The anaemia control model: Does it help nephrologists in therapeutic decision-making in the management of anaemia?

Abstract

Introduction: Anaemia is common in haemodialysis patients and treating it with erythropoiesis-stimulating agents (ESAs) is complex due to many factors.

Objectives: To assess the usefulness of the Anaemia Control Model (ACM) in the treatment of anaemia in haemodialysis.

Methods: ACM is a software that predicts the optimal dose of darbepoetin and iron sucrose to achieve target haemoglobin (Hb) and ferritin levels, and makes prescription suggestions. Study conducted in dialysis clinics lasting 18months with two intervention phases (IPs) with ACM (IP1, n:213; IP2, n:218) separated by a control phase (CP, n:219). The primary outcome was the percentage of Hb in range and the median dose of ESAs, and the secondary outcomes were transfusion, hospitalisation and cardiovascular events. Clinical and patient analyses were performed. Hb variability was assessed by the standard deviation (SD) of the Hb. We also analysed the patients with most of the suggestions confirmed (ACM compliant group).

Results: ACM increased the percentage of Hb in range: 80.9% in IP2, compared with 72.7% in the CP and reduced the intake of darbepoetin (IP1: 20 [70]; CP 30 [80] μg P=0.032) with less Hb fluctuation (0.91±0.49 in the CP to 0.82±0.37g/dl in IP2, P<0.05), improving in the ACM compliant group. The secondary outcomes decreased with the use of ACM.

Conclusions: ACM helps to obtain better anaemia results in haemodialysis patients, minimising the risks of treatment with ESAs and reducing costs.

Keywords: Agentes estimulantes de la eritropoyesis; Anaemia; Anemia; Artificial intelligence; Chronic kidney disease; Enfermedad renal crónica; Eritropoyetina; Erythropoiesis-stimulating agents; Erythropoietin; Haemodialysis; Hemodiálisis; Inteligencia artificial.