Hyponatremia and cerebral vasospasm in subarachnoid hemorrhage: a systematic review and meta-analysis
Bibliographic record
Abstract
Background Hyponatremia, defined as serum sodium < 135 mEq/L, is a common complication following aneurysmal subarachnoid hemorrhage (aSAH) and has been implicated in the development of cerebral vasospasm, a significant contributor to delayed cerebral ischemia and poor neurological outcomes. However, the strength and consistency of this association remain unclear. This study aimed to evaluate the relationship between hyponatremia and angiographically or radiologically confirmed vasospasm in patients with aSAH.Method A comprehensive search of PubMed, Scopus, Embase, and Medline was conducted through July 2025, adhering to PRISMA guidelines (CRD42024621575). Eligible studies included adult or pediatric patients with aSAH, reported serum sodium levels, and documented vasospasm confirmed by imaging. Data were extracted independently by three reviewers, and methodological quality was assessed using a modified Newcastle-Ottawa Scale. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated using a random-effects model. Heterogeneity and publication bias were assessed using I2 statistics and funnel plots, respectively.Results Seven studies comprising a total of 983 patients were included in both the systematic review and meta-analysis. Among these, 403 patients developed vasospasm, with 243 having experienced hyponatremia prior to the event. The pooled analysis demonstrated a significant association between hyponatremia and vasospasm (OR = 2.59; 95% CI: 1.60–4.20; p = 0.0001). Moderate heterogeneity was observed (I2 = 53%), and no evidence of publication bias was detected.Conclusion Hyponatremia is significantly associated with increased risk of cerebral vasospasm in SAH patients. Serum sodium may suggest potential as a component of risk stratification models. Prospective studies are needed to explore causality and the therapeutic impact of sodium correction on clinical outcomes.
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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 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.034 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 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".