Association Between Acute Myocardial Infarction Symptoms and Short- and Long-term Mortality After the Event
Bibliographic record
Abstract
BACKGROUND: In this study, we investigated various acute myocardial infarction (AMI) symptoms and their associations with short-term (28 day) and long-term mortality. METHODS: The analysis was based on 5900 patients, aged 25 to 84 years, with first-time AMI recorded by the population-based Myocardial Infarction Registry Augsburg between 2010 and 2017. Median follow-up time was 3.8 years (interquartile range: 1.1-6.3). As part of a face-to-face interview, the presence (yes/no) of 11 most common AMI symptoms at the acute event was assessed. Using multivariable-adjusted logistic regression and Cox regression models, the association between various symptoms and all-cause mortality was investigated. P values of the regression models were false discovery rate adjusted. RESULTS: Pain in various body parts (chest pain, left and right shoulder/arm/hand, between shoulder blades), sweating, nausea/vomiting, dizziness and fear of death/feeling of annihilation were significantly associated with a decreased 28-day mortality after AMI. The pain symptoms and sweating were also significantly associated with a decreased long-term mortality. Shortness of breath was significantly associated with a higher long-term mortality. CONCLUSIONS: The absence of several symptoms, including typical chest discomfort (chest pain or retrosternal pressure/tightness), is associated with unfavourable outcomes after AMI. This finding has implications for patient management and public health measures designed to encourage appropriate and prompt medical consultation of patients with atypical AMI symptoms.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".