Understanding Physicians' Risk Stratification of Acute Coronary Syndromes
Notice bibliographique
Résumé
BACKGROUND: An important treatment-risk paradox exists in the management of acute coronary syndromes (ACSs). However, the process of risk stratification by physicians and its relationship to the management of ACS have not been well studied. Our objective was to examine patient risk assessment by physicians in relation to treatment and objective risk score evaluation and the underlying patient characteristics that physicians consider to indicate high risk. METHODS: The prospective Canadian ACS 2 Registry recruited 1956 patients admitted for non-ST-segment elevation ACS in 36 hospitals in October 2002 to December 2003. We recorded patient risk assessment by the treating physician and case management on standardized case report forms and calculated the Thrombolysis in Myocardial Infarction (TIMI), Platelet glycoprotein IIb/IIIa in Unstable angina: Receptor Suppression Using Integrilin Therapy (PURSUIT), and Global Registry of Acute Cardiac Events (GRACE) risk scores. RESULTS: Of the 1956 patients with ACS, 347 (17.8%) were classified as low risk, 822 (42.0%) as intermediate risk, and 787 (40.2%) as high risk by their treating physicians. Patients considered as high risk were more likely to receive aggressive medical therapies and to undergo coronary angiography and revascularization. However, there were only weak correlations between risk assessment by physicians and all 3 validated risk scores. In multivariable analysis, history of stroke, worse Killip class, presence of ST-segment deviation, T-wave inversion, and positive cardiac biomarker status were all independently associated with high-risk categorization by the treating physician, while advanced age and previous coronary bypass surgery were independent negative predictors. There was no significant association between the high-risk category and several established prognosticators, such as history of heart failure, hemodynamic variables, and creatinine level. CONCLUSIONS: Contemporary risk stratification of ACS appears suboptimal and may perpetuate the treatment-risk paradox. Physicians may not recognize and incorporate the most powerful adverse prognosticators into overall patient risk assessment. Routine use of validated risk score may enhance risk stratification and facilitate more appropriate tailoring of intensive therapies toward high-risk patients.
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) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| 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 ».