Haemoglobin trajectories in chronic kidney disease and risk of major adverse cardiovascular events
Author:
Le Gall Lisa12, Harambat Jérôme123, Combe Christian45ORCID, Philipps Viviane1, Proust-Lima Cécile1, Dussartre Maris1, Drüeke Tilman6, Choukroun Gabriel78, Fouque Denis910, Frimat Luc1112, Jacquelinet Christian613, Laville Maurice10, Liabeuf Sophie814ORCID, Pecoits-Filho Roberto1516, Massy Ziad A617ORCID, Stengel Bénédicte6, Alencar de Pinho Natalia6ORCID, Leffondré Karen12, Prezelin-Reydit Mathilde1218ORCID, De Pinho Natalia Alencar, Combe Christian, Fouque Denis, Frimat Luc, Hamroun Aghilès, Jacquelinet Christian, Laville Maurice, Liabeuf Sophie, Massy Ziad A, Pascal Christophe, Pecoits-Filho Roberto, Stengel Bénédicte, Lange Céline, Lambert Oriane, Metzger Marie, Hannedouche T, Moulin B, Klein A, Combe C, Bourdenx J P, Keller A, Delclaux C, Vendrely B, Deroure B, Lacraz A, Lobbedez T, Landru I, Massy Z, Lang P, Belenfant X, Thervet E, Urena P, Delahousse M, Vela C, Essig M, Clément D, Sekhri H, Smati M, Jamali M, Hacq B, Panescu V, Bellou M, Frimat Luc, Kamar N, Noël C, Glowacki F, Maisonneuve N, Azar R, Hoffmann M, Hourmant M, Testa A, Besnier D, Choukroun G, Lambrey G, Burtey S, Lebrun G, Magnant E, Laville M, Fouque D, Juillard L, Chazot C, Zaoui P, Kuentz F,
Affiliation:
1. University Bordeaux, INSERM, Bordeaux Population Health , UMR1219, Bordeaux , France 2. University Bordeaux, INSERM , CIC-1401-EC, Bordeaux , France 3. Bordeaux University Hospital, Pediatric Nephrology Unit, Centre de Référence des Maladies Rénales Rares Sorare, Pellegrin-Enfants Hospital , Bordeaux , France 4. Bordeaux University Hospital, Department of Nephrology , transplantation, dialysis, Bordeaux , France 5. University Bordeaux , INSERM U1026, Bordeaux , France 6. Centre for research in Epidemiology and Population Health (CESP), Paris-Saclay University, Versailles Saint-Quentin University, Inserm U1018 Clinical Epidemiology Team , Villejuif , France 7. Amiens Picardie University Hospital, Department of Nephrology Dialysis Transplantation , Amiens , France 8. University of Picardie Jules Verne, MP3CV Research Unit , Amiens , France 9. Hopital Lyon Sud, Département de néphrologie , Lyon , France 10. Université Claude Bernard Lyon 1 , Carmen INSERM U1060, Pierre-Bénite , France 11. CHRU de Nancy, Department of Nephrology , Vandoeuvre-lès-Nancy , France 12. Lorraine University, APEMAC , Nancy , France 13. Agence de la biomedecine, La Plaine-Saint-Denis , France 14. Amiens-Picardie University Medical Center, Pharmacoepidemiology Unit, Department of Clinical Pharmacology , Amiens , France 15. DOPPS Program Area, Arbor Research Collaborative for Health , Ann Arbor, MI , USA 16. School of Medicine, Pontificia Universidade Catolica do Parana , Cutitiba, PR , Brazil 17. Ambroise Paré University Hospital, APHP, Department of Nephrology , Boulogne-Billancourt/Paris , France 18. Maison du REIN AURAD Aquitaine, Néphrologie , Gradignan, Nouvelle-Aquitaine , FR
Abstract
ABSTRACT
Background
The trajectories of haemoglobin in patients with chronic kidney disease (CKD) have been poorly described. In such patients, we aimed to identify typical haemoglobin trajectory profiles and estimate their risks of major adverse cardiovascular events (MACE).
Methods
We used 5-year longitudinal data from the CKD-REIN cohort patients with moderate to severe CKD enrolled from 40 nationally representative nephrology clinics in France. A joint latent class model was used to estimate, in different classes of haemoglobin trajectory, the competing risks of (i) MACE + defined as the first event among cardiovascular death, non-fatal myocardial infarction, stroke or hospitalization for acute heart failure, (ii) initiation of kidney replacement therapy (KRT) and (iii) non-cardiovascular death.
Results
During the follow-up, we gathered 33 874 haemoglobin measurements from 3011 subjects (median, 10 per patient). We identified five distinct haemoglobin trajectory profiles. The predominant profile (n = 1885, 62.6%) showed an overall stable trajectory and low risks of events. The four other profiles had nonlinear declining trajectories: early strong decline (n = 257, 8.5%), late strong decline (n = 75, 2.5%), early moderate decline (n = 356, 11.8%) and late moderate decline (n = 438, 14.6%). The four profiles had different risks of MACE, while the risks of KRT and non-cardiovascular death consistently increased from the haemoglobin decline.
Conclusion
In this study, we observed that two-thirds of patients had a stable haemoglobin trajectory and low risks of adverse events. The other third had a nonlinear trajectory declining at different rates, with increased risks of events. Better attention should be paid to dynamic changes of haemoglobin in CKD.
Funder
Agence Nationale de la Recherche
Publisher
Oxford University Press (OUP)
Subject
Transplantation,Nephrology
Cited by
1 articles.
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