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Updated: Feb 5, 2026

Full-root Aortic Valve Replacement by Stentless Aortic Xenografts in Patients with Small Aortic Roots
Published on: May 21, 2017
EXPRESS: The correlation between hemoglobin to red cell distribution width ratio and postoperative survival in
Chaojun Yan1, Jie He2, Ying Li3
1Cardiac Surgery Department, Southwest Hospital, Army Medical University, Chongqing, China.
Abstract:
The significance of hemoglobin levels and their relationship with red blood cell distribution width (RDW) in the cardiovascular field is increasingly being re-evaluated. The association of HRR (hemoglobin to red cell distribution width ratio) with overall survival outcomes in aortic valve replacement recipients was evaluated. This retrospective study selected 1,976 eligible patients who underwent their first aortic valve replacement surgery from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Univariate and multivariate Cox proportional hazards models were developed. A nomogram prediction model was constructed, and its performance was evaluated through receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Multivariate Cox regression analysis showed that after adjusting for age, sex, comorbidities, and laboratory indicators, for each 1-unit increase in HRR, the risk of mortality decreased by 90.7% (HR = 0.093, 95% CI: 0.028-0.315), 87.3% (HR = 0.127, 95% CI: 0.041-0.390), and 87.5% (HR = 0.125, 95% CI: 0.045-0.348) at 1, 3, and 5 years, respectively, with statistically significant trends (P for trend < 0.05). Restricted cubic spline (RCS) analysis did not reveal a nonlinear relationship between HRR and mortality (P-non-linear > 0.05). The nomogram model performed well in both the training and validation sets, with AUCs of 0.834 and 0.766 for 1-year predictions, respectively. This study demonstrates that preoperative HRR is a significant independent predictor of long-term all-cause mortality in aortic valve replacement recipients. Integrating HRR into clinical risk assessment may enhance prognostication and support individualized management strategies.
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