Serum Biomarkers of Iron Stores Are Associated with Increased Risk of All-Cause Mortality and Cardiovascular Events in Nondialysis CKD Patients, with or without Anemia
Notice bibliographique
Résumé
Significance Statement Management of iron deficiency in patients with nondialysis CKD focuses on improving erythropoiesis. Studies in patients with heart failure with similar iron deficiency pathogenesis found that treating iron deficiency improves cardiovascular outcomes, regardless of anemia. To evaluate a possible anemia-independent association of iron stores with outcomes in individuals with nondialysis CKD, the authors studied patients in nephrology-based clinics from a multinational cohort. They show that iron deficiency, as reflected by transferrin saturation index, is associated with higher risk of mortality and cardiovascular events in patients with CKD, with or without anemia. Intervention studies addressing the effects of treating iron deficiency beyond effects on erythropoiesis are necessary to challenge the current anemia-focused paradigm of iron deficiency management in nondialysis CKD, and potentially foster better strategies for improving patient outcomes. Background Approximately 30%–45% of patients with nondialysis CKD have iron deficiency. Iron therapy in CKD has focused primarily on supporting erythropoiesis. In patients with or without anemia, there has not been a comprehensive approach to estimating the association between serum biomarkers of iron stores, and mortality and cardiovascular event risks. Methods The study included 5145 patients from Brazil, France, the United States, and Germany enrolled in the Chronic Kidney Disease Outcomes and Practice Patterns Study, with first available transferrin saturation (TSAT) and ferritin levels as exposure variables. We used Cox models to estimate hazard ratios (HRs) for all-cause mortality and major adverse cardiovascular events (MACE), with progressive adjustment for potentially confounding variables. We also used linear spline models to further evaluate functional forms of the exposure-outcome associations. Results Compared with patients with a TSAT of 26%–35%, those with a TSAT ≤15% had the highest adjusted risks for all-cause mortality and MACE. Spline analysis found the lowest risk at TSAT 40% for all-cause mortality and MACE. Risk of all-cause mortality, but not MACE, was also elevated at TSAT ≥46%. Effect estimates were similar after adjustment for hemoglobin. For ferritin, no directional associations were apparent, except for elevated all-cause mortality at ferritin ≥300 ng/ml. Conclusions Iron deficiency, as captured by TSAT, is associated with higher risk of all-cause mortality and MACE in patients with nondialysis CKD, with or without anemia. Interventional studies evaluating the effect on clinical outcomes of iron supplementation and therapies for alternative targets are needed to better inform strategies for administering exogenous iron.
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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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| 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 ».