuis, John Oppenheimer, Elliot Israel, Flavia Hoyte, Katherine Rivera‐Spoljaric, Ellen McCabe, Susana Rangel, Lindsay Shade, Valerie G. Press, Lisa Hall, Dia Sue-Wah-Sing, Angel Melendez, H. C. Orr, Tonya Winders, Donna D. Gardner, Matthew A. Rank, Leonard B. Bacharier, Giselle Mosnaim, Derek K. Chu

Bibliographic record

VenueJAMA · 2024
Typereview
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsMcMaster UniversityImpact
FundersNational Institute on Minority Health and Health DisparitiesNational Heart, Lung, and Blood Institute
KeywordsMedicineFormoterolAsthmaRandomized controlled trialMEDLINERelative riskAdverse effectData extractionQuality of life (healthcare)Internal medicinePediatricsBudesonideConfidence interval

Abstract

fetched live from OpenAlex

Importance: The optimal inhaled reliever therapy for asthma remains unclear. Objective: To compare short-acting β agonists (SABA) alone with SABA combined with inhaled corticosteroids (ICS) and with the fast-onset, long-acting β agonist formoterol combined with ICS for asthma. Data Sources: The MEDLINE, Embase, and CENTRAL databases were searched from January 1, 2020, to September 27, 2024, without language restrictions. Study Selection: Pairs of reviewers independently selected randomized clinical trials evaluating (1) SABA alone, (2) ICS with formoterol, and (3) ICS with SABA (combined or separate inhalers). Data Extraction and Synthesis: Two reviewers independently extracted data and assessed risk of bias. Random-effects meta-analyses synthesized outcomes. GRADE (Grading of Recommendations Assessment, Development, and Evaluation) was used to evaluate the certainty of evidence. Main Outcomes and Measures: Asthma symptom control (5-item Asthma Control Questionnaire; range, 0-6, lower scores indicate better asthma control; minimum important difference [MID], 0.5 points), asthma-related quality of life (Asthma Quality of Life Questionnaire; range, 1-7, higher scores indicate better quality of life; MID, 0.5 points), risk of severe exacerbations, and risk of serious adverse events. Results: A total of 27 randomized clinical trials (N = 50 496 adult and pediatric patients; mean age, 41.0 years; 20 288 male [40%]) were included. Compared with SABA alone, both ICS-containing relievers were associated with fewer severe exacerbations (ICS-formoterol risk ratio [RR], 0.65 [95% CI, 0.60-0.72]; risk difference [RD], -10.3% [95% CI, -11.8% to -8.3%]; ICS-SABA RR, 0.84 [95% CI, 0.73-0.95]; RD, -4.7% [95% CI, -8.0% to -1.5%]) with high certainty. Compared with SABA alone, both ICS-containing relievers were associated with improved asthma control (ICS-formoterol RR improvement [MID] in total score, 1.07 [95% CI, 1.04-1.10]; RD, 4.1% [95% CI, 2.3%-5.9%]; ICS-SABA RR, 1.09 [95% CI, 1.03-1.15]; RD, 5.4% [95% CI, 1.8%-8.5%]) with high certainty. In an indirect comparison with ICS-SABA, ICS-formoterol was associated with fewer severe exacerbations (RR, 0.78 [95% CI, 0.66-0.92]; RD, -5.5% [95% CI, -8.4% to -2.0%]) with moderate certainty. Compared with SABA alone, ICS-formoterol (RD, -0.6% [95% CI, -1.3% to 0%]) was not associated with increased risk of serious adverse events (high certainty) and ICS-SABA (RD, 0% [95% CI, -1.1% to 1.2%]) was not associated with increased risk of serious adverse events (moderate certainty). Conclusions and Relevance: In this network meta-analysis of patients with asthma, ICS combined with formoterol and ICS combined with SABA were each associated with reduced asthma exacerbations and improved asthma control compared with SABA alone.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.018
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0120.002

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.

Opus teacher head0.042
GPT teacher head0.361
Teacher spread0.318 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations52
Published2024
Admission routes1
Has abstractyes

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