作者
Lisa Le Gall,Jérôme Harambat,Christian Combe,Viviane Philipps,Cécile Proust‐Lima,Maris Dussartre,Tilman B. Drüeke,Gabriel Choukroun,Denis Fouque,Luc Frimat,Christian Jacquelinet,Maurice Laville,Sophie Liabeuf,Roberto Pecoits‐Filho,Ziad A. Massy,Bénédicte Stengel,Natália Alencar de Pinho,Karen Leffondré,Mathilde Prézelin-Reydit,Natália Alencar de Pinho,Christian Combe,Denis Fouque,Luc Frimat,Aghilès Hamroun,Christian Jacquelinet,Maurice Laville,Ziad A. Massy,Ziad A. Massy,Christophe Pascal,Roberto Pecoits‐Filho,Céline Lange,Céline Lange,Oriane Lambert,Marie Essig,Thierry Hannedouche,Michel Delahousse,C Vela,Christian Combe,C Dubost,A. Keller,Mustafa Smati,Benoı̂t Vendrely,Benjamin Deroure,Adeline Lacraz,M Bellou,Isabelle Landru,Ziad A. Massy,Christian Noël,Xavier Belenfant,N. Maisonneuve,Raymond Azar,Michel Delahousse,C Vela,Marie Essig,C Dubost,H Sekhri,Mustafa Smati,Mohammad Jamali,B Hacq,Victor Panescu,M Bellou,Luc Frimat,Nassim Kamar,Charles Chazot,François Glowacki,N. Maisonneuve,Raymond Azar,Maxime Hoffmann,M Hourmant,Angelo Testa,Dominique Besnier,Gabriel Choukroun,G Lambrey,Stéphane Burtey,G. Lebrun,Éric Magnant,Maurice Laville,Denis Fouque,Laurent Juillard,Charles Chazot,Philippe Zaoui,F Kuentz
摘要
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.