Związek między wieloma wskaźnikami zapalenia a ryzykiem epilepsji pojawiającej się po udarze mózgu
Association Between Multiple Inflammation-Derived Indices and the Risk of Post-Stroke Epilepsy
W skrócie
Badanie wykazało, że jeden z mierników zapalenia w organizmie, zwany SIRI, może помóc w przewidywaniu, czy pacjent po udarze mózgu zachoruje na epilepsję. Im wyższy wskaźnik SIRI u pacjenta w ciągu pierwszych 24 godzin po udarze, tym większe ryzyko epilepsji. Naukowcy sugerują, że SIRI może być użytecznym narzędziem pomocniczym do wczesnego rozpoznania pacjentów zagrożonych epilepsją pospołudniową, ale potrzebne są dalsze badania, aby potwierdzić jego praktyczną wartość kliniczną.
Oryginalny abstract (angielski)
BACKGROUND: Post-stroke epilepsy (PSE) is a common and serious complication of stroke, yet simple and efficient risk assessment tools remain lacking in clinical practice. This study aimed to investigate the association between multiple core inflammation-derived indices and PSE, and to explore their potential reference value in risk stratification. METHODS: In this retrospective case-control study, we extracted data from hospitalized stroke patients at Hefei Second People's Hospital between January 2018 and December 2025 from the electronic medical record system. A 1:1 propensity score matching method was used to balance confounding factors including sex, age, and underlying diseases. Ultimately, 317 PSE patients (case group) and 317 stroke patients without PSE (control group) were included. Routine hematological parameters collected within 24 h of admission were used to calculate six inflammatory indices: the systemic immune-inflammation index (SIRI), neutrophil-to-lymphocyte ratio (NLR), derived neutrophil-to-lymphocyte ratio (DNLR), monocyte-to-lymphocyte ratio (MLR), neutrophil-to-platelet ratio (NPR), and neutrophil-monocyte-to-lymphocyte ratio (NMLR). Multivariable logistic regression models were employed to analyze the association between inflammatory indices and PSE risk, and nonlinear relationships and threshold effects were also explored. The discriminative ability and incremental value of each inflammatory index were assessed using receiver operating characteristic (ROC) curves, decision curve analysis (DCA), net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Subgroup analyses were conducted to verify the stability of the results. RESULTS: This study showed that for each one-standard-deviation increase in SIRI, the risk of PSE increased by 172% (OR = 2.72, FDR-adjusted p < 0.001). Quartile-stratified analysis revealed a clear dose-response relationship (trend p < 0.001). Similarly, the strength of association for SIRI was superior to that of other inflammation-derived indices. Compared with the other inflammatory indices, SIRI demonstrated relatively better discriminative ability in ROC analysis (AUC = 0.693, 95% CI: 0.654-0.732), NRI, and DCA. Restricted cubic spline regression and E-value analysis further supported the robustness of this association, and subgroup analyses indicated consistency across different subgroups. CONCLUSION: Systemic immune-inflammation index showed a relatively strong association with PSE risk and moderate discriminative ability in the stroke population, and may serve as an auxiliary reference indicator for early risk stratification of post-stroke epilepsy. However, its clinical utility requires further validation in prospective cohort studies.