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Association of SGLT2 Inhibitors With Cardiovascular and Kidney Outcomes in Patients With Type 2 Diabetes

2020· review· en· 1 212 citations· W3092379111 sur OpenAlex· 10.1001/jamacardio.2020.4511

Pourquoi ce travail est-il dans la base ?

Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.

Affiliation canadienneUne personne signataire a déclaré un établissement canadien. C'est la seule voie dont dispose la base habituelle.

Prédiction distillée sur la base complète

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.

Catégories candidates
aucune
Catégories consensuelles
aucune
Domaine
Signal candidat: aucuneSignal consensuel: aucune
Devis d'étude
Signal candidat: Sans objetSignal consensuel: aucune
Genre
Signal candidat: SynthèseSignal consensuel: Synthèse
Score de désaccord entre enseignants
0,901
Score d'incertitude au seuil
0,788
Statut de validation
machine_predicted_unvalidated · codex-gemma-dda1882f352a

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0030,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

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.

Tête enseignante Opus0,009
Tête enseignante GPT0,229
Écart entre enseignants
0,221 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validation
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 découle

Résumé

Importance: Sodium-glucose cotransporter 2 (SGLT2) inhibitors favorably affect cardiovascular (CV) and kidney outcomes; however, the consistency of outcomes across the class remains uncertain. Objective: To perform meta-analyses that assess the CV and kidney outcomes of all 4 available SGLT2 inhibitors in patients with type 2 diabetes. Data Sources: A systematic literature search was conducted in PubMed from January 1, 2015, to January 31, 2020. Study Selection: One hundred forty-five records were initially identified; 137 were excluded because of study design or topic of interest. As a result, a total of 6 randomized, placebo-controlled CV and kidney outcomes trials of SGLT2 inhibitors in patients with type 2 diabetes were identified, with contributory data from 9 publications. All analyses were conducted on the total patient population of these trials. Data Extraction and Synthesis: Standardized data search and abstraction were performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) Statement. Data were analyzed using a fixed-effect model. Main Outcomes and Measures: Outcomes included time to the first event of (1) the composite of major adverse CV events of myocardial infarction, stroke, or CV death, and each component, (2) the composite of hospitalization for heart failure (HHF) or CV death (HHF/CV death) and each component, and (3) kidney composite outcomes. For outcomes in the overall trial populations and in selected subgroups, hazard ratios (HRs) and 95% CIs were pooled and meta-analyzed across trials. Results: Data from 6 trials comprised 46 969 unique patients with type 2 diabetes, including 31 116 (66.2%) with atherosclerotic CV disease. The mean (SD) age of all trial participants was 63.7 (7.9) years; 30 939 (65.9%) were men, and 36 849 (78.5%) were White. The median number of participants per trial was 8246 (range, 4401-17 160). Overall, SGLT2 inhibitors were associated with a reduced risk of major adverse CV events (HR, 0.90; 95% CI, 0.85-0.95; Q statistic, P = .27), HHF/CV death (HR, 0.78; 95% CI, 0.73-0.84; Q statistic, P = .09), and kidney outcomes (HR, 0.62; 95% CI, 0.56-0.70; Q statistic, P = .09), with no significant heterogeneity of associations with outcome. Associated risk reduction for HHF was consistent across the trials (HR, 0.68; 95% CI, 0.61-0.76; I2 = 0.0%), whereas significant heterogeneity of associations with outcome was observed for CV death (HR, 0.85; 95% CI, 0.78-0.93; Q statistic, P = .02; I2 = 64.3%). The presence or absence of atherosclerotic CV disease did not modify the association with outcomes for major adverse CV events (HR, 0.89; 95% CI, 0.84-0.95 and HR, 0.94; 95% CI, 0.83-1.07, respectively; P = .63 for interaction), with similar absence of associations with outcome modification by prevalent atherosclerotic CV disease for HHF/CV death (P = .62 for interaction), HHF (P = .26 for interaction), or kidney outcomes (P = .73 for interaction). Conclusions and Relevance: In this meta-analysis, SGLT2 inhibitors were associated with a reduced risk of major adverse CV events; in addition, results suggest significant heterogeneity in associations with CV death. The largest benefit across the class was for an associated reduction in risk for HHF and kidney outcomes, with benefits for HHF risk being the most consistent observation across the trials.

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.

La notice

Revue
JAMA Cardiology
Thématique
Diabetes Treatment and Management
Domaine
Medicine
Établissements canadiens
University Health NetworkUniversity of Toronto
Organismes subventionnaires
VetenskapsrådetNovo NordiskSanofiGlaxoSmithKlinePfizerAstraZenecaEli Lilly and CompanyBristol-Myers Squibb
Mots-clés
MedicineType 2 diabetesHazard ratioInternal medicineKidney diseasePopulationDiabetes mellitusStroke (engine)Meta-analysisRandomized controlled trialMyocardial infarctionIntensive care medicineConfidence intervalEndocrinology
Résumé présent dans OpenAlex
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