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Individuals with post-stroke aphasia tend to recover their language to some extent; however, it remains challenging to reliably predict the nature and extent of recovery that will occur in the long term. The aim of this study was to quantitatively predict language outcomes in the first year of recovery from aphasia across multiple domains of language and at multiple timepoints post-stroke. We recruited 217 patients with aphasia following acute left hemisphere ischaemic or haemorrhagic stroke and evaluated their speech and language function using the Quick Aphasia Battery acutely and then acquired longitudinal follow-up data at up to three timepoints post-stroke: 1 month (n = 102), 3 months (n = 98) and 1 year (n = 74). We used support vector regression to predict language outcomes at each timepoint using acute clinical imaging data, demographic variables and initial aphasia severity as input. We found that ∼60% of the variance in long-term (1 year) aphasia severity could be predicted using these models, with detailed information about lesion location importantly contributing to these predictions. Predictions at the 1- and 3-month timepoints were somewhat less accurate based on lesion location alone, but reached comparable accuracy to predictions at the 1-year timepoint when initial aphasia severity was included in the models. Specific subdomains of language besides overall severity were predicted with varying but often similar degrees of accuracy. Our findings demonstrate the feasibility of using support vector regression models with leave-one-out cross-validation to make personalized predictions about long-term recovery from aphasia and provide a valuable neuroanatomical baseline upon which to build future models incorporating information beyond neuroanatomical and demographic predictors.

ObjectiveBroca's aphasia is a syndrome of impaired fluency with retained comprehension. The authors used an unbiased algorithm to examine which neuroanatomical areas are most likely to result in Broca's aphasia following surgical lesions.MethodsPatients were prospectively evaluated with standardized language batteries before and after surgery. Broca's area was defined anatomically as the pars opercularis and triangularis of the inferior frontal gyrus. Broca's aphasia was defined by the Western Aphasia Battery language assessment. Resections were outlined from MRI scans to construct 3D volumes of interest. These were aligned using a nonlinear transformation to Montreal Neurological Institute brain space. A voxel-based lesion-symptom mapping (VLSM) algorithm was used to test for areas statistically associated with Broca's aphasia when incorporated into a resection, as well as areas associated with deficits in fluency independent of Western Aphasia Battery classification. Postoperative MRI scans were reviewed in blinded fashion to estimate the percentage resection of Broca's area compared to areas identified using the VLSM algorithm.ResultsA total of 289 patients had early language evaluations, of whom 19 had postoperative Broca's aphasia. VLSM analysis revealed an area that was highly correlated (p < 0.001) with Broca's aphasia, spanning ventral sensorimotor cortex and supramarginal gyri, as well as extending into subcortical white matter tracts. Reduced fluency scores were significantly associated with an overlapping region of interest. The fluency score was negatively correlated with fraction of resected precentral, postcentral, and supramarginal components of the VLSM area.ConclusionsBroca's aphasia does not typically arise from neurosurgical resections in Broca's area. When Broca's aphasia does occur after surgery, it is typically in the early postoperative period, improves by 1 month, and is associated with resections of ventral sensorimotor cortex and supramarginal gyri.

After a stroke, individuals with aphasia often recover to a certain extent over time. This recovery process may be dependent on the health of surviving brain regions. Leukoaraiosis (white matter hyperintensities on MRI reflecting cerebral small vessel disease) is one indication of compromised brain health and is associated with cognitive and motor impairment. Previous studies have suggested that leukoaraiosis may be a clinically relevant predictor of aphasia outcomes and recovery, although findings have been inconsistent. We investigated the relationship between leukoaraiosis and aphasia in the first year after stroke. We recruited 267 patients with acute left hemispheric stroke and coincident fluid attenuated inversion recovery MRI. Patients were evaluated for aphasia within 5 days of stroke, and 174 patients presented with aphasia acutely. Of these, 84 patients were evaluated at ∼3 months post-stroke or later to assess longer-term speech and language outcomes. Multivariable regression models were fit to the data to identify any relationships between leukoaraiosis and initial aphasia severity, extent of recovery, or longer-term aphasia severity. We found that leukoaraiosis was present to varying degrees in 90% of patients. However, leukoaraiosis did not predict initial aphasia severity, aphasia recovery, or longer-term aphasia severity. The lack of any relationship between leukoaraiosis severity and aphasia recovery may reflect the anatomical distribution of cerebral small vessel disease, which is largely medial to the white matter pathways that are critical for speech and language function.

Classical models have traditionally focused on the left posterior inferior frontal gyrus (Broca's area) as a key region for motor planning of speech production. However, converging evidence suggests that it is not critical for either speech motor planning or execution. Alternative cortical areas supporting high-level speech motor planning have yet to be defined. In this review, we focus on the precentral gyrus, whose role in speech production is often thought to be limited to lower-level articulatory muscle control. In particular, we highlight neurosurgical investigations that have shed light on a cortical region anatomically located near the midpoint of the precentral gyrus, hence called the middle precentral gyrus (midPrCG). The midPrCG is functionally located between dorsal hand and ventral orofacial cortical representations and exhibits unique sensorimotor and multisensory functions relevant for speech processing. This includes motor control of the larynx, auditory processing, as well as a role in reading and writing. Furthermore, direct electrical stimulation of midPrCG can evoke complex movements, such as vocalization, and selective injury can cause deficits in verbal fluency, such as pure apraxia of speech. Based on these findings, we propose that midPrCG is essential to phonological-motoric aspects of speech production, especially syllabic-level speech sequencing, a role traditionally ascribed to Broca's area. The midPrCG is a cortical brain area that should be included in contemporary models of speech production with a unique role in speech motor planning and execution.

PurposeCommunity aphasia groups serve an important purpose in enhancing the quality of life and psychosocial well-being of individuals with chronic aphasia. Here, we describe the Aphasia Group of Middle Tennessee, a community aphasia group with a 17-year (and continuing) history, housed within Vanderbilt University Medical Center in Nashville, Tennessee.MethodWe describe in detail the history, philosophy, design, curriculum, and facilitation model of this group. We also present both quantitative and qualitative outcomes from group members and their loved ones.ResultsGroup members and their loved ones alike indicated highly positive assessments of the format and value of the Aphasia Group of Middle Tennessee.ConclusionBy characterizing in detail the successful Aphasia Group of Middle Tennessee, we hope this can serve as a model for clinicians interested in starting their own community aphasia groups, in addition to reaching individuals living with chronic aphasia and their loved ones through the accessible and aphasia-friendly materials provided with this clinical focus article.

Amid digital transformation, property valuation innovations (PVIs) can enhance professional service firms' (PSFs) operations. Meanwhile, literature suggests that some PSFs and property professionals are sceptical about the relevance of some PVIs because of compatibility, performance, complexity, and relative advantage issues. Such concerns affect PSFs and property professionals' decisions to adopt PVIs. While property literature is replete with evidence about the development phase of the innovation life cycle, little is known about how to aid PSFs and property professionals' innovation-decision processes. To help address these concerns, we adopted a non-systematic literature review approach to critically review Rogers (2003) Diffusion of Innovation (DOI) theory. The DOI theory is widely reported to successfully predict the adoption of emerging innovations within a social network. Based on Rogers' innovation-decision process, we proposed a dynamic process model to help bridge the innovation-adoption gap in the property profession. The conceptual model advocates collaboration between PVI developers and potential users to address adoption and engagement challenges through the innovation life cycle. The framework provides insights that can aid researchers, educators, and professional bodies in evaluating suitable ways to promote digital innovations as decision support systems to facilitate data management amid the digital revolution. [ABSTRACT FROM AUTHOR]

There is a rich tradition of research on the neuroanatomical correlates of spoken language production in aphasia using constrained tasks (e.g. picture naming), which offer controlled insights into the distinct processes that govern speech and language (i.e. lexical-semantic access, morphosyntactic construction, phonological encoding, speech motor programming/execution). Yet these tasks do not necessarily reflect everyday language use. In contrast, naturalistic language production (also referred to as 'connected speech' or 'discourse') more closely approximates typical processing demands, requiring the dynamic integration of all aspects of speech and language. The brain bases of naturalistic language production remain relatively unknown, however, in part because of the difficulty in deriving features that are salient, quantifiable and interpretable relative to both speech-language processes and the extant literature. The present cross-sectional observational study seeks to address these challenges by leveraging a validated and comprehensive auditory-perceptual measurement system that yields four explanatory dimensions of performance—Paraphasia (misselection of words and sounds), Logopenia (paucity of words), Agrammatism (grammatical omissions) and Motor speech (impaired speech motor programming/execution). We used this system to characterize naturalistic language production in a large and representative sample of individuals with acute post-stroke aphasia (n = 118). Scores on each of the four dimensions were correlated with lesion metrics, and multivariate associations among the dimensions and brain regions were then explored. Our findings revealed distinct yet overlapping neuroanatomical correlates throughout the left-hemisphere language network. Paraphasia and logopenia were associated primarily with posterior regions, spanning both dorsal and ventral streams, which are critical for lexical-semantic access and phonological encoding. In contrast, agrammatism and motor speech were associated primarily with anterior regions of the dorsal stream that are involved in morphosyntactic construction and speech motor planning/execution, respectively. Collectively, we view these results as constituting a brain–behaviour model of naturalistic language production in aphasia, aligning with both historical and contemporary accounts of the neurobiology of spoken language production. [ABSTRACT FROM AUTHOR]

A 17-year-old female was diagnosed with inflammatory bowel disease and started on infliximab. A few weeks after starting infliximab, she developed a recurrence of daily fevers associated with an intermittent dry cough, which worsened over the course of a month. A chest radiograph, abdominal ultrasound, and computed tomography scan of the chest and abdomen revealed a heterogeneous spleen with multiple hyperechoic areas, tiny splenic micronodules, and diffuse micronodularity throughout the lungs. She was transferred to a tertiary care hospital because of hypotension, new oxygen requirements, and ongoing fever. Her bloodwork on presentation to tertiary care revealed pancytopenia and elevated inflammatory markers; she had splenomegaly on MRI. As her clinical picture evolved, she continued to have persistent fevers and anorexia despite ongoing management. Infectious diseases, rheumatology, and gastroenterology were consulted to guide the evaluation and management of this patient's complex clinical course. [ABSTRACT FROM AUTHOR]

Digitalisation is causing significant changes in professional practices and has profound impacts on skills requirements in the service industry. Demand for jobs that require soft skills but do not involve routine processes will be high, while jobs that involve routine processes will be lost or facilitated by technology. In both instances, professionals must acquire complementary skills to operate effectively. As a service profession, valuation is set to undergo changes requiring a shift in valuers' mindsets towards data-driven technologies. Therefore, this study aims to reveal the additional skills valuers need due to digitalisation and the approaches used to acquire these skills. The study used a qualitative approach and analysed practising valuers' perspectives. The study's findings indicate that information technology, time management, interpersonal, and conceptual skills are crucial for valuation practice, and practising valuers acquire these skills through personal-level or corporate-level approaches. The findings provide insights regarding knowledge gaps that require coordinated efforts from professional bodies, training institutions, and policymakers to bridge. Collaboration between institutions is necessary to ensure that the valuation profession can transition smoothly into the digital world to continue to assure society of quality valuations for a stable global economic development. [ABSTRACT FROM AUTHOR]

Background Integrating artificial intelligence (AI) in healthcare settings has the potential to benefit clinical decision-making. Addressing challenges such as ensuring trustworthiness, mitigating bias, and maintaining safety is paramount. The lack of established methodologies for pre- and post-deployment evaluation of AI tools regarding crucial attributes such as transparency, performance monitoring, and adverse event reporting makes this situation challenging. Objectives This paper aims to make practical suggestions for creating methods, rules, and guidelines to ensure that the development, testing, supervision, and use of AI in clinical decision support (CDS) systems are done well and safely for patients. Materials and Methods In May 2023, the Division of Clinical Informatics at Beth Israel Deaconess Medical Center and the American Medical Informatics Association co-sponsored a working group on AI in healthcare. In August 2023, there were 4 webinars on AI topics and a 2-day workshop in September 2023 for consensus-building. The event included over 200 industry stakeholders, including clinicians, software developers, academics, ethicists, attorneys, government policy experts, scientists, and patients. The goal was to identify challenges associated with the trusted use of AI-enabled CDS in medical practice. Key issues were identified, and solutions were proposed through qualitative analysis and a 4-month iterative consensus process. Results Our work culminated in several key recommendations: (1) building safe and trustworthy systems; (2) developing validation, verification, and certification processes for AI-CDS systems; (3) providing a means of safety monitoring and reporting at the national level; and (4) ensuring that appropriate documentation and end-user training are provided. Discussion AI-enabled Clinical Decision Support (AI-CDS) systems promise to revolutionize healthcare decision-making, necessitating a comprehensive framework for their development, implementation, and regulation that emphasizes trustworthiness, transparency, and safety. This framework encompasses various aspects including model training, explainability, validation, certification, monitoring, and continuous evaluation, while also addressing challenges such as data privacy, fairness, and the need for regulatory oversight to ensure responsible integration of AI into clinical workflow. Conclusions Achieving responsible AI-CDS systems requires a collective effort from many healthcare stakeholders. This involves implementing robust safety, monitoring, and transparency measures while fostering innovation. Future steps include testing and piloting proposed trust mechanisms, such as safety reporting protocols, and establishing best practice guidelines. [ABSTRACT FROM AUTHOR]

Author(s): Charushree Prasad [sup.1] , Deborah M. Levy [sup.2] [sup.3] , Diane Hebert [sup.1] [sup.3] , Rose Chami [sup.4] [sup.5] , Chia Wei Teoh [sup.1] [sup.3] Author Affiliations: (1) grid.42327.30, [...]