Key result
Adding systemic immune-inflammation index to basic models linked to ~477% better prediction of severe CAD.
Why the study?
The comparative predictive power of systemic immune-inflammation index and Naples prognostic score for coronary artery disease severity was unclear.
Does the systemic immune-inflammation index (SII) or Naples prognostic score (NPS) improve the prediction of coronary artery disease severity in patients undergoing CCTA?
Observational (n=1,138)
Does the systemic immune-inflammation index (SII) or Naples prognostic score (NPS) improve the prediction of coronary artery disease severity in patients undergoing CCTA?
Odds Ratio: 5.77 (95% CI 4.15–8.02)
p-value: p=< .001
The systemic immune-inflammation index (SII), but not the Naples prognostic score, provides incremental value over traditional risk factors in predicting CAD severity on CCTA.
SII may refine CAD severity prediction on CCTA; leaves open prospective validation before any clinical use.
This study compared the predictive power of the systemic immune-inflammation index (SII) and Naples prognostic score (NPS) in determining the severity of coronary artery disease (CAD). The study included 1138 patients who underwent coronary computed tomographic angiography (CCTA). The primary outcome was the evaluation of CAD severity, determined by the Coronary Artery Disease-Reporting and Data System (CAD-RADS) obtained from the CCTA scans. A basic statistical model including age, gender, chest pain, diabetes mellitus, hypertension, hyperlipidemia, and smoking was built, and categorical variables, NPS (Naples 3,4 vs 0,1,2) and SII, were added to the basic statistical model. The net benefits of the predictive parameters were determined by a decision curve analysis, and the association between CAD-RADS and NPS, SII was quantified by odds ratios (OR) and 95% confidence intervals (CI). The decision curve analysis showed that adding SII to the statistical model had a better full range of probability of clinical net benefit compared with the baseline model (OR: 5.77, 95% CI 4.15–8.02, P < .001). However, adding the NPS ( P = .11) to the model did not outperform the basic statistical model. In conclusion, the SII may have a net predictive effect on top of traditional risk factors.
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Özkan et al. (2023) conducted an observational in Coronary artery disease severity (n=1,138). Systemic immune-inflammation index (SII) vs. Basic statistical model (traditional risk factors) was evaluated on Evaluation of CAD severity determined by CAD-RADS (OR 5.77, 95% CI 4.15-8.02, p=< .001). Adding the systemic immune-inflammation index to a basic statistical model significantly improved the prediction of coronary artery disease severity (OR 5.77; 95% CI 4.15-8.02; P < .001).
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