Introduction

Over recent decades the early management of acute stroke has changed dramatically and the early post-stroke period has been the focus of much research. With advances in pharmacotherapeutics, and on the basis of many randomized controlled trials, the potential interventions now available within the first 24–48 hours following acute stroke are numerous.

This chapter will present the evidence and best practice guidance for interventions during the first 24–48 hours following stroke, based upon the European Stroke Organisation Guidelines 2008 and the European Stroke Initiative recommendations for the management of intracranial hemorrhage [1,2]. For the purposes of this chapter, the interventions discussed will generally be limited to the initial 48 hours following ictus. Access to some of these therapies may not be universal and may be dictated by local availability at individual stroke units. As with other aspects of stroke care, however, close cooperation and inter-disciplinary communication are essential.

Thrombolysis

In respect of acute interventions, one of the most significant advances during the last two decades has been the introduction of intravenous thrombolysis as a standard therapy for a well-selected population of patients with acute ischemic stroke. At present, the only thrombolytic agent licensed in Europe for the treatment of ischemic stroke is recombinant-tissue plasminogen activator (rtPA), alteplase.

Introduction

The experimental basis for neuroprotection is well founded. In a range of animal models of ischemic stroke, drugs acting by a variety of mechanisms can be administered up to several hours after the ischemic insult and reductions in infarct volume can be demonstrated. Whilst individual models have their proponents and their disadvantages, numerous strategies have been sufficiently convincing to encourage clinical development. Examples of drugs reaching large clinical trials range from free radical scavengers, γ-aminobutyric acid (GABA) agonists and calcium antagonists, through a range of drugs acting on the glutamate cascade to precursors of membrane constituents such as citicoline. Unfortunately, the range of drugs and mechanisms that has been tested in the clinic and has so far failed, exactly parallels the former list (Table 35.1). In most cases, the result has been neutral but a few drugs had adverse effects that were not anticipated from the preclinical studies.

In the face of these disappointments, some pessimism amongst the clinical researchers would be understandable, but instead a cautious optimism remains. This is based on sound scientific analysis of the progress that has been made and the prospects for adjusting the development strategy for future compounds.

Potential reasons for the failure of previous clinical trials have been widely reviewed. Most are speculative, but the principles that underlie them can readily be tested and bear repetition. First, the translation from animal models to human stroke demands certain assumptions.

Introduction

apprentice n. Learner of a craft. [Old French apprendre]

In the field of clinical decision-making, a decision aid that is able to continue to learn from ‘experience’ is likely to have an advantage over one which is not. For instance, a system that is developed from data gathered at one location should be able, safely, to tune in to local conditions, for example demography elsewhere. Similarly, as practice or technology changes, such changes should be accommodated by the device itself, rather than by having to involve statisticians, knowledge engineers, etc. to rederive algorithms. After all, when doctors change hospital they are not subjected to complete retraining. Neither should a computerized decision aid have to be. Of course, this assumes the need for such systems in the first place, which is a wider question not addressed here. We use the analogy of an apprentice to motivate development of systems that learn in perpetuity.

Expert systems are characterized by the processes of rule elicitation, rule-base development and inference. Knowledge, in the form of rules, is built into the system a priori and, once embedded, remains unchanged throughout the lifetime of the system, unless a knowledge engineer intervenes. Conclusions are drawn by a deductive process. As a model of human expert behaviour this has some drawbacks because it presupposes that once individuals have achieved expert status they no longer continue to learn from their experience.