Cognitive and mood assessment tools for use in stroke

No abstract available

Risk factors for chest infection in acute stroke: a prospective cohort study

<p><b>Background and Purpose:</b> Pneumonia is a major cause of morbidity and mortality after stroke. We aimed to determine key characteristics that would allow prediction of those patients who are at highest risk for poststroke pneumonia.</p> <p><b>Methods:</b> We studied a series of consecutive patients with acute stroke who were admitted to hospital. Detailed evaluation included the modified National Institutes of Health Stroke Scale; the Abbreviated Mental Test; and measures of swallow, respiratory, and oral health status. Pneumonia was diagnosed by set criteria. Patients were followed up at 3 months after stroke.</p> <p><b>Results:</b> We studied 412 patients, 391 (94.9%) with ischemic stroke and 21 (5.1%) with hemorrhagic stroke; 78 (18.9%) met the study criteria for pneumonia. Subjects who developed pneumonia were older (mean±SD age, 75.9±11.4 vs 64.9±13.9 years), had higher modified National Institutes of Health Stroke Scale scores, a history of chronic obstructive pulmonary disease, lower Abbreviated Mental Test scores, and a higher oral cavity score, and a greater proportion tested positive for bacterial cultures from oral swabs. In binary logistic-regression analysis, independent predictors (P<0.05) of pneumonia were age >65 years, dysarthria or no speech due to aphasia, a modified Rankin Scale score ≥4, an Abbreviated Mental Test score <8, and failure on the water swallow test. The presence of 2 or more of these risk factors carried 90.9% sensitivity and 75.6% specificity for the development of pneumonia.</p> <p><b>Conclusions:</b> Pneumonia after stroke is associated with older age, dysarthria/no speech due to aphasia, severity of poststroke disability, cognitive impairment, and an abnormal water swallow test result. Simple assessment of these variables could be used to identify patients at high risk of developing pneumonia after stroke.</p&gt

No Loving Voice to Cheer

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She Was Born In Old Virginia

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The purpose of rating quality of evidence differs in an overview, as compared to guidelines or recommendations

No abstract available

An algorithm was developed to assign GRADE levels of evidence to comparisons within systematic reviews

Objectives: One recommended use of the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach is supporting quality assessment of evidence of comparisons included within a Cochrane overview of reviews. Within our overview, reviewers found that current GRADE guidance was insufficient to make reliable and consistent judgments. To support our ratings, we developed an algorithm to grade quality of evidence using concrete rules. Methods: Using a pragmatic, exploratory approach, we explored the challenges of applying GRADE levels of evidence and developed an algorithm to applying GRADE levels of evidence in a consistent and transparent approach. Our methods involved application of algorithms and formulas to samples of reviews, expert panel discussion, and iterative refinement and revision. Results: The developed algorithm incorporated four key criteria: number of participants, risk of bias of trials, heterogeneity, and methodological quality of the review. A formula for applying GRADE level of evidence from the number of downgrades assigned by the algorithm was agreed. Conclusion: Our algorithm which assigns GRADE levels of evidence using a set of concrete rules was successfully applied within our Cochrane overview. We propose that this methodological approach has implications for assessment of quality of evidence within future evidence syntheses