Association of the systemic immune-inflammation index (SII) and clinical outcomes in patients with stroke: A systematic review and meta-analysis
Bibliographic record
Abstract
Introduction: A novel systemic immune-inflammation index (SII) has been proven to be associated with outcomes in patients with cancer. Although some studies have shown that the SII is a potential and valuable tool to diagnose and predict the advise outcomes in stroke patients. Nevertheless, the findings are controversial, and their association with clinical outcomes is unclear. Consequently, we conducted a comprehensive review and meta-analysis to explore the relationship between SII and clinical outcomes in stroke patients. Methods: A search of five English databases (PubMed, Embase, Cochrane Library, Scopus, and Web of Science) and four Chinese databases (CNKI, VIP, WanFang, and CBM) was conducted. Our study strictly complied with the PRISMA (the Preferred Reporting Items for Systematic Reviews and Meta-Analyses). We used the NOS (Newcastle-Ottawa Scale) tool to assess the possible bias of included studies. The endpoints included poor outcome (the modified Rankin Scale [mRS] ≥ 3 points or > 3 points), mortality, the severity of stroke (according to assessment by the National Institute of Health stroke scale [NIHSS] ≥ 5 points), hemorrhagic transformation (HT) were statistically analyzed. Results: = 42%). We also investigated the difference in SII levels in poor/good outcomes, death/survival, and minor/moderate-severe stroke groups. Our analysis demonstrated that the SII level of the poor outcome, death, and moderate-severe stroke group was much higher than that of the good outcome, survival, and minor stroke group, respectively (standard mean difference [SMD] 1.11, 95% CI 0.61-1.61, P < 0.00001 [poor/good outcome]; MD 498.22, 95% CI 333.18-663.25, P < 0.00001 [death/survival]; SMD 1.35, 95% CI 0.48-2.23, P = 0.002 [severity of stroke]). SII, on the other hand, had no significant impact on recanalization (OR 1.50, 95% CI 0.86-2.62, P = 0.16). Discussion: To the best of our knowledge, this may be the first meta-analysis to look at the link between SII and clinical outcomes in stroke patients. The inflammatory response after a stroke is useful for immunoregulatory treatment. Stroke patients with high SII should be closely monitored, since this might be a viable treatment strategy for limiting brain damage after a stroke. As a result, research into SII and the clinical outcomes of stroke patients is crucial. Our preliminary findings may represent the clinical condition and aid clinical decision-makers. Nonetheless, further research is needed to better understand the utility of SII through dynamic monitoring. To generate more robust results, large-sample and multi-center research are required. Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42022371996.
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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 | 0.013 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.034 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".