Systemic inflammation–based hematological indices and 90-day functional outcomes after intravenous thrombolysis in acute ischemic stroke: a systematic review
Bibliographic record
Abstract
Background: Acute ischemic stroke (AIS) is one of the leading causes of mortality and long-term disability worldwide. Intravenous thrombolysis (IVT) with recombinant tissue plasminogen activator (rt-PA) remains the standard treatment for eligible patients; however, considerable inter-individual variability exists in post-treatment functional outcomes. Increasing evidence suggests that systemic inflammation plays a crucial regulatory role in both ischemic injury cascades and reperfusion efficacy. In recent years, several inflammation-based hematological indices derived from complete blood counts-such as the neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), inflammation prognostic index (IPI), and pan-immune-inflammation value (PIV)-have been proposed. These indices comprehensively reflect the balance between innate immune activation and adaptive immune suppression and are considered potential prognostic biomarkers. Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we systematically searched PubMed, Embase, and Web of Science for English-language studies published between 2015 and 2025 investigating the relationship between inflammation-based hematological indices and functional outcomes in adult AIS patients receiving intravenous rt-PA. Eligible studies were limited to IVT-only cohorts reporting associations between composite inflammatory indices and clinical outcomes. The search strategy was framed using the PICO (Population, Intervention, Comparison, and Outcome) approach, and study quality was assessed using the Newcastle-Ottawa Scale (NOS). Results: A total of 15 observational cohort studies involving approximately 4,000 AIS patients were included. Higher baseline or early values of NLR, SII, SIRI, and PIV were independently associated with unfavorable 90-day functional outcomes, with predictive performance (AUC) generally ranging from 0.70 to 0.80. Several studies further indicated that dynamic changes in inflammatory indices within 24-48 h after IVT provided stronger prognostic discrimination than baseline measurements, underscoring the clinical value of early immune monitoring during the acute phase of stroke. Conclusion: Systemic inflammation plays a central role in the pathophysiology and therapeutic response of AIS. Composite inflammation-based hematological indices are simple, economical, and reproducible tools that may assist in early risk stratification and individualized prognostic assessment following IVT. Future studies should incorporate dynamic longitudinal monitoring and integrate multimodal clinical and biomarker data within large, multicenter cohorts to improve model precision and enhance translational applicability.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.010 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".