Notice bibliographique
Résumé
It has been my pleasure to serve as President of the American Society for Preventive Cardiology (ASPC) over the past 2 years. During my tenure, we have revitalized our Society and strengthened our relationship with our journal, Preventive Cardiology. In November 2009 we held a joint symposium with the National Lipid Association prior to the American Heart Association’s Annual Meeting in Orlando, Florida. This symposium on “Overcoming Challenges in Cardiovascular Disease (CVD) Prevention: A Focus on the Cardiometabolic Risk Continuum,” enabled our Society to contribute our own special expertise to the proceedings, while strengthening our relationship with a partner society. My section, on treatment of hypertension based on global risk, was directly targeted at a key element of prevention and an example of how we convey our insights to the broader medical community. On March 5, 2010, we again reached out to partner organizations by participating in the Joint Conference–50th Cardiovascular Disease Epidemiology and Prevention and Nutrition, Physical Activity and Metabolism 2010, in San Francisco, California. We conducted a session on what has become a tradition for the ASPC, a debate on prevention guidelines that illustrated the range of opinion and depth of approach embraced by our field. We will continue to team up and partner with organizations that share our goals and mission and strengthen our Society while we enhance our branch of medicine. Note that there is an application for membership in the ASPC included in this journal and we invite you to apply for membership. We are looking forward to an active year in 2010, as health care is on the national agenda and prevention is in the spotlight and central to improving care and reducing costs and burden. By now our lawmakers are familiar with the grim statistics: over a third of adult Americans will experience coronary heart disease in their lifetimes. Whether the condition is angina pectoris, myocardial infarction, or coronary disease death, predicting the onset and occurrence of these events is critical in our clinical decision making. Going forward, practitioners should be thoroughly familiar with traditional approaches, as the multivariable prediction model developed by the Framingham investigators has been extensively validated with cohort studies and captures a range of factors, including age, sex, cholesterol level, and smoking status. Increasingly, we are seeing practitioners test the limits of our science. Physicians and other health care professionals are examining alternative measures of coronary heart disease and surrogate markers that may help to predict clinical events and guide preventive care in cardiology. Our task is to add to the body of knowledge and help researchers and clinicians alike gain greater insight into the process and theory of risk estimation. By gauging additional variables in models that include traditional risk assessment criteria, the statistical significance of alternate approaches may be clarified as to their predictive value. While there is room for improvement, our current standards for coronary heart disease risk assessment are proven to be relatively accurate. The value of new factors for assessment should be judged also for their applicability; traditional approaches are by now well understood and familiar to both clinicians and patients, and recommendations for medical therapy and lifestyle modification are practical and low in cost. Thus, while caution is warranted, we can also be cautiously optimistic that new developments now emerging from studies in omega 3 fatty acids and high-density lipoprotein cholesterol therapeutics will change and improve the landscape for diagnosis and prevention.
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 | 0,000 |
| 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 ».