Socioeconomic position and incidence of acute myocardial infarction: a meta-analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: A negative socioeconomic gradient is established for coronary heart disease (CHD) mortality and survival, while socioeconomic patterning of disease incidence is less well investigated. To study socioeconomic inequalities in the incidence of acute myocardial infarction (AMI), the major component of CHD, a meta-analysis was undertaken to summarise existing evidence on the issue. METHODS: A systematic search was performed in PubMed and EMBASE databases for observational studies on AMI incidence and socioeconomic position (SEP), published in English to April 2009. A random-effects model was used to pool the risks estimates from the individual studies. RESULTS: Among 1181 references, 70 studies fulfilled the inclusion criteria. An overall increased risk of AMI among the lowest SEP was found for all three indicators: income (pooled RR 1.71, 95% CI 1.43 to 2.05), occupation (pooled RR 1.35, 95% CI 1.19 to 1.53) and education (pooled RR 1.34, 95% CI 1.22 to 1.47). The strongest associations were seen in high-income countries such as USA/Canada and Europe, while the results were inconsistent for middle and low-income regions. CONCLUSION: AMI incidence is associated with low SEP. The nature of social stratification at the level of economic development of a country could be involved in the differences of risk of AMI between social groups.
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.
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 | 0.046 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.004 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it