A global perspective on cardiovascular risk factor management in patients with CHD and different educational level: SURF CHD II
Notice bibliographique
Résumé
Abstract Background Clinical guidelines recommend that patients with established coronary heart disease (CHD) change health behaviors and use medication to control risk factors (RF), eventually reducing cardiovascular risk. Nevertheless, RF management in daily practice is challenging and RF control in secondary prevention remains suboptimal. Patients with low educational level tend to have higher cardiovascular risk. This association varies indifferent contexts, yet research on health inequalities in secondary prevention has focused mostly on high-income countries. Purpose To provide a global picture of health inequalities in RF management in secondary prevention of CHD, by assessing RF recording, target attainment, and treatment by educational level in patients from four world regions. Methods The Survey of Risk Factors in Coronary Heart Disease (SURF CHD) II is a clinical audit on RF management, undertaken in patients with CHD during routine outpatient visits. The survey is easy to perform, allowing its use in low-resource centers. We studied RF recording (data availability), attainment of targets defined by guidelines, and treatment (medication and cardiac rehabilitation). RF included smoking, physical activity, waist circumference, blood pressure, LDL, non-HDL cholesterol, triglycerides, and Hba1c (among diabetics). We reported the % of recording, target attainment and treatment in patients with primary/secondary schooling and in those with tertiary education. We assessed differences in RF management by educational level with logistic regression adjusted by age and sex, and stratified by region. Results 13884 patients were enrolled in 29 countries in Europe (N=10255), South-East Asia (SEA) (N=2290), the Americas (N=779) and North Africa and Eastern Mediterranean (N=560). 47.0% of participants had tertiary education, 34.5% had secondary schooling, and 18.6% primary schooling. RF recording ranged from 22.2% (waist circumference) to 93.0% (blood pressure); target attainment from 15.9% (waist circumference) to 76.9% (smoking). 50.5% participated in cardiac rehabilitation. RF information was collected more often in highly educated patients for most RF in the Americas, and for blood pressure and HBa1c in SEA. BMI and waist circumference were more frequently registered among lower-educated participants in Europe and SEA. Highly educated patients were more likely to meet RF targets for smoking in most regions, physical activity in Americas and Europe, LDL in SEA, and Non-HDL cholesterol and Hba1c in SEA and Americas regions. Patients with higher education participated more often in cardiac rehabilitation in all regions except SEA (Figure 1). Conclusions Health inequalities persist in secondary prevention of CHD: highly educated patients are generally more likely to have RF information recorded, have RF levels on target and attend cardiac rehabilitation. However, these associations present specific patterns by RF and region.
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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 | 0,001 | 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 ».