The Cardiovascular Literature-Based Risk Algorithm (CALIBRA): Predicting Cardiovascular Events in Patients With Non-Dialysis Dependent Chronic Kidney Disease.

Background and Objectives

Cardiovascular (CV) disease is the main cause of morbidity and mortality in patients suffering from chronic kidney disease (CKD). Although it is widely recognized that CV risk assessment represents an essential prerequisite for clinical management, existing prognostic models appear not to be entirely adequate for CKD patients. We derived a literature-based, naïve-bayes model predicting the yearly risk of CV hospitalizations among patients suffering from CKD, referred as the CArdiovascular, LIterature-Based, Risk Algorithm (CALIBRA).

Methods

CALIBRA incorporates 31 variables including traditional and CKD-specific risk factors. It was validated in two independent CKD populations: the FMC NephroCare cohort (European Clinical Database, EuCliD

Results

CALIBRA showed good discrimination in both the EuCliD

Conclusion

CALIBRA provides accurate and robust stratification of CKD patients according to CV risk and allows score calculations with improved accuracy compared to established CV risk scores also in real-world clinical cohorts with considerable missingness rates. Our results support the generalizability of CALIBRA across different CKD populations and clinical settings.

Informations de copyright

Copyright © 2022 Neri, Lonati, Titapiccolo, Nadal, Meiselbach, Schmid, Baerthlein, Tschulena, Schneider, Schultheiss, Barbieri, Moore, Steppan, Eckardt, Stuard and Bellocchio.

Déclaration de conflit d'intérêts

LN, JT, FB, SoS, StS, CM, CB, and UT are full time employees at Fresenius Medical Care. CL provided medical writing services on behalf of Fresenius Medical Care. HM reports grants from KfH Foundation of Preventive Medicine, and grants from German ministry of Education and Research. MatS reports grants from Fresenius Medical Care during the conduct of the study. BB reports grants from the Federal Ministry of Education and Research (Bundesministerium für Bildung und Forschung (www.bmbf.de), FKZ 01ER 0804, 01ER 0818, 01ER 0819, 01ER 0820 und 01ER 0821), and grants from Foundation for Preventive Medicine of the KfH (Kuratorium für Heimdialyse und Nierentransplantation e.V.–Stiftung Präventivmedizin; www.kfh-stiftung-praeventivmedizin.de). MarS reports grants from Fresenius Medical Care outside the submitted work. K-UE reports grants from: Astra Zeneca, Bayer, Fresenius Medical Care, Vifor, and Amgen during the conduct of the study, personal fees from Akebia, Astellas, Astra Zeneca, Bayer, and Boehringer Ingelheim, and grants from Genzyme, Shire, and Vifor outside the submitted work. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.