Articles: subarachnoid-hemorrhage.
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Cochrane Db Syst Rev · Jan 2025
Review Meta AnalysisThrombolysis for aneurysmal subarachnoid haemorrhage.
Aneurysmal subarachnoid haemorrhage continues to cause a significant burden of morbidity and mortality despite advances in care. Trials investigating local administration of thrombolytics have reported promising results. ⋯ There is some evidence that thrombolysis can probably improve outcomes after aneurysmal subarachnoid haemorrhage, without increasing the risk of haemorrhagic complications. Thrombolysis likely reduces the risk of poor functional outcome and cerebral artery vasospasm, and may reduce the risk of delayed cerebral ischaemia, but it likely makes little to no difference to case fatality or hydrocephalus, and may make little to no difference to the risk of cerebral infarction. However, the current evidence is still uncertain. The uncertainty is primarily due to the small total number of participants and outcome events. Data from further studies are required to confirm the efficacy of thrombolysis for improving outcomes after aneurysmal subarachnoid haemorrhage.
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Review Meta Analysis
Clinical Characteristics as Predictors of Early and Delayed Cerebral Infarction in Aneurysmal Subarachnoid Hemorrhage Patients: A Meta-Analysis of 4527 Cases.
Predictors of delayed cerebral infarction (DCI) and early cerebral infraction (ECI) among aneurysmal subarachnoid hemorrhage (aSAH) patients remain unclear. We aimed to systematically review and synthesize the literature on predictors of ECI and DCI among aSAH patients. ⋯ Female sex, admission disease severity, presence of vasospasm and Fisher grading can predict DCI risk post-aSAH. Significant knowledge gaps exist for ECI predictors. Further large standardized cohorts are warranted to guide prognosis and interventions.
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Meta Analysis
Effect of Statin Treatment in Patients with Aneurysmal Subarachnoid Hemorrhage: A Network Meta-Analysis.
There are knowledge gaps regarding the relative efficacy of statins for aneurysmal subarachnoid hemorrhage (aSAH). This study aims to examine the comparative effectiveness and determine the ranking of different statins with network meta‑analysis in patients with aSAH. ⋯ Simvastatin 80 mg might be the most effective intervention in reducing DCI. Additionally, short-term therapy might provide more benefits. Further research with longer follow-up is warranted to validate the current findings in patients with aSAH who are at high risk of DCI.
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Review Meta Analysis
Global Disparities in the Presentation and Management of Aneurysmal Subarachnoid Hemorrhage (aSAH): A Review and Analysis.
Aneurysmal subarachnoid hemorrhage (aSAH) is associated with high mortality rates. There is a significant gap in the literature describing global disparities in demographics, management, and outcomes among patients with aSAH. We aimed to conduct a systematic review and meta-analysis to assess global disparities in aSAH presentation and management. ⋯ In this analysis, we found similar rates of high-grade SAH hemorrhages in HIC and LIC but a lack of endovascular coil embolization treatments reported in LIC. Additional research and discussion are needed to identify reasons for treatment disparities and intervenable societal factors to improve aSAH outcomes worldwide.
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Review Meta Analysis
Machine Learning Algorithms to Predict Delayed Cerebral Ischemia After Subarachnoid Hemorrhage: A Systematic Review and Meta-analysis.
Delayed cerebral ischemia (DCI) is a common and severe complication after subarachnoid hemorrhage (SAH). Logistic regression (LR) is the primary method to predict DCI, but it has low accuracy. This study assessed whether other machine learning (ML) models can predict DCI after SAH more accurately than conventional LR. ⋯ For ML models, the pooled sensitivity was 0.74 (95% CI 0.61-0.86; p < 0.01) and the pooled specificity was 0.78 (95% CI 0.71-0.86; p = 0.02). Our results suggest that ML algorithms performed better than conventional LR at predicting DCI. Trial Registration: PROSPERO (International Prospective Register of Systematic Reviews) CRD42023441586; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=441586.