SUN-LB015 Baseline Characteristics and Effects on CV and Kidney Outcomes with Linagliptin Versus Placebo, Across GFR Categories in CARMELINA
Notice bibliographique
Résumé
People with type 2 diabetes (T2D) with concomitant chronic kidney disease (CKD) and cardiovascular (CV) disease are at increased risk for recurrent CV events and hypoglycemia. Treatment of these individuals is clinically challenging, where the evidence-base for safety and efficacy of glucose lowering drugs is scarce, in particular in GFR categories G3b (eGFR 30-44 ml/min/1.73m(2)), G4 (eGFR < 30) and G5 (eGFR < 15). We analyzed baseline characteristics and effects on CV and kidney outcomes with the DPP-4 inhibitor linagliptin (LINA) vs. placebo (PBO), across GFR categories in CARMELINA (NCT01897532). People with T2D and either i) UACR >30 mg/g with concomitant CV disease, or ii) eGFR <45 ml/min/1.73m² regardless of UACR, or eGFR ≥45 - 75mL/min/1.73m² and UACR > 200 mg/g, were randomized to LINA 5 mg or placebo (PBO) q.d. in a double-blind fashion. The primary outcome was first occurrence of CV death, non-fatal myocardial infarction, or non-fatal stroke (3P-MACE), with an adjudicated secondary composite outcome of ESKD, renal death, or sustained ≥40% decrease in eGFR from baseline. Other adjudicated outcomes included hospitalized heart failure (hHF) and the 3P-MACE components. Subgroup-effects across GFR categories (G≤2, G3a, G3b and G≥4) were also assessed. Of the 6979 participants, 15.2% were in GFR category G≥4, 27.8% G3b, 19.3% G3a, and 37.7% G≤2 at baseline. Participants in G≥4 (mean±SD eGFR 23.4±4.2 mL/min/1.73m²) or G3b (eGFR 37.2±4.1) as compared with G3a (eGFR 51.4±4.4) and G≤2 (eGFR 81.6±16.7) had more albuminuria, longer T2D duration and were more frequently treated with insulin, but less often with sulfonylureas and metformin. Over a median 2.2 years, LINA did not affect the risk for 3P-MACE (HR.1.02 [95% CI, 0.89, 1.17]), the secondary kidney composite outcome (1.04 [0.89, 1.22]), hHF (0.90 [0.74, 1.08]), or CV mortality (0.96 [0.81, 1.14]). Incidences were higher by declining kidney function, e.g. the 3P-MACE PBO incidence rate was 2.4 fold higher in G≥4 (9.6 per 100 patient-yrs) relative to G≤2 (4.0 per 100-patient yrs), whereas the kidney composite 9.8 fold (14.7 vs 1.5 per 100 patient-yrs), hHF 4.1 fold (6.2 vs 1.5 per patient-yrs) and CV death 3.0 fold (6.8 vs 2.3 per 100 patient-yrs) higher, respectively. A consistent neutral effect was observed across all GFR categories (interaction p-values: 0.84 [3P-MACE], 0.36 [kidney composite], 0.88 [hHF], 0.23 [CV mortality]). Adverse events (AE) increased with declining kidney function, but the proportion with ≥1 AE, or ≥1 serious AE were balanced between LINA and PBO across the GFR categories. HbA1c was reduced significantly, but without increased risk for hypoglycemia with LINA vs PBO, across all GFR categories. These findings in a large, international CV outcome trial in patients with T2D and concomitant CV and renal disease support the safety and tolerability of LINA as a T2D therapy that can be used across a broad range of kidney disease. Unless otherwise noted, all abstracts presented at ENDO are embargoed until the date and time of presentation. For oral presentations, the abstracts are embargoed until the session begins. Abstracts presented at a news conference are embargoed until the date and time of the news conference. The Endocrine Society reserves the right to lift the embargo on specific abstracts that are selected for promotion prior to or during ENDO.
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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,003 | 0,003 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 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 ».