Diagnostic value of IL-6 for patients with asthma: a meta-analysis
Bibliographic record
Abstract
BACKGROUND: IL-6 is a pleotropic cytokine that acts as a pro-inflammatory mediator and acute-phase response inducer, but has also been reported to possess anti-inflammatory properties. The objective of this study was to assess the validity of serum IL-6 test for diagnosis of asthma. METHODS: A literature search was conducted using PubMed, Embase, and Cochrane library from January 2007 to March 2021 to identify relevant studies. Eleven studies were included in this analysis, involving 1977 patients with asthma and 1591 healthy non-asthmatic controls. The meta-analysis was performed using Review Manager 5.3 software and Stata 16.0. Random effect model or fixed effect model (FEM) was used to estimate the standardized mean differences (SMDs) with 95% confidence intervals (CIs). RESULTS: The meta-analysis results revealed that the serum IL-6 levels were higher in asthmatic patients than healthy non-asthmatic controls (SMD 1.31, 95% CI 0.82-1.81, P < 0.00001). IL-6 levels are significantly elevated in pediatric patients with asthma (SMD 1.58, 95% CI 0.75-2.41, P = 0.0002) and mildly elevated in adult patients with asthma (SMD 1.08, 95% CI 0.27-1.90, P = 0.009). In addition, a subgroup analysis of asthma disease status showed that IL-6 levels were increased in stable (SMD 0.69, 95% CI 0.28-1.09, P = 0.009) and exacerbation asthma (SMD 2.15, 95% CI 1.79-2.52, P < 0.00001) patients. CONCLUSION: The results of this meta-analysis suggest that serum IL-6 levels were significantly elevated in asthmatic patients as compared to normal population. IL-6 levels can be used as an auxiliary indicator to distinguish individuals with asthma from healthy non-asthmatic controls.
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 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 | 0.021 | 0.049 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.069 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".