24 SGLT-2I therapy in heart failure : challenges and opportunities
Notice bibliographique
Résumé
Introduction Heart failure (HF) is a complex disease which is growing to be a significant cause of morbidity and mortality leading to increased cost of chronic care and hospitalization. In the DAPA-HF study, the sodium-glucose co-transporter 2 inhibitor (SGLT-2i) dapagliflozin was shown to reduce the risk of worsening HF and death in patients with HF with reduced ejection fraction (HFrEF). Our goal was to conduct an audit in a tertiary referral centre at University Hospital Galway (UHG) to identify patients with HFrEF who fulfil the eligibility criteria for SGLT-2i therapy, as seen in the DAPA-HF study. We also sought to identify patients with Type 2 Diabetes Mellitus (T2DM) in our HFrEF cohort who are potential candidates for improvement of glycaemic control with SGLT-2i therapy according to the ADA-EASD Guidelines. Methodology A retrospective audit was conducted on 129 patients with HFrEF attending the specialist-led heart failure clinic at UHG between January and March 2020. Demographic, clinical, biochemical and medication data were collected from medical charts and our local digital database:EVOLVE® and CVWeb®. Patients had to meet the DAPA-HF inclusion criteria to be deemed eligible for dapagliflozin therapy. Results Table 1 summarises the baseline clinical data and table 2 summarises the list of medical therapy at our centre. Of note, the 129 patients in our study represented a more elderly cohort compared to the DAPA-HF study population. Only 49/129 (38%) of our HFrEF patients were eligible for SGLT-2i therapy based on the DAPA-HF inclusion criteria. This is primarily due to the higher than expected percentage of patients in our cohort who were asymptomatic (34.9%) and who had low NT-proBNP levels (29.6%). 16/129 (12.4%) had severe CKD with an eGFR <30 ml/min/1.73 m2. There were only 26/129 (20.2%) patients with T2DM of which 6 patients were already on SGLT-2i. The majority had ischemic cardiomyopathy (69%) with concomitant risk factors and (30.8%) had poor glycaemic control. Conclusion This study shows a lower than expected number of patients in our centre who would have been included in the DAPA-HF trial. This could be because many patients in this cohort were already on optimal HF treatment, many being asymptomatic and had low NT-proBNP levels. Some patients were also ineligible for SGLT-2i because of Stage 4 CKD. One-third of the diabetic patients in this HFrEF cohort were not at target HbA1C range and according to the ADA-EASD Guidelines, all these patients should have SGLT-2i added to intensify glycaemic control. Lately, the Canadian Heart Society have updated their guidelines with a strong recommendation to introduce SGLT-2i in diabetics with ischemic cardiomyopathy despite adequate glycaemic control for cardiovascular benefits. SGLT-2i represents an important, but underutilized therapeutic option by cardiologists, likely due to the lack of familiarity on its use. This study reveals that SGLT-2i prescription could potentially increase in HFrEF patients with or without T2DM as guidelines will soon be updated based on robust evidence from large-scale clinical trials and when prescribers become aware of the indication for primary prevention of heart failure hospitalization and death.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,014 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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 source (Gemma direct ou Codex distillé), 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 ».