Krebs von den lungen-6 as a clinical marker for hypersensitivity pneumonitis: A meta-analysis and bioinformatics analysis
Bibliographic record
Abstract
Aim: Hypersensitivity pneumonitis (HP), also referred to as exogenous allergic alveolitis, is one of the most common interstitial lung diseases (ILDs). A potential immune biomarker, Krebs von den lgen-6 (KL-6) characterizes the progression and severity of HP. The meta-analysis in this study was conducted to elucidate the variations in the concentrations of KL-6 in different types of HP. Methods: A systematic search of various databases such as EMBASE, Pubmed, CNKI, VIP, Web of Science, and WanFang was carried out to find relevant published articles between January 1980 and August 2022 that explored the relationship between KL-6 and allergic pneumonia. Standardized mean difference (SMD) and 95% confidence interval (CI) were used as effect sizes for comparison among different groups. The GSE47460 and GSE150910 datasets were downloaded to extract and validate the differences in KL-6 mRNA expression between HP lung tissue and healthy controls. Furthermore, the single-cell sequencing dataset GSE135893 was downloaded to extract KL-6 mRNA expression in type II alveolar epithelial cells to validate the differences between HP and healthy controls. Two researchers evaluated the quality of the included studies by employing Newcastle-Ottawa Scale. All the qualified studies were subjected to statistical analyses carried out utilizing RevMan 5.2, Stata 11.0, and R software 4.1.3. Results: Twenty studies aligned perfectly with the inclusion criteria of the meta. The concentrations of KL-6 were substantially higher in the blood of HP patients as compared to the control group. Subgroup analyses were carried out in accordance with the allergen source and the results revealed that patients with different allergens had higher blood KL-6 concentrations than healthy controls. Additionally, different subgroups of subjects were created for meta-analysis as per the fibrosis status, race, measurement method, and sample type. The concentration of KL-6 in blood was much higher in all HP subgroups than in healthy control groups. Moreover, the bioinformatics analysis revealed that KL-6 mRNA expression was higher in HP lung tissue and type II alveolar epithelial cells as compared to healthy controls. Conclusion: The present meta-analysis and bioinformatics analysis suggested that the concentration levels of KL-6 varied between HP patients and healthy individuals, and the KL-6 concentrations may be higher in the blood samples of HP patients. Systematic review registration: https://www.crd.york.ac.uk/prospero/, CRD42022355334.
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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 | 0.017 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.060 |
| Bibliometrics | 0.009 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".