Cerebrospinal Fluid and Microdialysis Cytokines in Aneurysmal Subarachnoid Hemorrhage: A Scoping Systematic Review
Bibliographic record
Abstract
OBJECTIVE: To perform two scoping systematic reviews of the literature on cytokine measurement in cerebral microdialysis (CMD) and cerebrospinal fluid (CSF) in aneurysmal subarachnoid hemorrhage (SAH) patients, aiming to summarize the evidence relating cytokine levels to pathophysiology, disease progression, and outcome. METHODS: Two separate systematic reviews were conducted: one for CMD cytokines and the second for CSF cytokines. DATA SOURCES: Articles from MEDLINE, BIOSIS, EMBASE, Global Health, Scopus, Cochrane Library (inception to October 2016), reference lists of relevant articles, and gray literature were searched. STUDY SELECTION: Two reviewers independently identified all manuscripts utilizing predefined inclusion/exclusion criteria. A two-tier filter of references was conducted. DATA EXTRACTION: Patient demographic and study data were extracted to tables. RESULTS: CMD in 246 aneurysmal SAH patients. Similarly, 20 studies were identified describing the analysis of CSF cytokines in 630 patients. The two scoping systematic reviews demonstrated the following: (1) limited literature available on CMD cytokine measurement in aneurysmal SAH with some preliminary data supporting feasibility of measurement and potential association between interleukin (IL)-6 and patient outcome. (2) Various CSF measured cytokines may be associated with patient outcome at 3-6 months, including IL-1ra, IL-6, IL-8, and tumor necrosis factor-alpha. (3) There is a small literature body supporting an association between acute/subacute CSF transforming growth factor levels and the development of chronic hydrocephalus at 2-3 months. CONCLUSION: The evaluation of CMD and CSF cytokines is an emerging area of the literature in aneurysmal SAH. Further large prospective multicenter studies on cytokines in CMD and CSF need to be conducted.
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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 | 0.017 | 0.070 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.009 |
| Bibliometrics | 0.017 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".