Integrating coronary CT angiography-derived vulnerable plaque features, the systemic immune-inflammation index, and traditional Chinese medicine syndrome elements for prediction of acute coronary syndrome: an exploratory retrospective cohort study

Background Acute coronary syndrome (ACS) arises from disruption of coronary atherosclerotic plaques. We assessed whether integrating coronary CT angiography (CCTA)-defined vulnerable plaque (VP), the systemic immune-inflammation index (SII), and traditional Chinese medicine (TCM) syndrome elements improves prediction of incident ACS. Methods This retrospective cohort study enrolled 266 hospitalized patients with >25% coronary stenosis on CCTA (July 2019-July 2021); patients with ACS at baseline were excluded, and all completed a fixed 3-year follow-up from the index CCTA (index date). VP was defined as ≥2 high-risk CCTA features and SII as platelet × neutrophil/lymphocyte count; eight TCM syndrome elements were diagnosed by standardized criteria. Firth-penalized logistic regression with LASSO selection was evaluated by the area under the curve (AUC), calibration, reclassification indices, and decision curve analysis, with selection-inclusive bootstrap internal validation. Results Twenty-two patients developed ACS. In the five-variable Firth model, VP (odds ratio [OR] 12.84, 95% confidence interval [CI] 3.64–45.28), SII (OR 1.18 per 100 × 10 9 /L, 95% CI 1.04–1.33; nonlinear association, P for nonlinearity < 0.001), and the phlegm-turbidity syndrome element (OR 3.07, 95% CI 1.15–8.22) independently predicted ACS. The final three-variable model (ORs 16.30, 1.15 per 100 × 10 9 /L, and 3.65, respectively) showed the best apparent discrimination (AUC 0.873, 95% CI 0.806–0.940; selection-inclusive optimism-corrected AUC 0.812, 95% CI 0.741–0.871) and calibration (intercept −0.07, slope 1.06; Brier score 0.0630), with sensitivity 81.8% and specificity 77.9%, the widest net-benefit threshold range (1%–49%), and nominally higher integrated discrimination improvement over the binary VP indicator (0.073, 95% CI 0.021–0.122). Among 94 patients with VP, spotty calcification, the napkin-ring sign, and stenosis severity were also associated with ACS; SII showed a dose-response relationship (Cochran-Armitage Z = 3.075, P = 0.002); and coexisting blood stasis plus phlegm turbidity marked a subgroup with 56.2% ACS incidence (9/16; exploratory) versus 17.5% (7/40) and 13.6% (3/22) for either element alone. Conclusions An exploratory multimodal model combining CCTA-defined vulnerable plaque, SII, and the phlegm-turbidity syndrome element nominally improved ACS risk prediction over a binary VP indicator. Given the few events and single-center retrospective design, these hypothesis-generating findings require external and prospective validation.