Cumulative biomarker domain burden across inflammatory, coagulation, and metabolic domains confers additional independent risk for poor 90-day functional outcome after endovascular thrombectomy, with each additional abnormal domain increasing risk by 57.6%, though stroke severity remains the primary determinant of outcome.
Key Findings
Results
Poor functional outcome at 90 days occurred in the majority of patients who underwent endovascular thrombectomy for large-vessel occlusion acute ischemic stroke.
Poor functional outcome (mRS > 2) occurred in 63.6% of patients.
The study included 379 patients with large-vessel occlusion acute ischemic stroke who underwent endovascular thrombectomy.
This was a single-center retrospective study.
Functional outcome was assessed at 90 days using the modified Rankin Scale (mRS > 2 defined as poor outcome).
Results
Higher baseline NIHSS, BMI, and NLR were independent predictors of poor functional outcome at 90 days.
Baseline NIHSS, BMI, and NLR remained independent predictors after multivariable logistic regression.
All analyses were adjusted for confounders with FDR correction applied.
Stroke severity (NIHSS) was identified as the primary determinant of outcome.
These three variables were the primary drivers of unfavorable outcomes.
Results
Patients with poor outcomes exhibited significantly different inflammatory, coagulation, and metabolic biomarker profiles compared to those with good outcomes.
Patients with poor outcomes had higher hsCRP, D-dimer, NLR, WBC, and glucose levels.
Patients with poor outcomes had lower lymphocyte and platelet counts.
All biomarker differences reached statistical significance after FDR adjustment (all FDR-adjusted p < 0.05).
A clear dose-response relationship was observed between cumulative biomarker domain burden and risk of poor functional outcome.
A biomarker domain burden score was constructed ranging from 0 to 3 abnormal domains.
Adjusted odds ratios for poor outcome were 2.19, 3.27, and 3.39 for one, two, and three abnormal domains, respectively.
Each additional abnormal domain increased risk by 57.6% (p = 0.002).
No significant interactions were detected between domains, indicating additive rather than synergistic effects.
Results
The clinical prediction model demonstrated acceptable discrimination, but adding biomarker information did not significantly improve model performance.
The clinical model achieved an AUC of 0.756.
After biomarker integration, AUC increased minimally to 0.760.
The difference between the two AUCs was not statistically significant according to the paired DeLong test (p = 0.684).
The improvement after biomarker integration was described as 'minimal.'
Results
Post-treatment intracranial hemorrhage was common, and higher baseline NIHSS was independently associated with its occurrence.
Any radiographically detected post-treatment intracranial hemorrhage (ICH) occurred in 50.4% of patients.
This broad outcome included both symptomatic and asymptomatic hemorrhagic events.
Higher baseline NIHSS was independently associated with post-treatment hemorrhage.
NLR showed borderline significance as a predictor of post-treatment intracranial hemorrhage.
What This Means
This research suggests that when patients suffer a major stroke caused by a blocked large blood vessel and receive a procedure to remove the clot (endovascular thrombectomy), their recovery is strongly influenced by how severe the stroke is at the start, but also by disturbances across multiple body systems simultaneously. In a study of 379 stroke patients, nearly two-thirds (63.6%) had poor functional outcomes 90 days later. Patients who fared worse tended to have elevated markers of inflammation, abnormal blood clotting, and higher blood sugar levels, alongside lower counts of protective immune cells and platelets. Importantly, having problems in more of these biological 'domains' at once compounded the risk — each additional abnormal system raised the odds of a poor outcome by about 58%.
This research suggests that the combined burden of biological abnormalities across inflammatory, clotting, and metabolic systems matters beyond any single marker in isolation, and that the effects appear to be additive rather than synergistic. However, while these biomarkers were statistically associated with outcomes, adding them to a clinical prediction model that already included standard information like stroke severity did not meaningfully improve the model's ability to predict who would do poorly. Post-treatment bleeding in the brain was also very common, affecting about half of all patients, with stroke severity again being the strongest predictor.
Practically, this research suggests that clinicians may benefit from assessing multiple biological systems together — not just one inflammation or clotting marker — when evaluating stroke patients after thrombectomy. However, the limited added predictive value of biomarkers beyond clinical variables like stroke severity score suggests that these laboratory measures may be more useful for understanding disease mechanisms than for changing clinical predictions in the short term. Future prospective studies could help clarify whether targeting these abnormal biological domains might improve patient outcomes.
Wang S, Xie Y, Zhang Y. (2026). Cumulative inflammatory, coagulation, and metabolic abnormalities predict poor 90-day functional outcome after endovascular thrombectomy for large-vessel occlusion acute ischemic stroke.. Frontiers in neurology. https://doi.org/10.3389/fneur.2026.1866039