To improve the quality of secondary prevention strategies in diabetic patients: the BRING-UP Prevention study results
Notice bibliographique
Résumé
Abstract Background Cardiovascular disease (CVD) is the leading cause of morbidity and mortality in people with diabetes, making secondary prevention strategies critical to improving patient outcomes. The role of lipid-lowering therapy and blood pressure control is well established, but novel therapies such as SGLT-2 inhibitors and GLP-1 RA are also showing favourable results in reducing cardiovascular events. In addition, optimising glycaemic control and promoting lifestyle changes remain cornerstone strategies for reducing long-term CV risk. Purpose To try to narrow the gap between what is recommended and what is implemented in clinical practice in type 2 diabetic patients, we designed a national implementation science project, BRING-UP Prevention, based on educational programmes and patient data collection. Methods BRING-UP Prevention is a nationwide, observational, prospective, multicentre study enrolling patients with a documented prior atherothrombotic event in 2 enrolment phases preceded by an educational intervention to discuss guideline recommendations. Primary endpoint: Rate of patients achieving target LDL cholesterol. Secondary endpoints: rate of patients achieving target blood pressure (<130/80 mmHg) rate of diabetic patients achieving target HbA1c (<7%) rate of overweight patients (BMI >27 kg/m2) achieving at least 10% weight loss. The first phase has recently been completed. Results 189 cardiology centres collected data on 4790 patients, of whom 1317 (27.5%) had diabetes. Follow-up data were available for 1229/1317 patients (93.3%). The figure shows LDL cholesterol levels at baseline and after 6 months. The rate of diabetic patients with LDL cholesterol <55 mg/dL increased from 43.4% to 65.5% with treatment based on statins and ezetimibe in 65.8% of patients. PCSK9 inhibitors were used in 5.6% of patients. HbA1c, measured at follow-up in only 61.8% of patients, was <7% in only 46.7% of patients. Pts with blood pressure <130/80 mmHg were 36.5% at baseline and 42.5% at follow-up. The rate of pts doing light physical activity increased from 36.2% to 50.1%. At baseline, 46.1% of patients had a BMI >27, which decreased to 43.3% at follow-up. 11.3% of overweight patients lost more than 10% of their body weight during follow-up. The most commonly prescribed antidiabetic medications at both baseline and follow-up were metformin (51.1%), SGLT2 inhibitors (49.6%), insulin (27.1%), and GLP-1 RA (19.4%). Conclusions This study shows that it is possible to improve adherence to the guideline target for LDL cholesterol with cost-effective drugs. There seems to be a need for more intensive strategies to improve blood pressure, HbA1c levels and lifestyle changes.
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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 | 0,023 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| 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 | 0,001 |
| 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 ».