Grading Scales for Subarachnoid Hemorrhage - Animal Models of Acute Neurological Injuries: Injury and Mechanistic Assessments - page 279

Chapter 19
Grading Scales for Subarachnoid Hemorrhage
Andrew Losiniecki and Mario Zuccarello
Abstract
There are numerous grading scales for subarachnoid hemorrhage (SAH) that are in use today. They
attempt to subdivide patients into groups based on both clinical and radiographic fi ndings. Some of the
scales in common use include variables that account for the amount and location of hemorrhage, initial
neurological status, and accompanying neurological symptoms. The value of grading scales can be assessed
for their ability to predict functional outcomes, estimate surgical risk and to provide a risk assessment for
the development of cerebral vasospasm. Most scales have been derived retrospectively and intra-operator
variability in assigning scores is inherent in any scoring system. As more and more information is included
in a grading scale, they become more diffi cult to use and interpret while providing only slightly increased
information on outcome in comparison to some single variable systems. The review that follows provides
information on the foundations of those scales in common use today and provides a suggestion on the
future direction of SAH grading scales.
Key words: Intracerebral hemorrhage, Minimally invasive neurosurgery, Surgical techniques
1. Introduction
The diagnosis of aneurysmal (SAH) carries with it a wide range of
presenting neurological conditions and potential outcomes. Early
stratifi cation of patients based on presenting symptoms can be
important to help guide timing of potential treatment options as
well as providing information to the patient or their family on
probable clinical course. It is oftentimes the unpredictable and unex-
pected pulmonary embolus, pneumonia, or severe systemic infection
that can lead to a signifi cant amount of hospital morbidity and mor-
tality. The ability of any scale to predict these seemingly unexpected
complications is probably much like predicting where lightening
will strike and is diffi cult if not impossible and likely provide some
of the inaccuracy in those predictive scales in use today.