Atopic eczema and major cardiovascular outcomes: A systematic review and meta-analysis of population-based studies
Bibliographic record
Abstract
BACKGROUND: Atopic eczema is a common inflammatory skin disease. Various inflammatory conditions have been linked to cardiovascular disease, a major cause of global mortality and morbidity. OBJECTIVE: We sought to systematically review and meta-analyze population-based studies assessing associations between atopic eczema and specific cardiovascular outcomes. METHODS: MEDLINE, Embase, and Global Health were searched from inception to December 2017. We obtained pooled estimates using random-effects meta-analyses. We used a multivariate Bayesian meta-regression model to estimate the slope of effect of increasing atopic eczema severity on cardiovascular outcomes. RESULTS: Nineteen relevant studies were included. The effects of atopic eczema reported in cross-sectional studies were heterogeneous, with no evidence for pooled associations with angina, myocardial infarction, heart failure, or stroke. In cohort studies atopic eczema was associated with increased risk of myocardial infarction (n = 4; relative risk [RR], 1.12; 95% CI, 1.00-1.25), stroke (n = 4; RR, 1.10; 95% CI, 1.03-1.17), ischemic stroke n = 4; RR, 1.17; 95% CI, 1.14-1.20), angina (n = 2; RR, 1.18; 95% CI, 1.13-1.24), and heart failure (n = 2; RR, 1.26; 95% CI, 1.05-1.51). Prediction intervals were wide for myocardial infarction and stroke. The risk of cardiovascular outcomes appeared to increase with increasing severity (mean RR increase between severity categories, 1.15; 95% credibility interval, 1.09-1.21; uncertainty interval, 1.04-1.28). CONCLUSION: Significant associations with cardiovascular outcomes were more common in cohort studies but with considerable between-study heterogeneity. Increasing atopic eczema severity was associated with increased risk of cardiovascular outcomes. Improved awareness among stakeholders regarding this small but significant association is warranted.
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 | 0.013 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.033 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".