This national, prospective and multicenter study aimed to describe the real-life impact of comorbidities on hemoglobin stability in patients with chronic kidney disease on hemodialysis, treated with CERA in relay of an erythropoietin stimulating agent. Comorbidities were defined by the Charlson Index (adjusted on age) and hemoglobin stability as a variation of ±1g/dL after the 6-month treatment period. The 585 analyzed patients were distributed as follows according to the adjusted Charlson index: score≤3 (12% of patients), 4≤score≤5 (17%), 6≤score≤7 (31%) and score≥8 (40%). At CERA start, its median monthly dose was of 100μg for the overall population, with no changes during the treatment period and with little variation according to the comorbidity score. Patients with stable hemoglobin (56%, 67% if score≤3) were more numerous to reach the therapeutic target range between 10 and 12g/dL after 6 months (85% versus 43% if not stable hemoglobin). Patients with low C-reactive protein value (≤5mg/L ; P=0.04), no red blood cell transfusion (P=0.03), or no/low dose of intravenous iron (≤200mg ; P=0.03) were more likely to reach stable hemoglobin under CERA after 6 months. Among the 644 CERA-treated patients, 4 patients (<1%) had one serious adverse event related to treatment. A stable hemoglobin within the therapeutic target was reached in the majority of the patients after 6 months in current practice with a lower CERA dose, regardless of the comorbidities scores of patients on hemodialysis.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.nephro.2018.11.006DOI Listing

Publication Analysis

Top Keywords

hemoglobin stability
12
stable hemoglobin
12
comorbidities hemoglobin
8
patients
8
stability patients
8
patients chronic
8
chronic kidney
8
hemodialysis treated
8
treated cera
8
treatment period
8

Similar Publications

: Depression often coexists with anemia, potentially sharing common pathways, highlighting the need for treatments addressing both conditions simultaneously. This study evaluated the effect of probiotics on red blood cell (RBC) parameters in adults with depressive disorder. We hypothesized that probiotics would positively influence RBC parameters, potentially modulated by baseline inflammation or dietary intake, with improved RBC function correlating with better antidepressant outcomes.

View Article and Find Full Text PDF

Development and validation of a risk prediction model for acute kidney injury in coronary artery disease.

BMC Cardiovasc Disord

January 2025

Center for Coronary Artery Disease, Division of Cardiology, Beijing Anzhen Hospital, Capital Medical University, 2 Anzhen Road, Chaoyang District, Beijing, 100029, China.

Background: Acute Kidney Injury (AKI) is a sudden and often reversible condition characterized by rapid kidney function reduction, posing significant risks to coronary artery disease (CAD) patients. This study focuses on developing accurate predictive models to improve the early detection and prognosis of AKI in CAD patients.

Methods: We used Electronic Health Records (EHRs) from a nationwide CAD registry including 54 429 patients.

View Article and Find Full Text PDF

Amycolatopsis sp. BJA-103 was isolated for its exceptional feather-degradation capability, leading to the purification, cloning, and heterologous expression of the keratinase enzyme, KER0199. Sequence analysis places KER0199 within the S8 protease family, revealing <60 % sequence similarity to known proteases.

View Article and Find Full Text PDF

Rationale: Spontaneous retroperitoneal hematoma (SRH) is a rare but potentially fatal condition, often associated with anticoagulation therapy. With the global prevalence of COVID-19 and the widespread use of anticoagulants in its management, there is an increasing need to recognize rare but serious complications like SRH. This case report aims to emphasize the importance of early recognition and intervention of SRH in patients with COVID-19 undergoing anticoagulation therapy, to improve patient outcomes and reduce mortality.

View Article and Find Full Text PDF

Objectives: The high incidence of coronary artery heart disease (CHD) poses a significant burden and challenge to public health systems globally. Effective prevention and early diagnosis of CHD have become key strategies to alleviate this burden. This study aims to explore the application of advanced machine learning techniques to enhance the accuracy of early screening and risk assessment for CHD.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!