Outcome after aneurysmal subarachnoid haemorrhage: the use of a graphical model in the assessment of risk factors.

Abstract

In 102 consecutive prospectively identified patients with subarachnoid haemorrhage (SAH) we have analysed the severity of the initial haemorrhage and the direct and indirect effects of adverse factors on outcome. The data we recorded included delay in diagnosis, risk groups, Doppler measurements, angiographic findings, surgical events and outcome at 1 year. By using a temporal graphical chain model, the associations between all variables and possible causal pathways were statistically determined. The severity of the initial haemorrhage, as determined by means of a clinical assessment and CT scanning, allowed low-, medium- and high-risk patient groups and a statistically predictable outcome to be identified. The overall management mortality was 13.7% at 1 year; 70.6% had a favourable outcome and 15.7% were severely disabled. Outcome was directly associated with risk group (p = 0.0038) and rebleeding (p = 0.0000). Delayed diagnosis led to a poorer outcome (p = 0.014)--an indirect association probably due to rebleeding. Adverse surgical events led to a significantly poorer outcome in high-risk patients. No significant relationship was found either between age and risk group (p = 0.7784) or between age and outcome (p = 0.6418). Preoperative clinical (WFNS) grade was unreliable in predicting outcome. It is the particular risk group, determined by the initial SAH, that indicates the individual patient's outcome. Management strategies can reduce preventable adverse events such diagnostic delay and rebleeding. Future studies should stratify patients according to risk group, delay in diagnosis and rebleeding in order to enable a clearer comparison to be made of treatment methods.