Predictive Model for the Occurrence of Cerebral Vasospasm Complicating Subarachnoid Haemorrhage by Combined Analysis of the Kinetics of a Panel of Biomarkers.

Subarachnoid hemorrhage (SAH) is the rupture of a cerebral aneurysm, resulting in bleeding into the subarachnoid space.

This condition has significant morbidity and mortality. The patient's functional outcome is primarily determined by the severity of cerebral ischemic lesions that develop during the first few weeks after the acute phase. The main focus of resuscitation management in patients are the 'delayed ischemic lesions'. These lesions are caused by various phenomena, with vasospasm being the most common mechanism. The caliber of cerebral arteries will shrink, reducing the blood flow delivered to the parenchyma, leading to a deficit of energy metabolites in neurons and causing their death. This complication typically occurs within a well-defined time frame, ranging from 3 to 21 days after bleeding, and peaking around the seventh day.

The objective of this study is to create a novel predictive method for symptomatic vasospasm. This method will incorporate routine clinical and radiological biomarkers, as well as innovative biological assays. The aim is to enable earlier diagnosis and even pre-emptive treatment of this pathology.

Several studies have examined the predictive potential of various blood biomarkers for neurological prognosis and the incidence of delayed brain damage in patients. These studies have demonstrated strong associations between them. For instance, one study found that patients with the most severe vasospasm had a significantly higher peak in cerebrospinal fluid of several biomarkers associated with neurodegeneration, such as Neuron Specific Enolase (NSE). Additionally, the plasma concentration-time curves demonstrated simultaneous elevations during periods of vasospasm.

However, no study has examined the practical clinical use of these biomarkers during hospitalization to predict the occurrence of vasospasm on a daily basis or at specific times of interest. This is particularly important as the pathophysiological time sequence appears to be common to all patients. A single study has attempted to establish a predictive algorithm for delayed cerebral lesions, achieving a certain degree of effectiveness (over 90% correct predictions and sensitivity of around 93%), by combining a single biomarker assay and clinical parameters. However, this study only focuses on ischemic lesions at 6 weeks and cannot be used to guide therapy during initial management.