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Published on: January 28, 2020
The Role of the Inflammatory Prognostic Index in Patients with Non-ST Elevation Myocardial Infarction Undergoing
Ersan Oflar1, Muhsin Kalyoncuoğlu1, Atilla Koyuncu1
1Department of Cardiology, Bakırköy Sadi Konuk Training and Research Hospital, University of Health Sciences, 34147 Istanbul, Turkey.
Insights
The inflammatory prognostic index (IPI) can predict major adverse cardiovascular and cerebrovascular events (MACCEs) in non-ST elevation myocardial infarction (NSTEMI) patients after percutaneous coronary intervention (PCI). Higher IPI scores indicate a greater risk of MACCEs within one year.
Area of Science:
- Cardiology
- Internal Medicine
- Biomarkers
Background:
- Assessing prognosis in non-ST elevation myocardial infarction (NSTEMI) patients undergoing percutaneous coronary intervention (PCI) is crucial.
- Inflammatory markers may offer valuable prognostic information.
Purpose of the Study:
- To evaluate the prognostic role of the admission inflammatory prognostic index (IPI) in predicting major adverse cardiovascular and cerebrovascular events (MACCEs).
- To compare the predictive accuracy of IPI against other inflammatory markers.
Main Methods:
- A cohort of 1142 NSTEMI patients undergoing PCI was analyzed.
- The inflammatory prognostic index (IPI) was calculated using C-reactive protein/albumin ratio (CAR) and neutrophil-to-lymphocyte ratio (NLR).
- Patients were stratified based on the median IPI value, and MACCEs were tracked over one year.
Main Results:
- Higher admission IPI values were significantly associated with an increased risk of MACCEs within one year (p < 0.001).
- The IPI demonstrated superior predictive performance (AUC = 0.70) compared to CAR (AUC = 0.64), NLR (AUC = 0.64), and AISI (AUC = 0.59).
- Incorporating IPI into a multivariable model significantly improved risk prediction (C-index = 0.84).
Conclusions:
- The admission inflammatory prognostic index (IPI) is a promising tool for predicting MACCEs in NSTEMI patients undergoing PCI.
- IPI offers a simple yet effective method for risk stratification in this patient population.
- Clinical implementation of IPI could enhance patient management and outcomes.
Abstract:
Background/Objectives: To evaluate the prognostic role of the inflammatory prognostic index (IPI) value at admission in major adverse cardiovascular and cerebrovascular events (MACCEs) in individuals with non-ST elevation myocardial infarction (NSTEMI) undergoing percutaneous coronary intervention (PCI). Methods: A total of 1142 NSTEMI patients with a mean age of 61.9 ± 12.5 years were included. Admission C-reactive protein level, serum albumin level, and complete blood counts of participants were collected from hospital records. The IPI was calculated based on the following formula: C-reactive protein/albumin ratio (CAR) x neutrophil-to-lymphocyte ratio (NLR). An aggregate index of systemic inflammation (AISI) value was calculated using the ''neutrophil count x monocyte count x platelet/lymphocyte count'' formula. The study cohort was divided into two groups according to the median IPI value. Results: Patients with higher IPI values were statistically more likely to suffer from MACCEs within one year (p < 0.001), thus the admission IPI value was found to be associated with future development of MACCEs. Furthermore, it had sufficient discrimination power (AUC = 0.70) and predictive accuracy in identifying MACCEs compared to other inflammatory parameters such as the CAR (AUC = 0.64), the NLR (AUC = 0.64), and the AISI (AUC = 0.59). Adding the IPI to the baseline multivariable logistic regression model significantly improved the model's discrimination and net clinical benefit effect for identifying patients who would suffer from MACCEs, with a C-index of 0.84 (95% CI: 0.82-0.86) and explanatory power of 23.2% (R2 = 0.232, DeLong test p = 0.001). High-risk patients with an IPI value greater than 2.43 had significantly more adverse events (p < 0.001). Conclusions: The IPI may be a promising inflammatory index for use in clinical practice to determine the risk prediction of MACCEs in NSTEMI patients undergoing PCI.
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