Stroke

Stroke is a preventable and treatable disease. It can present with the sudden onset of any neurological disturbance, including limb weakness or numbness, speech disturbance, visual loss or disturbance of balance. Over the last two decades, a growing body of evidence has overturned the traditional perception that stroke is simply a consequence of aging which inevitably results in death or severe disability. Evidence is accumulating for more effective primary and secondary prevention strategies, better recognition of people at highest risk and thus most in need of active intervention, interventions that are effective so on after the onset of symptoms, and an understanding of the processes of care that contribute to a better outcome. In addition, there is now good evidence to support interventions and care processes in stroke rehabilitation. In the UK, the National Sentinel Stroke Audits 2,3 have documented changes in secondary care provision over the last 10 years, with increasing numbers of patients being treated in stroke units, more evidence-based practice, and reductions in mortality and length of stay. In order for evidence from research studies to improve outcomes for patients, it needs to be put into practice. National guidelines provide clinicians, managers and service users with summaries of evidence and recommendations for clinical practice. Implementation of guidelines in practice, supported by regular audit, improves the processes of care and clinical outcome. This guideline covers interventions in the acute stage of a stroke (‘acute stroke’) or transient ischaemic attack (TIA). Most of the evidence considered relates to interventions in the first 48 hours after onset of symptoms, although some interventions of up to 2 weeks are covered as well. This guideline is a stand-alone document, but is designed to be read alongside the Intercollegiate Stroke Working Party guideline ‘National clinical guideline for stroke’* which considers evidence for interventions from the acute stage into rehabilitation and life after stroke. The Intercollegiate Stroke Working Party guideline is an update of the 2004 2nd edition and includes all the recommendations contained within this guideline. This acute stroke and TIA guideline is also designed to be read alongside the Department of Health’s (DH) ‘National stroke strategy’ (NSS). Where there are differences between the recommendations made within this acute stroke and TIA guideline and the NSS, the Guideline Development Group (GDG) members feel that their recommendations are derived from systematic methodology to identify all of the relevant literature.

Structure and classification of zoophytes. By James D. Dana.

c. 2

Enhancing text classification to improve information filtering

Text classification, information filtering, semi-supervised learning, quality control

Partially supervised learning of fuzzy classification rules

Fuzzy classification, semi-supervised learning, data mining

Validation of the Killip-Kimball Classification and Late Mortality after Acute Myocardial Infarction

Background: The classification or index of heart failure severity in patients with acute myocardial infarction (AMI) was proposed by Killip and Kimball aiming at assessing the risk of in-hospital death and the potential benefit of specific management of care provided in Coronary Care Units (CCU) during the decade of 60. Objective: To validate the risk stratification of Killip classification in the long-term mortality and compare the prognostic value in patients with non-ST-segment elevation MI (NSTEMI) relative to patients with ST-segment elevation MI (STEMI), in the era of reperfusion and modern antithrombotic therapies. Methods: We evaluated 1906 patients with documented AMI and admitted to the CCU, from 1995 to 2011, with a mean follow-up of 05 years to assess total mortality. Kaplan-Meier (KM) curves were developed for comparison between survival distributions according to Killip class and NSTEMI versus STEMI. Cox proportional regression models were developed to determine the independent association between Killip class and mortality, with sensitivity analyses based on type of AMI. Results: The proportions of deaths and the KM survival distributions were significantly different across Killip class >1 (p <0.001) and with a similar pattern between patients with NSTEMI and STEMI. Cox models identified the Killip classification as a significant, sustained, consistent predictor and independent of relevant covariables (Wald χ2 16.5 [p = 0.001], NSTEMI) and (Wald χ2 11.9 [p = 0.008], STEMI). Conclusion: The Killip and Kimball classification performs relevant prognostic role in mortality at mean follow-up of 05 years post-AMI, with a similar pattern between NSTEMI and STEMI patients.

Prototype-based classification and clustering

Magdeburg, Univ., Fak. für Informatik, Habil.-Schr., 2006