In the early stages of neurodegenerative disorders, individuals may exhibit a decline in language abilities that is difficult to quantify with standardized tests. Careful analysis of connected speech can provide valuable information about a patient's language capacities. To date, this type of analysis has been limited by its time-consuming nature. In this study, we present a method for evaluating and classifying connected speech in primary progressive aphasia using computational techniques. Syntactic and semantic features were automatically extracted from transcriptions of narrative speech for three groups: semantic dementia (SD), progressive nonfluent aphasia (PNFA), and healthy controls. Features that varied significantly between the groups were used to train machine learning classifiers, which were then tested on held-out data. We achieved accuracies well above baseline on the three binary classification tasks. An analysis of the influential features showed that in contrast with controls, both patient groups tended to use words which were higher in frequency (especially nouns for SD, and verbs for PNFA). The SD patients also tended to use words (especially nouns) that were higher in familiarity, and they produced fewer nouns, but more demonstratives and adverbs, than controls. The speech of the PNFA group tended to be slower and incorporate shorter words than controls. The patient groups were distinguished from each other by the SD patients' relatively increased use of words which are high in frequency and/or familiarity.

The 2019 update of the Canadian Stroke Best Practice Recommendations (CSBPR) for Mood, Cognition and Fatigue following Stroke is a comprehensive set of evidence-based guidelines addressing three important issues that can negatively impact the lives of people who have had a stroke. These include post-stroke depression and anxiety, vascular cognitive impairment, and post-stroke fatigue. Following stroke, approximately 20% to 50% of all persons may be affected by at least one of these conditions. There may also be overlap between conditions, particularly fatigue and depression. If not recognized and treated in a timely matter, these conditions can lead to worse long-term outcomes. The theme of this edition of the CSBPR is Partnerships and Collaborations, which stresses the importance of integration and coordination across the healthcare system to ensure timely and seamless care to optimize recovery and outcomes. Accordingly, these recommendations place strong emphasis on the importance of timely screening and assessments, and timely and adequate initiation of treatment across care settings. Ideally, when screening is suggestive of a mood or cognition issue, patients and families should be referred for in-depth assessment by healthcare providers with expertise in these areas. As the complexity of patients treated for stroke increases, continuity of care and strong communication among healthcare professionals, and between members of the healthcare team and the patient and their family is an even bigger imperative, as stressed throughout the recommendations, as they are critical elements to ensure smooth transitions from acute care to active rehabilitation and reintegration into their community.

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