Symptoms and ASCVD score fail to identify majority of the patients at risk of first myocardial infarction
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».