Association between systemic immune-inflammation index, systemic inflammation response index, and adverse outcomes in aneurysmal subarachnoid hemorrhage: a meta-analysis
Bibliographic record
Abstract
Purpose This systematic review seeks to explore the link of the systemic immune-inflammation index (SII) and systemic inflammation response index (SIRI), to adverse outcomes (AOs) in aneurysmal subarachnoid hemorrhage (aSAH). The findings may provide scientific evidence to enable the timely identification of patients at high risk and guide the formulation of personalized treatment strategies. Patients and methods PubMed, Cochrane, Embase, and Web of Science databases were comprehensively retrieved from inception to August 10, 2024. The Newcastle-Ottawa Scale (NOS) was leveraged for appraise the quality of the encompassed studies. Statistical analyses were undertaken via Stata 17.0, and a bivariate mixed-effects model was applied for diagnostic value evaluation. Results Sixteen studies involving 4,510 aSAH individuals were encompassed. The meta-analysis demonstrated SII as a predictor of poor 90-day outcomes [Odds Ratio (OR) = 1.94, 95% Confidence Interval (CI): 1.35–2.78, p < 0.001], with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.77 (95% CI: 0.73–0.81), sensitivity of 0.71 (95% CI: 0.61–0.79), and specificity of 0.72 (95% CI: 0.62–0.80). Additionally, SII can be utilized for forecasting delayed cerebral ischemia (DCI) (OR = 1.39, 95% CI: 1.35–1.43, p < 0.001), with an AUC of 0.80 (95% CI: 0.76–0.83), sensitivity of 0.75 (95% CI: 0.56–0.88), and specificity of 0.73 (95% CI: 0.62–0.82). SIRI was also found to predict unfavorable 90-day outcomes (OR = 1.19, 95% CI: 1.09–1.30, p < 0.001), with an AUC of 0.79 (95% CI: 0.75–0.82), sensitivity of 0.66 (95% CI: 0.58–0.73), and specificity of 0.76 (95% CI, 0.73–0.80). However, SIRI was not a significant predictor of DCI (OR = 1.37, 95% CI: 0.94–2.02, p = 0.105) or postoperative pneumonia (POP) (OR = 3.73, 95% CI: 0.68–20.35, p = 0.128). Conclusion Both SII and SIRI serve as predictive biomarkers for unfavorable 90-day outcomes in the aSAH population, with SII also demonstrating predictive value for DCI. While both indices exhibit moderate accuracy, further research is necessitated to validate their clinical utility. Clinical trial registration https://www.crd.york.ac.uk/PROSPERO/ , Registration No: CRD42024585116.
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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 | 0.015 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.044 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".