Symptoms and ASCVD score fail to identify majority of the patients at risk of first myocardial infarction
Bibliographic record
Abstract
Abstract Background Cardiovascular disease screening has long relied on the presence of symptoms like chest pain or on the Atherosclerotic Cardiovascular Disease (ASCVD) risk score, which is typically initiated at age 40. However, current research suggests that the ASCVD risk score may not incorporate a comprehensive range of factors and should be started earlier. Furthermore, the absence of symptoms such as angina in some patients prior to acute coronary syndrome (ACS) casts doubt on the reliability of symptom-based screening methods. Purpose This study aimed to evaluate the effectiveness of the ASCVD risk score and chest pain as predictors for ACS. Methods We retrospectively analyzed the data of all patients of 65 or younger who presented with their first ACS event in a single US center from January 2020 to January 2024. We collected the demographic and clinical data, including age, sex, lipid panel, blood pressure, medical history, onset of symptoms, and calculated their individual ASCVD risk score. We explored whether these patients, if assessed one week before their ACS event, would have been identified as at risk and thus prescribed lipid lowering or recommended for further diagnostic tests. Results Among 166 patients presenting with ACS, 64 (39%) were considered low risk with an ASCVD risk score of <5 or too low to calculate. 20 (12%) patients were assessed as borderline risk with an estimated risk score of 5-7.5%. In the intermediate risk category, 20 patients (12%) had a score of 7.5% -10% and 42 patients (25%) were estimated to have a score of >10 to <20%. 14 patients (8%) fell in the high-risk category, and lastly 6 patients had an LDL that was above 190 mg/dl. Regarding symptoms of chest pain or shortness of breath, 14 patients (8%) did not experience any symptoms prior to their presentation, 98 (59%) patients experienced their first episode of symptoms within 48 hours, 19 patients (11%) within 2 days to a week, 10 patients (6%) had CP leading up to their event from a week to a month, 6 patients (4%) in the range of a month to 3 months and 19 patients (11%) had symptoms longer than 3 months prior to their presentation. To summarize if there were seen 1 week prior to their first ACS events, 51% of them were not recommended for statin therapy based on their ASCVD risk score and 67% of patients either had no chest pain until the event or chest pain within 48hrs of onset of their ACS and consequently would not have been routinely screened for coronary artery disease (CAD) by any anatomical or functional methods. Conclusion(s) ASCVD risk score and symptoms fail to identify majority of patient below 65 years of age with their first MI. Given high prevalence of CAD and associated mortality, improved screening tools, in addition to symptomatology or risk scores, would be more effective in identifying individuals at risk.
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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 | 0.007 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".