Efficacy of Jia Wei Yang He formula as an adjunctive therapy for asthma: study protocol for a randomized, double blinded, controlled trial
Bibliographic record
Abstract
Over the past two or three decades, the prevalence of asthma has significantly increased worldwide; therefore, effective treatment without side effects is of utmost importance. Traditional Chinese medicine (TCM) plays a vital role in reducing symptoms and improving the quality of life in persistent-asthma patients. The aim of this study is to evaluate the efficacy of the Jia Wei Yang He (JWYH) formula in the treatment of asthma and to explore the relationship between the airway microbiome and TCM treatment in asthma patients. This multicenter, parallel-arm, randomized, double-blinded, placebo-controlled trial will assess the efficacy of JWYH in asthma patients with usual care. Persistent-asthma patients without life-threatening disease will be enrolled on a random basis and are equally assigned to a high- or a low-dose JWYH plus usual care group, or a placebo plus usual care group. Patients are followed up for 4 months. Accordingly, 240 patients will yield sufficient statistical power to determine a difference between groups. Based on modified intent-to-treat (mITT) analyses, the three groups will be compared at 4 weeks after the beginning of treatment. The primary efficacy measurement is the mean change in the Asthma Control Test (ACT) score from baseline to 4 weeks post treatment. Secondary outcomes include forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), peak expiratory flow (PEF), and asthma exacerbations. This trial also includes analyses of the associations between airway microbiome and asthma treatment. In this study, a randomized clinical trial design is described. The results are based on several outcomes that estimate the efficacy of the JWYH formula and prospective links between the airway microbiome and asthma treatment. ClinicalTrials.gov, ID: NCT03299322 . Registered on 3 October 2017.
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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 | 0.020 | 0.021 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.014 | 0.005 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.059 | 0.010 |
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".