Chest pain symptoms during myocardial infarction in patients with and without diabetes: a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: Chest pain (CP) is key in diagnosing myocardial infarction (MI). Patients with diabetes mellitus (DM) are at increased risk of an MI but may experience less CP, leading to delayed treatment and worse outcomes. We compared the prevalence of CP in those with and without DM who had an MI. METHODS: The study population was people with MI presenting to healthcare services. The outcome measure was the absence of CP during MI, comparing those with and without DM. Medline and Embase databases were searched to 18 October 2021, identifying 9272 records. After initial independent screening, 87 reports were assessed for eligibility against the inclusion criteria, quality and risk of bias assessment (Strengthening the Reporting of Observational Studies in Epidemiology and Newcastle-Ottawa criteria), leaving 22 studies. The meta-analysis followed Meta-analysis Of Observational Studies in Epidemiology criteria and reported according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Pooled ORs, weights and 95% CIs were calculated using a random-effects model. RESULTS: This meta-analysis included 232 519 participants from 22 studies and showed an increased likelihood of no CP during an MI for those with DM, compared with those without. This was 43% higher in patients with DM in the cohort and cross-sectional studies (OR: 1.43; 95% CI: 1.26 to 1.62), and 44% higher in case-control studies (OR: 1.44; 95% CI: 1.11 to 1.87). CONCLUSION: In patients with an MI, patients with DM are less likely than those without to have presentations with CP recorded. Clinicians should consider an MI diagnosis when patients with DM present with atypical symptoms and treatment protocols should reflect this, alongside an increased patient awareness on this issue. PROSPERO REGISTRATION NUMBER: CRD42017058223.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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; a candidate call from one teacher head, 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".