Abstract

Abstract Background and Aims Anemia in chronic kidney disease (CKD) has been repeatedly associated with increased cardiovascular and all-cause morbidity and mortality. Most observational studies have focused on one single measurement of hemoglobin, but very few have investigated the trajectory of hemoglobin over time. Our aim was to identify, in moderate to severe CKD, typical profiles of hemoglobin trajectories, and to estimate their associated risk of major adverse cardiovascular event (MACE). Method We used data from the CKD-REIN cohort, which included 3033 patients with moderate to severe CKD from 40 nationally representative nephrology clinics in France between 2013 and 2016. A minimum of one hemoglobin measurement was necessary to be included. The primary endpoint was MACE defined as the first event among cardio-vascular death, myocardial infarction, stroke or hospitalization for acute heart failure. Secondary events included initiation of kidney replacement therapy (KRT) and death. A joint latent class mixed model was used to identify classes of hemoglobin trajectory and estimate the risk of each event. Once the model had identified classes and assigned participants in their class, we described the characteristics of patients in each class a posteriori. We also performed a posterior analysis to describe the course of estimated glomerular filtration rate (eGFR) in each class. Results A total of 3011 subjects were included in the analysis: 66% were men, median age at inclusion was 69 years. A total of 33874 hemoglobin measurements have been analyzed (median of 10 per patient). A total of 460 MACE, 522 KRT before MACE and 216 deaths before MACE or KRT, were recorded over a median follow-up of 4.3 years (Interquartile Range IQR 2.3-5.0). Five distinct classes were identified with a predominant one, Class-1 (‘constant’) including 63% (n = 1885) of the studied population with an overall stable trajectory surrounding a hemoglobin concentration of 13 g/dL (See figure below). For this class, risks of events were very low throughout the follow-up. Patients in this class had fewer cardiovascular risk factors, lower eGFR, and less often increased proteinuria at baseline than in other classes. Class-2 trajectory (‘late strong decline’, n = 75, 2.5%) had an abrupt decline at 2 years of follow-up; concomitantly risks of KRT and death before MACE emerged but the risk of MACE remained low over the follow-up. Patients classified in this class had more often tubulo-interstitial or unknown nephropathy than in other classes. Classes 3 ‘(late moderate decline, n = 438, 14.6%) and 4 (‘early moderate decline, n = 356, 11.8%) exhibited more moderate decline of hemoglobin level occurring on average at 3 and 1 year of follow-up, respectively. For these two classes, the risk of KRT before MACE increased from the start of these declines but their risks of MACE increased from the cohort entry. Class-5 (‘early strong decline’, n = 257, 8.5%) had a collapsing trajectory right from the entry into the cohort, and had a risk of MACE increasing rapidly in the very first year. Patients from Class-3 and Class-5, who had the highest risk of MACE, also had a worse cardiovascular profile at baseline. The average eGFR trajectories estimated in each of the 5 identified classes of hemoglobin showed similar patterns as those for hemoglobin. Conclusion In patients with CKD under nephrology care, most of patients have normal and stable hemoglobin values over time. In about one third of patients, 4 profiles of hemoglobin decline were observed, likely matching those of eGFR decline. These 4 classes with declining profiles had different levels of MACE risk and a strong increased risk of KRT after hemoglobin decline. This study suggests that more attention should be paid to dynamic changes of hemoglobin in the management of CKD.

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