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Development of a Novel Inflammatory Index to Predict Coronary Artery Disease Severity in Patients With Acute Coronary
Sridhar Mangalesh1, Sharmila Dudani2, Nalin K Mahesh3
1Department of Medicine, Army College of Medical Sciences, New Delhi, India.
Insights
A new index, the systemic immune-inflammation response index (SIIRI), shows promise in predicting severe coronary artery disease (CAD). This novel marker outperformed existing indices in identifying patients with significant coronary artery disease.
Area of Science:
- Cardiovascular Medicine
- Inflammation Biomarkers
- Clinical Diagnostics
Background:
- Systemic immune-inflammation index (SII) and systemic inflammation response index (SIRI) are established predictors for coronary artery disease (CAD).
- There is a need for improved inflammatory markers to assess CAD severity accurately.
Purpose of the Study:
- To develop and validate a novel systemic immune-inflammation response index (SIIRI) for predicting severe CAD.
- To compare the predictive performance of SIIRI against existing inflammatory markers.
Main Methods:
- A novel index, SIIRI (neutrophil × monocyte × platelet ÷ lymphocyte), was calculated for 240 acute coronary syndrome patients undergoing percutaneous coronary intervention.
- Coronary artery disease severity was assessed using the SYNTAX score.
- Multivariate analysis and receiver operator characteristic (ROC) curves were used to evaluate SIIRI's predictive value.
Main Results:
- SIIRI independently predicted severe CAD (OR 1.666 per 10^5 unit increase).
- SIIRI demonstrated the highest area under the ROC curve (.771) compared to SII, SIRI, and other ratios.
- Adding SIIRI to a baseline model significantly improved model performance, including discrimination and reclassification.
Conclusions:
- The novel SIIRI is a valuable and independent predictor of severe coronary artery disease.
- SIIRI offers superior predictive capability for severe CAD compared to existing inflammatory indices.
- SIIRI enhances clinical risk stratification models for patients with acute coronary syndromes.
Abstract:
The systemic immune-inflammation index (SII) and systemic inflammation response index (SIRI) have previously demonstrated predictive value in coronary artery disease (CAD). We developed on an expanded, novel systemic immune-inflammation response index (SIIRI), calculated as peripheral neutrophil × monocyte × platelet ÷ lymphocyte count. We assessed 240 patients with an acute coronary syndrome that subsequently underwent percutaneous coronary intervention. CAD severity was measured using the SYNTAX score. Laboratory measurements, including cell counts, were obtained on admission. On multivariate analysis, the SIIRI was an independent predictor of severe CAD with an adjusted odds ratio (OR) of 1.666 [1.376-2.017] per 105-unit increase. The SIIRI had the highest area under the receiver operator curve of .771 [.709-.833] compared to the SII, SIRI neutrophil-lymphocyte ratio, monocyte-lymphocyte ratio, and platelet-lymphocyte ratio. The optimal cut-off for SIIRI was 4.3 × 105, with sensitivity = 69.9% and specificity = 75.8%. Increment in model performance resulting from adding SIIRI versus other inflammatory indices was assessed using discrimination, calibration, and goodness-of-fit measures. When added to a baseline model, the SIIRI resulted in a significant increase in the c-statistic and significant net reclassification index (.808, P < .0001) and integrated discrimination index (.129, P < .0001), and a decrease in Akaike and Bayesian information criteria.
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