Clinical impact of leukoaraiosis burden and chronological age on neurological deficit recovery and 90-day outcome after minor ischemic stroke

BACKGROUND AND AIMS: Ischemic stroke remains a leading cause of disability, particularly among the elderly, but this association has not been consistently noted among patients with minor stroke. We sought to determine the association of chronological age and leukoaraiosis, which is considered a marker of biological age, with the degree of neurological deficit recovery and 90-day disability after minor ischemic stroke. METHODS: We retrospectively analyzed 185 patients with a minor ischemic stroke (National Institutes of Health Stroke Scale [NIHSS] score \u3c /=5). Leukoaraiosis severity was graded according to the van Swieten scale. NIHSS was assessed at baseline, discharge, and 90-days. Multivariable linear and ordinal logistic regression analyses were constructed to identify independent predictors of the degree of NIHSS-improvement (DeltaNIHSS) and 90-day outcome as assessed by the modified Rankin Scale (mRS). RESULTS: Patients with severe leukoaraiosis had attenuated DeltaNIHSS at 90days as compared to patients with none-to-mild leukoaraiosis (p=0.028). After adjustment, leukoaraiosis severity (p \u3c 0.001) but not chronological age (p=0.771) was independently associated with the DeltaNIHSS by day 90. Severe leukoaraiosis (p=0.003, OR 3.1, 95%-CI 1.5-6.4), older age (p=0.001, OR 1.0 95%-CI 1.0-1.1), and admission NIHSS (p \u3c 0.001, OR 1.5, 95%-CI 1.2-1.8) were independent predictors of the 90-day mRS. CONCLUSION: Leukoaraiosis is a more sensitive predictor for neurological deficit recovery after ischemic stroke than chronological age. Further study is required to establish the specific contribution of leukoaraiosis to functional outcome after minor ischemic stroke beyond its impact on recovery mechanisms

Reducing the Cost of Protein Identifications from Mass Spectrometry Databases

mass spectrometry, machine learning, workflow management, noise filtering We present two techniques to improve the computational efficiency of protein discovery from mass spectrometry databases: noise filtering and hierarchical searching. Our approaches are orthogonal to existing algorithms and are based on the observation that typical mass spectrometry data contains a large amount of noise that can lead to wasteful computation. Our first improvement uses standard machine learning techniques with novel feature vectors derived from the mass spectra to identify and filter the noisy spectra. We demonstrate this approach results in computational gains of around 38 % with less than 10 % loss of peptides. Additionally we present a hierarchical searching scheme in which most samples are matched against a small database at low computational cost, leaving only a small number of samples to be searched against larger databases. Combining this scheme with the machine learning filters leads to a further performance improvement o

12 versus 24 h bed rest after acute ischemic stroke thrombolysis: a preliminary experience

BACKGROUND: The practice of \u3e /=24 h of bed rest after acute ischemic stroke thrombolysis is common among hospitals, but its value compared to shorter periods of bed rest is unknown. METHODS: Consecutive adult patients with a diagnosis of ischemic stroke who had received intravenous thrombolysis treatment from 1/1/2010 until 4/13/2016, identified from the local ischemic stroke registry, were included. Standard practice bed rest for \u3e /=24 h, the protocol prior to 1/27/2014, was retrospectively compared with standard practice bed rest for \u3e /=12 h, the protocol after that date. The primary outcome was favorable discharge location (defined as home, home with services, or acute rehabilitation). Secondary outcome measures included incidence of pneumonia, NIHSS at discharge, and length of stay. RESULTS: 392 patients were identified (203 in the \u3e /=24 h group, 189 in the \u3e /=12 h group). There was no significant difference in favorable discharge outcome in the \u3e /=24 h bed rest protocol compared with the \u3e /=12 h bed rest protocol in multivariable logistic regression analysis (76.2% vs. 70.9%, adjusted OR 1.20 CI 0.71-2.03). Compared with the \u3e /=24 h bed rest group, pneumonia rates (8.3% versus 1.6%, adjusted OR 0.12 CI 0.03-0.55), median discharge NIHSS (3 versus 2, adjusted p = .034), and mean length of stay (5.4 versus 3.5 days, adjusted p = .006) were lower in the \u3e /=12 h bed rest group. CONCLUSION: Compared with \u3e /=24 h bed rest, \u3e /=12 h bed rest after acute ischemic stroke reperfusion therapy appeared to be similar. A non-inferiority randomized trial is needed to verify these findings

Natural Human-Human-System Interaction

The importance of a vision can be that of providing a model within which we think and create. If the model is outdated, thinking becomes unduly constrained. The paper proposes to replace the paradigm of human-computer interaction (HCI) with a more comprehensive model for thinking about future systems and interfaces. Recent progress in speech technologies has managed to establish a powerful application paradigm, i.e. that of natural task-oriented spoken language dialogue systems. This application paradigm points towards the broader goal of natural humanhuman -system interaction (HHSI) in virtual, combined virtual and physical, and physical environments. On the backdrop of the natural HHSI model and the rapidly changing environment of advanced systems research, the types of research that are likely to be needed in the future are discussed. The discussion deliberately de-emphasises next-generation systems research in order to shift the focus to a range of equally important, existing or emerging research objectives which sometimes show a tendency to be overshadowed by the next-generation challenges