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Published on: December 11, 2017
Inflammatory prognostic index predicts late mortality after surgical aortic valve replacement
Batuhan Yazıcı1, Mustafa Can Kaplan2, Zinar Apaydın3
1Hatay Training and Research Hospital, Hatay, Turkey.
The preoperative Inflammatory Prognostic Index (IPI) predicts late mortality in patients undergoing surgical aortic valve replacement (AVR). A high IPI score independently indicates increased risk, aiding in patient risk stratification.
Area of Science:
- Cardiology
- Surgical Outcomes
- Biomarkers
Background:
- Surgical aortic valve replacement (AVR) is a critical procedure for severe aortic valve disease.
- Accurate preoperative risk stratification is essential for optimizing patient outcomes after AVR.
- The Inflammatory Prognostic Index (IPI) is a potential biomarker for systemic inflammation.
Purpose of the Study:
- To evaluate the prognostic value of the preoperative Inflammatory Prognostic Index (IPI) in predicting late mortality after isolated surgical AVR.
- To determine if IPI is an independent predictor of long-term survival in this patient cohort.
Main Methods:
- Retrospective analysis of 400 patients undergoing elective, isolated surgical AVR (2015-2023).
- Calculation of IPI using C-reactive protein (CRP), neutrophil-to-lymphocyte ratio (NLR), and albumin.
- Stratification into low- and high-IPI groups using ROC analysis (cut-off: 0.2588).
- Cox proportional hazards regression for predictor identification.
Main Results:
- Patients with high IPI (≥0.2588) had significantly higher late mortality (10.3% vs 2.3%, p < .001).
- High IPI was independently associated with increased late mortality (HR = 3.405, p = .013) in multivariate analysis.
- Kaplan-Meier analysis showed lower long-term survival in the high-IPI group (log-rank p < .001).
Conclusions:
- Preoperative IPI is a simple, accessible, and independent predictor of late mortality following surgical AVR.
- Incorporating IPI into preoperative risk assessment can enhance prognostic stratification and guide perioperative management.
- This biomarker may help identify high-risk patients needing closer monitoring or tailored interventions.
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