This dual-center retrospective cohort study analyzed 4403 patients with acute ischemic stroke who underwent intravenous thrombolysis. Researchers examined the independent and joint associations of remnant cholesterol (RC) levels and the Cholesterol, high-density lipoprotein, and glucose (CHG) index with two outcomes: hemorrhagic transformation (HT) and poor functional prognosis at 90 days (modified Rankin Scale score >2).
Patients who experienced HT had lower RC and CHG levels compared to those without HT. For the joint effect of higher RC and CHG levels, the study found an odds ratio of 0.18 (95% CI: 0.12–0.25) for HT, indicating a negative association. Similarly, for poor 90-day prognosis, the joint effect showed an odds ratio of 0.40 (95% CI: 0.32–0.49). The combination of RC and CHG demonstrated better predictive efficacy for both outcomes than either biomarker alone, with area under the curve values of 0.750 for HT and 0.721 for poor prognosis.
Safety and tolerability data were not reported in this analysis. The study's retrospective observational design represents its primary limitation, as it can only demonstrate associations rather than establish causality. The biomarkers were calculated from routine laboratory measurements rather than prospectively measured for this purpose.
While the authors suggest these biomarkers might eventually support pre-thrombolysis risk stratification, clinicians should interpret these findings cautiously. The associations require validation in prospective studies before any consideration of clinical implementation. The absence of absolute risk numbers and detailed safety data further limits immediate practice implications.
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This study aimed to investigate the independent and joint effects of two novel lipid-derived biomarkers—Remnant cholesterol (RC) and Cholesterol, high-density lipoprotein, and glucose (CHG) index—with hemorrhagic transformation (HT) and poor prognosis in patients with acute ischemic stroke (AIS) after intravenous thrombolysis (IVT).
In this dual-center retrospective cohort study, 4403 AIS patients undergoing IVT were analyzed. RC and the CHG index were calculated from routine baseline biochemical measurements. The primary outcome was HT, and the secondary outcome was poor prognosis at 90 days (modified Rankin Scale [mRS] score > 2). Multivariable logistic regression and restricted cubic spline (RCS) models were used to assess linear and non-linear associations. Subgroup and receiver operating characteristic (ROC) analyses were conducted to evaluate robustness and discriminative ability. Mediation analysis explored the potential mediating role of the systemic immune-inflammation index (SII).
Patients with HT or a poor prognosis had lower RC and CHG levels. Multivariate logistic regression analysis revealed that both RC and CHG were negatively associated with the risk of HT and with a poor prognosis. The joint effects showed that patients with higher levels of RC and CHG had a significantly lower risk of HT (OR = 0.18, 95% CI: 0.12–0.25) and poor prognosis (OR = 0.40, 95% CI: 0.32–0.49). Subgroup analyses confirmed the consistency of these negative associations across age, sex, baseline NIHSS, and vascular comorbidities. The RCS models showed a non-linear association between RC and poor prognosis (P for non-linearity < 0.05) but a linear trend with HT (P > 0.05). In contrast, CHG showed a U-shaped non-linear association with both outcomes (P < 0.05). Moreover, the combination of RC and CHG had better predictive efficacy for HT (AUC = 0.750, 95% CI: 0.727–0.773, P < 0.001) and poor prognosis (AUC = 0.721, 95% CI: 0.705–0.737, P < 0.001) than alone. Mediation analysis further showed that SII partially mediated these associations.
High RC and CHG levels were associated with a lower risk of HT and poor prognosis in AIS patients undergoing IVT. Integrating these biomarkers enhances predictive performance, supporting their potential utility in pre-thrombolysis risk stratification and personalized treatment decision-making.