Increased Serum S100A12 Levels are Associated with Higher Risk of Acute Heart Failure in Patients with Type 2 Diabetes
Notice bibliographique
Résumé
AIMS: The hyperglycaemic stress induces the release of inflammatory proteins such as S100A12, one of the endogenous ligands of the receptors for advanced glycation end products (RAGE). Chronic activation of RAGE has multiple deleterious effects in target tissues such as the heart and the vessels by promoting oxidative stress, inflammation by the release of cytokines, macrophages infiltration, and vascular cell migration and proliferation, causing ultimately endothelial cell and cardiomyocyte dysfunction. The aim of our study was to investigate the prognostic value of circulating S100A12 beyond established cardiovascular risk factors (CVRF) for heart failure (HF) and major adverse cardiovascular events (MACE) in a cohort of patients with type 2 diabetes. METHODS AND RESULTS: Serum S100A12 concentrations were measured at baseline in 1345 type 2 diabetes patients (58% men, 64 ± 11 years) recruited in the SURDIAGENE prospective cohort. Endpoints were the occurrence of acute HF requiring hospitalization (HHF) and MACE. We used a proportional hazard model adjusted for established CVRF (age, sex, duration of diabetes, estimated glomerular filtration rate, albumin/creatinine ratio, history of coronary artery disease) and serum S100A12. During the median follow-up of 84 months, 210 (16%) and 505 (38%) patients developed HHF and MACE, respectively. Baseline serum S100A12 concentrations were associated with an increased risk of HHF [hazard ratio (HR) (95% confidence interval) 1.28 (1.01-1.62)], but not MACE [1.04 (0.90-1.20)]. After adjustment for CVRF, S100A12 concentrations remained significantly associated with an increased risk of HHF [1.29 (1.01-1.65)]. In a sub-analysis, patients with high probability of pre-existing HF [N terminal pro brain natriuretic peptide (NT-proBNP) >1000 pg/mL, n = 87] were excluded. In the remaining 1258 patients, the association of serum S100A12 with the risk of HHF tended to be more pronounced [1.39 (1.06-1.83)]. When including the gold standard HF marker NT-proBNP in the model, the prognostic value of S100A12 for HHF did not reach significance. Youden method performed at 7 years for HHF prediction yielded an optimal cut-off for S100A12 concentration of 49 ng/mL (sensitivity 53.3, specificity 52.2). Compared with those with S100A12 ≤ 49 ng/mL, patients with S100A12 > 49 ng/mL had a significantly increased risk of HHF in the univariate model [HR = 1.58 (1.19-2.09), P = 0.0015] but also in the multivariate model [HR = 1.63 (1.23-2.16), P = 0.0008]. After addition of NT-proBNP to the multivariate model, S100A12 > 49 ng/mL remained associated with an increased risk of HHF [HR = 1.42 (1.07-1.90), P = 0.0160]. However, the addition of S100A12 categories on top of multivariate model enriched by NT-pro BNP did not improve the ability of the model to predict HHF (relative integrated discrimination improvement = 1.9%, P = 0.1500). CONCLUSIONS: In patients with type 2 diabetes, increased serum S100A12 concentration is independently associated with risk of HHF, but not with risk of MACE. Compared with NT-proBNP, the potential clinical interest of S100A12 for the prediction of HF events remains limited. However, S100A12 could be a candidate for a multimarker approach for HF risk assessment in diabetic patients.
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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 | 0,000 | 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 ».