Diagnosing Trousseau syndrome (TS) in its early stages presents significant difficulties owing to the lack of distinctive symptoms. Emerging research suggests that immune-mediated inflammatory processes play a crucial role in TS development. This investigation explores the evaluation of the utility of the systemic immune-inflammation index (SII) in the early diagnosis of TS with acute ischemic stroke (AIS) as its initial manifestation. This study employed a retrospective design to examine 30 patients treated at Affiliated Hospital of Jiangsu University from 2018 to 2025. Clinical records were reviewed to obtain demographic information, National Institutes of Health Stroke Scale (NIHSS), hematological parameters: complete blood count, C-reactive protein (CRP), coagulation profiles, and oncological biomarkers. The SII was derived through computational analysis using the formula: (neutrophil count × platelet count)/lymphocyte count. Participants were stratified into two distinct cohorts based on the temporal relationship between AIS onset and cancer diagnosis: the AIS-TS group (n = 14) comprised patients whose AIS represented the initial manifestation of TS, while the NAIS-TS group (n = 16) included individuals who developed AIS subsequent to their cancer diagnosis. Logistic regression analysis was implemented to investigate potential associations between SII values and AIS-TS classification. Additionally, the relationship between SII and D-dimer index (DDI) concentrations was examined through bivariate correlation analysis. Correlation analyses employed Pearson’s or Spearman’s correlation coefficient, selected based on the normality of variable distributions. To assess the diagnostic accuracy of AIS-TS, receiver operating characteristic (ROC) curve analysis was employed as the evaluation approach. In the logistic regression model, a total of 5 variables with P < 0.1 in the univariate logistic regression analysis were included in the multivariate logistic regression analysis. The adjusted odds ratios (ORs) of advanced age and SII for the AIS-TS group were 1.224 (95% CI 1.015–1.475, P = 0.034) and 1.006 (95% CI 1.001–1.012, P = 0.023), respectively. Spearman's correlation showed a significant but moderate correlation (r = 0.484, P = 0.007) of SII and DDI. The diagnostic efficacy for AIS-TS, the area under the ROC curve for indicators age and SII were comparable (AUC: 0.781 vs. 0.824, P = 0.732); however, their combined use in diagnostic analysis demonstrated a substantial improvement in diagnostic performance (AUC = 0.879). The optimal cut-off value estimated by Youden's index was 71.5 years for age and 434.18 for SII, respectively. SII and advanced age can serve as independent indicators for TS in patients presenting with AIS as the initial clinical manifestation. Age and SII demonstrate moderate indicative value individually, and their combined use enhances indicative performance.
Ke et al. (Sun,) studied this question.