Analysis of variable metabolites in preterm infants with bronchopulmonary dysplasia: a systematic review and meta-analysis
Bibliographic record
Abstract
Numerous studies have attempted to identify potential biomarkers for early detection of bronchopulmonary dysplasia (BPD) in preterm infants using metabolomics techniques. However, the presence of consistent evidence remains elusive. Our study aimed to conduct a systematic review and meta-analysis to identify differences in small-molecule metabolites between BPD and non-BPD preterm infants. Through meticulous screening of numerous samples, we identified promising candidates, providing valuable insights for future research. We searched PubMed, the Cochrane Library, Embase, Web of Science, China National Knowledge Internet, Wan-fang database, Chinese Science and Technique Journal Database and Chinese Biomedical Literature Database from inception until January 16, 2024. Studies were comprehensively reviewed against inclusion criteria. We included case-control studies and adhered to Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. Study quality was assessed with the Newcastle-Ottawa scale. We compared the changes in metabolite levels between the BPD and non-BPD preterm infants. A meta-analysis was conducted on targeted metabolomics research data based on the strategy of standardized mean differences (MD) and 95% confidence intervals (CI).Fifteen studies (1357 participants) were included. These clinical-based metabolomics studies clarified 110 differential metabolites between BPD and non-BPD preterm infants. The meta-analysis revealed higher glutamate concentration in the BPD group compared to the non-BPD group (MD = 1, 95% CI 0.59 to 1.41, p < 0.00001). Amino acids were identified as the key metabolites distinguishing preterm infants with and without BPD, with glutamate potentially serving as a BPD predictor in this population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.024 | 0.009 |
| Bibliometrics | 0.015 | 0.026 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".