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Updated: Sep 11, 2025

Technique and Patient Selection Criteria of Right Anterior Mini-Thoracotomy for Minimal Access Aortic Valve Replacement
Published on: March 26, 2018
Preoperative Outcome Predictors in Aortic Valve Replacement: A Single-Center Retrospective Study
Ilenia Foffa1,2, Augusto Esposito3, Ludovica Simonini1
1Institute of Clinical Physiology, National Research Council, 54100 Massa, Italy.
Abstract:
Background: Several blood biomarkers have shown a major role in predicting major adverse complications (MACs) in patients who have undergone cardiac surgery. Here, we aimed to investigate the possible role of the blood urea nitrogen (BUN) to serum albumin ratio (BAR) and the inflammatory prognostic index (IPI) in predicting major adverse complication after surgical aorta valve replacement (SAVR). Methods: The clinical, echocardiographic, and clinical-chemistry laboratory data of 195 patients who underwent SAVR were evaluated. The post-surgical MACs (death, surgical re-exploration, myocardial infarction and cerebral ischemia) during the hospitalization were recorded. Univariate and multivariate logistic regression analyses were studied by comparing the basic clinical features, echocardiographic parameters, and patients' hematological indices between patients with or without MACs. Results: The mean age was 66.1 years, and 62.5% were males. Logistic regression analysis showed that the left atrium volume (LAV), BAR, and IPI as either continuous or categorical variables were independently associated with MACs. Moreover, we found a combined effect of higher LAV with a higher value of BAR or IPI. Combined higher levels of LAV and BAR increased the risk of developing MACs by 9.8 (CI 95% = 2.8-34.3, p = 0.0003), while higher values of LAV and IPI increased the risk of developing MACs by 4.5. Conclusions: Higher levels of BAR and IPI, alone or in combination with higher LAVs, showed an independent predictive value of MACs after SAVR. These findings strongly support the importance of evaluating easily available biomarkers of the pre-operative status of patients in order to predict adverse outcomes.
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