Lipid peroxidation metabolites as biomarkers in patients with aneurysmal subarachnoid hemorrhage and cerebral vasospasm or delayed cerebral ischemia: a systematic review
Bibliographic record
Abstract
Intracranial aneurysms often remain asymptomatic until rupture, causing aneurysmal subarachnoid hemorrhage (aSAH). aSAH frequently leads to cerebral vasospasm (CVS) and delayed cerebral ischemia (DCI), significantly increasing the risk of severe neurological deficits and mortality. Identifying reliable biomarkers, such as lipid peroxidation metabolites (LPMs), is crucial for early prediction and timely intervention. This study summarizes current knowledge on LPMs as potential biomarkers for CVS and DCI after aSAH. A systematic review was conducted following PRISMA guidelines. Two independent authors searched PubMed, Web of Science, and Scopus for articles studying the association between non-enzymatic and enzymatic lipid metabolites and CVS or DCI after aSAH. Quality and risk of bias were evaluated using the Newcastle-Ottawa Scale. Extracted data included metabolite concentrations, biological sample types, timing of collection, patient demographics, clinical severity of aSAH, Fisher's grade, DCI definition, and relationship to DCI. Of 519 records screened, 17 studies were included. Lipid metabolites were measured in blood (5 studies), cerebrospinal fluid (11 studies), and urine (2 studies). F2-isoprostanes (F2-IsoPs), studied in 7 articles, were linked to increased DCI risk, with elevated levels observed within three days post-aSAH. Isofurans (IsoFs) predicted DCI risk between days 5 and 8 post-aSAH, while elevated cholesteryl ester hydroperoxide (CEOOH) levels on day 2 linked to symptomatic vasospasm. Enzymatic arachidonic acid (AA) metabolites, including 6-keto-prostaglandin F1-α, prostaglandin D2, and leukotriene C4, were also associated with early DCI risk. To the best of our knowledge, this review is the first to comprehensively assess all LPMs in relation to CVS and DCI. Elevated concentrations of F2-IsoPs and enzymatic AA derivatives may serve as biomarkers for DCI prediction in aSAH. These findings highlight the need to explore the potential of LPMs, paving the way for risk stratification and timely interventions to improve patient outcomes and aid researchers in developing predictive scoring systems for DCI. Clinical trial number Not applicable.
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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 | 0.004 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".