Training community resource center and clinic personnel to prompt patients in listing questions for doctors: Follow-up interviews about barriers and facilitators to the implementation of consultation planning

BackgroundVisit preparation interventions help patients prepare to meet with a medical provider. Systematic reviews have found some positive effects, but there are no reports describing implementation experiences. Consultation Planning (CP) is a visit preparation technique in which a trained coach or facilitator elicits and documents patient questions for an upcoming medical appointment. We integrated CP into a university breast cancer clinic beginning in 1998. Representatives of other organizations expressed interest in CP, so we invited them to training workshops in 2000, 2001, and 2002.ObjectivesIn order to learn from experience and generate hypotheses, we asked: 1) How many trainees implemented CP? 2) What facilitated implementation? 3) How have trainees, patients, physicians, and administrative leaders of implementing organizations reacted to CP? 4) What were the barriers to implementation?MethodsWe attempted to contact 32 trainees and scheduled follow-up, semi-structured, audio-recorded telephone interviews with 18. We analyzed quantitative data by tabulating frequencies and qualitative data by coding transcripts and identifying themes.ResultsTrainees came from two different types of organizations, clinics (which provide medical care) versus resource centers (which provide patient support services but not medical care). We found that: 1) Fourteen of 21 respondents, from five of eight resource centers, implemented CP. Four of the five implementing resource centers were rural. 2) Implementers identified the championing of CP by an internal staff member as a critical success factor. 3) Implementers reported that modified CP has been productive. 4) Four respondents, from two resource centers and two clinics, did not implement CP, reporting resource limitations or conflicting priorities as the critical barriers.ConclusionCP training workshops have been associated with subsequent CP implementations at resource centers but not clinics. We hypothesize that CP workshops combined with an internal champion and adequate program resources may be sufficient for some patient support organizations to implement CP

JOSA: Joint surface-based registration and atlas construction of brain geometry and function

Surface-based cortical registration is an important topic in medical image analysis and facilitates many downstream applications. Current approaches for cortical registration are mainly driven by geometric features, such as sulcal depth and curvature, and often assume that registration of folding patterns leads to alignment of brain function. However, functional variability of anatomically corresponding areas across subjects has been widely reported, particularly in higher-order cognitive areas. In this work, we present JOSA, a novel cortical registration framework that jointly models the mismatch between geometry and function while simultaneously learning an unbiased population-specific atlas. Using a semi-supervised training strategy, JOSA achieves superior registration performance in both geometry and function to the state-of-the-art methods but without requiring functional data at inference. This learning framework can be extended to any auxiliary data to guide spherical registration that is available during training but is difficult or impossible to obtain during inference, such as parcellations, architectonic identity, transcriptomic information, and molecular profiles. By recognizing the mismatch between geometry and function, JOSA provides new insights into the future development of registration methods using joint analysis of the brain structure and function.Comment: A. V. Dalca and B. Fischl are co-senior authors with equal contribution. arXiv admin note: text overlap with arXiv:2303.0159

The Brainstem in Emotion: A Review

Emotions depend upon the integrated activity of neural networks that modulate arousal, autonomic function, motor control, and somatosensation. Brainstem nodes play critical roles in each of these networks, but prior studies of the neuroanatomic basis of emotion, particularly in the human neuropsychological literature, have mostly focused on the contributions of cortical rather than subcortical structures. Given the size and complexity of brainstem circuits, elucidating their structural and functional properties involves technical challenges. However, recent advances in neuroimaging have begun to accelerate research into the brainstem’s role in emotion. In this review, we provide a conceptual framework for neuroscience, psychology and behavioral science researchers to study brainstem involvement in human emotions. The “emotional brainstem” is comprised of three major networks – Ascending, Descending and Modulatory. The Ascending network is composed chiefly of the spinothalamic tracts and their projections to brainstem nuclei, which transmit sensory information from the body to rostral structures. The Descending motor network is subdivided into medial projections from the reticular formation that modulate the gain of inputs impacting emotional salience, and lateral projections from the periaqueductal gray, hypothalamus and amygdala that activate characteristic emotional behaviors. Finally, the brainstem is home to a group of modulatory neurotransmitter pathways, such as those arising from the raphe nuclei (serotonergic), ventral tegmental area (dopaminergic) and locus coeruleus (noradrenergic), which form a Modulatory network that coordinates interactions between the Ascending and Descending networks. Integration of signaling within these three networks occurs at all levels of the brainstem, with progressively more complex forms of integration occurring in the hypothalamus and thalamus. These intermediary structures, in turn, provide input for the most complex integrations, which occur in the frontal, insular, cingulate and other regions of the cerebral cortex. Phylogenetically older brainstem networks inform the functioning of evolutionarily newer rostral regions, which in turn regulate and modulate the older structures. Via these bidirectional interactions, the human brainstem contributes to the evaluation of sensory information and triggers fixed-action pattern responses that together constitute the finely differentiated spectrum of possible emotions

Correction: Common Data Elements for Disorders of Consciousness: Recommendations from the Working Group on Neuroimaging

The list of Curing Coma Campaign Collaborators included in the Acknowledgements section has been updated. Flora Hammond, Raimund Helbok, and Naomi Niznick have been added to the list. Several spelling errors have been corrected. A revised file has been included

Clinical Guidelines for the Emergency Department Evaluation of Subarachnoid Hemorrhage

BackgroundSubarachnoid hemorrhage (SAH) is frequently caused by the rupture of an intracranial aneurysmal vessel or arteriovenous malformation, leading to a cascade of events that can result in severe disability or death. When evaluating for this diagnosis, emergency physicians have classically performed a noncontrast computed tomography (NCCT) scan, followed by a lumbar puncture (LP). Recently, however, as CT technology has advanced, many studies have questioned the necessity of the LP in the SAH diagnostic algorithm and have instead advocated for noninvasive techniques, such as NCCT alone or NCCT with CT angiogram (CTA).ObjectiveThe primary goal of this literature search was to determine the appropriate emergency department (ED) management of patients with suspected SAH.MethodsA MEDLINE literature search from October 2008 to June 2015 was performed using the keywords computed tomography AND subarachnoid hemorrhage AND lumbar puncture, while limiting the search to human studies written in the English language. General review articles and single case reports were omitted. Each of the selected articles then underwent a structured review.ResultsNinety-one articles were identified, with 31 papers being considered appropriate for analysis. These studies then underwent a rigorous review from which recommendations were developed.ConclusionsThe literature search supports that NCCT followed by CTA is a reasonable approach in the evaluation of ED patients with possible SAH

Common Data Elements for COVID-19 Neuroimaging: A GCS-NeuroCOVID Proposal

Funder: National Institute of Neurological Disorders and Stroke; doi: http://dx.doi.org/10.13039/100000065Funder: James S. McDonnell Foundation; doi: http://dx.doi.org/10.13039/100000913Funder: National Institute of Health ResearchFunder: United Kingdom Research and InnovationFunder: Addenbrooke’s Charitable Trus

Diagnosing Level of Consciousness: Limits of the Glasgow Coma Scale Total Score

In nearly all clinical and research contexts, the initial severity of a traumatic brain injury (TBI) is measured using the Glasgow Coma Scale (GCS) total score. The GCS total score however, may not accurately reflect level of consciousness, a critical indicator of injury severity. We investigated the relationship between GCS total scores and level of consciousness in a consecutive sample of 2455 adult subjects assessed with the GCS 69,487 times as part of the multi-center Transforming Research and Clinical Knowledge in TBI (TRACKTBI) study. We assigned each GCS subscale score combination a level of consciousness rating based on published criteria for the following disorders of consciousness (DoC) diagnoses: coma, vegetative state/ unresponsive wakefulness syndrome, minimally conscious state, and post-traumatic confusional state, and present our findings using summary statistics and four illustrative cases. Participants had the following characteristics: mean (standard deviation) age 41.9 (17.6) years, 69% male, initial GCS 3–8 = 13%; 9–12 = 5%; 13–15 = 82%. All GCS total scores between 4–14 were associated with more than one DoC diagnosis; the greatest variability was observed for scores of 7–11. Further, a wide range of total scores was associated with identical DoC diagnoses. Importantly, a diagnosis of coma was only possible with GCS total scores of 3–6. The GCS total score does not accurately reflect level of consciousness based on published DoC diagnostic criteria. To improve the classification of patients with TBI and to inform the design of future clinical trials, clinicians and investigators should consider individual subscale behaviors and more comprehensive assessments when evaluating TBI severityTRACK-TB

Correction: Common Data Elements for Disorders of Consciousness: Recommendations from the Working Group on Neuroimaging.

peer reviewe

Predicting Long-Term Recovery of Consciousness in Prolonged Disorders of Consciousness Based on Coma Recovery Scale-Revised Subscores: Validation of a Machine Learning-Based Prognostic Index.

peer reviewedPrognosis of prolonged Disorders of Consciousness (pDoC) is influenced by patients' clinical diagnosis and Coma Recovery Scale-Revised (CRS-R) total score. We compared the prognostic accuracy of a novel Consciousness Domain Index (CDI) with that of clinical diagnosis and CRS-R total score, for recovery of full consciousness at 6-, 12-, and 24-months post-injury. The CDI was obtained by a combination of the six CRS-R subscales via an unsupervised machine learning technique. We retrospectively analyzed data on 143 patients with pDoC (75 in Minimally Conscious State; 102 males; median age = 53 years; IQR = 35; time post-injury = 1-3 months) due to different etiologies enrolled in an International Brain Injury Association Disorders of Consciousness Special Interest Group (IBIA DoC-SIG) multicenter longitudinal study. Univariate and multivariate analyses were utilized to assess the association between outcomes and the CDI, compared to clinical diagnosis and CRS-R. The CDI, the clinical diagnosis, and the CRS-R total score were significantly associated with a good outcome at 6, 12 and 24 months. The CDI showed the highest univariate prediction accuracy and sensitivity, and regression models including the CDI provided the highest values of explained variance. A combined scoring system of the CRS-R subscales by unsupervised machine learning may improve clinical ability to predict recovery of consciousness in patients with pDoC