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Record W4413879905 · doi:10.15586/aei.v53i5.1394

Association between serum copper and childhood asthma: A systematic review and meta-analysis

2025· review· en· W4413879905 on OpenAlexaboutno aff
Beilei Wang, Xinming Su, Xiang Ma

Bibliographic record

VenueAllergologia et Immunopathologia · 2025
Typereview
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMeta-analysisAsthmaAssociation (psychology)Systematic reviewMEDLINEImmunologyInternal medicine

Abstract

fetched live from OpenAlex

Background: Asthma is a chronic respiratory disease with complex pathogenesis. Some studies suggest that certain trace metals may be associated with asthma. However, the relationship between serum copper (Cu) and childhood asthma remains unclear. This meta-analysis evaluates the association between Cu and childhood asthma. Methods: Studies of multiple databases were searched from inception to 2024. We recorded the standardized mean difference (SMD), 95% confidence intervals (CIs), and other data. The analysis was performed using Stata 18.0 software. Two independent reviewers appraised methodological quality using the Newcastle–Ottawa Scale. Sensitivity analysis was used to test robustness. To evaluate publication bias, we used Begg’s funnel plots and Egger’s regression test. Results: A total of 11 studies with a combined 1006 participants were included. There was no significant difference in the level of serum Cu between children with asthma cases and controls (SMD = −0.032, 95% CI: −0.291–0.228, P = 0.811). There was significant heterogeneity among the studies (I2 = 73.5%, P < 0.0001). Subgroup analysis demonstrated that heterogeneity was not caused by the continent of origin, publication year, sample size, detection methods, and the mean age of participants. No publication bias was found. Conclusion: There is no statistically significant association between serum Cu levels and childhood asthma. Further research, particularly large-scale prospective cohort studies, is needed to clarify this relationship.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.730
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0150.003
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.033
GPT teacher head0.334
Teacher spread0.301 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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