Diagnosing and treating stable angina. a contemporary approach for practicing physicians
Notice bibliographique
Résumé
Longer life expectancy and advancements in coronary artery disease management have improved life expectancy and survival, increasing the prevalence of chronic coronary syndromes (CCS). Angina is a common symptom in patients with CCS but remains underdiagnosed and undertreated. Contemporary guidelines provide detailed information on diagnosing and treating angina based on evidence and expert consensus; however, their extensive nature may hinder uptake by non-specialists. This review presents a practical approach to diagnosing stable angina, followed by the three pillars of CCS management: 1) healthy lifestyle including appropriate exercise, diet, and avoiding toxic habits; 2) optimal medical therapy, including treatment recommended to prevent cardiovascular events and drugs for the control of myocardial ischemia and angina tailored to the patient’s comorbidities; and 3) myocardial revascularization when indicated. This approach may be useful for practicing physicians but is not intended to substitute more detailed and authoritative documents. Checklists are proposed to help focus patient–physician interactions and make follow-up visits more efficient. This approach seeks to increase the proportion of correct angina diagnoses and patients receiving evidence-based treatments, emphasizing the importance of patient education, managing residual angina, and reducing cardiovascular risk. We include reference to the recently published 2024 ESC guidelines on chronic coronary syndromes. Advances in the diagnosis and treatment of coronary heart diseases have greatly increased survival after a heart attack and increased life expectancy. As a result, an increasing number of people are living with chronic heart diseases that impair blood flow to the heart muscle, causing chest pain (angina). This can limit one’s quality of life and capacity to perform daily functions without pain. There are several underlying causes of angina, and it also occurs in people who have not had a heart attack. Management should address three important areas: (i) Lifestyle changes should include regular exercise, a heart-healthy diet, and avoidance of smoking, while keeping blood pressure, serum cholesterol levels, and other so-called risk factors under control to prevent future cardiovascular events. (ii) Anti-angina medications (antianginal drugs) should be personalized based on the underlying cause of a patient’s angina, their cardiovascular characteristics, the presence of other medical conditions and the medications that they are currently taking. The physician may need to adjust this tailored treatment to achieve optimal results for the individual patient. (iii) If this optimal medical therapy does not provide sustained relief, the physician may refer the patient to a cardiology center for further testing and to evaluate whether a revascularization procedure would be appropriate. Administering the optimal antianginal treatment for each patient, and careful adherence to lifestyle recommendations provide the best chance for restoring quality of life, reducing medical visits and improving long-term outcomes.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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 tête enseignante, 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 ».