Efficacy of probiotics as adjuvant therapy in bronchial asthma: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background Asthma is a chronic, heterogeneous disease characterized by airway inflammation. Asthma exacerbations significantly increase the disease burden, necessitating new therapeutic approaches. Emerging evidence suggests probiotics, through the gut-lung axis, may benefit asthma management by modulating immune responses and reducing inflammation. Methods This systematic review and meta-analysis adhered to PRISMA guidelines and was registered with PROSPERO (CRD42023480098). A comprehensive search of PubMed, Scopus, Web of Science, and Embase was conducted up to March 2024. Inclusion criteria encompassed randomized controlled trials (RCTs) evaluating probiotic interventions in asthma patients. Statistical analysis was done using RevMan 5.3, with odds ratios (OR) and 95% confidence intervals (CI) calculated, and heterogeneity assessed using I2 statistics. Results Twelve RCTs, comprising 1401 participants, met the inclusion criteria. The probiotic strains investigated included various Lactobacillus and Bifidobacterium species. Meta-analysis revealed significant improvements in asthma control test scores (OR 1.18, 95% CI: 1.18–3.64, p = 0.0001) following probiotic supplementation. Probiotics also improved fractional exhaled nitric oxide (FeNO) in one study, but pooled FeNO and eosinophil data were not statistically significant (p = 0.46 and p = 0.29, respectively). One study observed fewer asthma exacerbations in the probiotic group (24/212) compared to placebo (67/210), with no difference in exacerbation duration. Conclusion Probiotic supplementation may be beneficial in improving asthma symptom control with no significant impact on lung function indices or eosinophil levels. Probiotics can be a potential adjunctive therapy in asthma management, particularly for asthma symptom control.
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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 | 0.014 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.026 | 0.044 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".