Acute Coronary Care in the Elderly, Part I
Notice bibliographique
Résumé
BACKGROUND: Age is an important determinant of outcomes for patients with acute coronary syndromes (ACS); however, community practice reveals a disproportionately lower use of cardiovascular medications and invasive treatment even among elderly patients with ACS who would stand to benefit. Reasons include limited trial data to guide the care of older adults and uncertainty about benefits and risks, particularly with newer medications or invasive treatments and in the setting of advanced age or complex health status. METHODS AND RESULTS: This 2-part American Heart Association scientific statement summarizes evidence on patient heterogeneity, clinical presentation, and treatment of non-ST-elevation ACS in relation to age (< 65, 65 to 74, 75 to 84, and > or = 85 years). In addition, we review methodological issues that influence the acquisition and application of evidence to the elderly patients treated in community practice. A writing group combining international cardiovascular and geriatric perspectives convened to summarize available data from trials (5 combined Virtual Coordinating Center for Global Collaborative Cardiovascular Research [VIGOUR] trials) and 3 registries (Global Registry of Acute Coronary Events, National Registry of Myocardial Infarction, and the Can Rapid risk stratification of Unstable angina patients Suppress ADverse outcomes with Early implementation of the American College of Cardiology/American Heart Association guidelines national quality improvement initiative [CRUSADE]) to provide a conceptual framework for future work in the care of the elderly with acute cardiac disease. Treatment for non-ST-segment-elevation ACS (Part I) and ST-segment-elevation myocardial infarction (Part II) are reviewed. In addition, ethical considerations pertaining to acute care and secondary prevention are considered (Part II). The primary goal is to identify the areas in which sufficient evidence is available to guide practice, as well as to determine areas that warrant further study. Although treatment-related benefits should rise in an elderly population with high disease risk, data to assess these benefits are limited, outcomes of importance vary, and heterogeneity among the elderly increases treatment-related risks. Although a uniform approach to care in the oldest of the old is unlikely, understanding the major contributors to benefits and risks from treatment will advance the ability to apply guideline-based care in this subset of patients. CONCLUSIONS: Although a few recent trials have described treatment effects in older patients, others continue to exclude patients on the basis of age. Going forward, prospective trials should enroll elderly subjects proportionate to their prevalence among the treated population to define risk and benefit. Findings from age subgroup analyses should be reported in a consistent manner across trials, including absolute and relative risks for efficacy and safety. Outcomes of particular relevance to the elderly, such as quality of life, physical function, and independence, should also be considered. Creatinine clearance should be calculated for every elderly patient to enable appropriate dosing. In addition, physicians need an understanding of conditions unique to older patients (eg, frailty, cognitive impairment) that influence treatment goals and outcomes. With these efforts, treatment risks can be minimized, and benefits can be placed in the health context of the elderly patient with ACS.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,005 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».