A recent study published in the Journal of Cardiology has brought to light the significance of red blood cell distribution width (RDW) as a prognostic factor for patients undergoing transcatheter aortic valve implantation (TAVI). The comprehensive evaluation has added valuable insights into preprocedural risk assessment, potentially influencing how medical professionals prepare for and follow up on this increasingly common procedure.

The Clinical Significance of RDW in TAVI Patients

In a large-scale study, Yishay Szekely et al. investigated the link between RDW levels and mortality rates in patients with severe aortic stenosis (AS) treated with TAVI. The findings, which spanned a cohort of 1029 patients, showcased RDW, a parameter routinely reported in complete blood counts, as an independent marker of short- and long-term mortality outcomes in these individuals.

The research indicated that patients with an RDW greater than 15.5% experienced significantly higher mortality rates at both one-year (17% vs. 6%) and five-year (38% vs. 20%) milestones when compared to patients with lower RDW levels. These statistics are derived from a population with a mean age of 83.1 years and varied comorbid conditions, reflecting the high-risk nature of patients typically selected for TAVI.

Study Design and Key Outcomes

The study was prospectively conducted, analyzing patient data such as medical history, left ventricle ejection fraction (LVEF), frailty score, and Society of Thoracic Surgeons (STS) score, along with periprocedural laboratory results. Using RDW as a prognostic factor creates a potential paradigm shift in the pre-TAVI risk assessment, which currently relies heavily on established scoring systems like the STS score.

DOI: 10.1016/j.jjcc.2019.04.005

The Implications for TAVI Risk Stratification

With baseline RDW greater than 15.5% being independently associated with all-cause mortality (hazard ratio 1.83), there is a strong case for incorporating RDW into preprocedural evaluation routines. However, the authors highlight the necessity for further research to understand the underlying mechanisms that drive the association between RDW and mortality.

Beyond the Numbers: Understanding RDW

RDW measures the heterogeneity in the size of circulating erythrocytes (red blood cells). Elevated RDW levels can indicate various pathological conditions ranging from malnutrition to chronic inflammation, and it is increasingly recognized for its prognostic value across different clinical settings.

The Frontiers of Medical Research

In embracing findings like those from Szekely et al., the medical community moves closer to refining the methods by which we evaluate and mitigate risks associated with complex procedures like TAVI. Furthermore, the implications of this study are not confined to TAVI alone but may extend to other cardiovascular interventions, underscoring the critical nature of multifactorial risk assessment in cardiology.


1. Szekely Y, Finkelstein A, Bazan S, et al. Red blood cell distribution width as a prognostic factor in patients undergoing transcatheter aortic valve implantation. J Cardiol. 2019;74(3):212-216. DOI: 10.1016/j.jjcc.2019.04.005
2. Ferrara F, Lancellotti P. The Red Cell Distribution Width: A Simple Parameter with Multiple Clinical Applications. Crit Rev Clin Lab Sci. 2015;52(2):86-105.
3. Tonelli M, Sacks F, Arnold M, et al. Relation between red blood cell distribution width and cardiovascular event rate in people with coronary disease. Circulation. 2008;117(2):163-168.
4. van Kimmenade RRJ, Mohammed AA, Uthamalingam S, et al. Red blood cell distribution width and 1-year mortality in acute heart failure. Eur J Heart Fail. 2010;12(2):129-136.
5. Patel KV, Semba RD, Ferrucci L, et al. Red cell distribution width and mortality in older adults: A meta-analysis. J Gerontol A Biol Sci Med Sci. 2010;65A(3):258-265.


1. Red Blood Cell Distribution Width
2. Transcatheter Aortic Valve Implantation
3. TAVI Prognosis
4. Aortic Stenosis Treatment
5. RDW Mortality Link

This study’s insightfully sheds light on the multifaceted nature of patient assessment, paving the way for enhanced prognostic tools that could lead to better outcomes and more personalized care for individuals facing cardiovascular interventions. With the evolution of such predictive markers, the future of cardiac medicine continues to hinge on the intricate balance between clinical experience and data-driven innovation.