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Objective No available assessment tool offers a brief and psychometrically sound way for clinicians to quantify assessment of MS in a typical office visit. The objective of this study was to develop a brief clinician-reported outcome measure of MS signs and symptoms to standardize and quantify assessments that occur during a typical neurology office visit. Methods A questionnaire, called the Clinician Rating of Multiple Sclerosis (CRoMS), was developed in the following steps: literature review; concept elicitation interviews (to generate questionnaire themes and content) with patients with MS (n=14); concept elicitation interviews with neurologists (n=9); online qualitative survey with neurologists in the US, UK, Germany, and Sweden (n=72); online survey with neurologists to evaluate the first draft of the ClinRO (n=26); an in-person meeting with neurologists to discuss and revise the draft ClinRO (n=9); and interviews with neurologists and MS nurses to further refine and finalize the ClinRO (n=16). Results Across all steps of this research, several signs and symptoms consistently emerged as important for assessment in a typical office visit: walking, balance, upper limb function, coordination, weakness, fatigue, pain, sensory symptoms, bladder function, visual function, cognition, spasticity, spasms, and mood. The importance of these signs and symptoms was supported by neurologists during the online surveys and the in-person meeting. Neurologists were generally able to complete the draft ClinRO measure without difficulty, although minor revisions were suggested to refine the ClinRO for future use. Conclusion The CRoMS may be a useful tool for efficiently assessing the severity of MS symptoms. This brief clinician-reported measure could help standardize and quantify assessments in clinical studies and clinical settings.

Purpose: To compare physicians’ ability to read Alberta Stroke Program Early CT Score (ASPECTS) in patients with a large vessel occlusion within 6 hours of symptom onset when assisted by a machine learning-based automatic software tool, RAPID ASPECTS, compared with their unassisted score. Materials and Methods: 50 baseline CT scans selected from two prior studies (CRISP and GAMES-RP) were read by 3 experienced neuroradiologists who were provided access to a follow-up MRI. The average ASPECT score of these reads was used as the reference standard. Two additional neuroradiologists and 6 non-neuroradiologist readers then read the scans both with and without assistance from the RAPID ASPECTS software and reader improvement was determined. The primary hypothesis was that the agreement between typical readers and the consensus of 3 expert neuroradiologists would be improved with RAPID-assisted vs. unassisted reads. Agreement was based on the percentage of the individual ASPECT regions (50 cases, 10 regions each; N=500) where agreement was achieved. Results: Typical non-neuroradiologist readers agreed with the expert consensus read in 72% of the 500 ASPECTS regions, evaluated without software assistance. The automated software alone agreed in 77%. When the typical readers read the scan in conjunction with the software, agreement improved to 78% (P Conclusion: Typical readers had statistically significant improvement in their scoring of scans when the scan was read in conjunction with the automated RAPID ASPECTS software, achieving agreement rates that were comparable to neuroradiologists.

To compare physicians' ability to read Alberta Stroke Program Early CT Score (ASPECTS) in patients with a large vessel occlusion within 6 hours of symptom onset when assisted by a machine learning-based automatic software tool, compared with their unassisted score.50 baseline CT scans selected from two prior studies (CRISP and GAMES-RP) were read by 3 experienced neuroradiologists who were provided access to a follow-up MRI. The average ASPECT score of these reads was used as the reference standard. Two additional neuroradiologists and 6 non-neuroradiologist readers then read the scans both with and without assistance from the software reader-augmentation program and reader improvement was determined. The primary hypothesis was that the agreement between typical readers and the consensus of 3 expert neuroradiologists would be improved with software augmented vs. unassisted reads. Agreement was based on the percentage of the individual ASPECT regions (50 cases, 10 regions each; N=500) where agreement was achieved.Typical non-neuroradiologist readers agreed with the expert consensus read in 72% of the 500 ASPECTS regions, evaluated without software assistance. The automated software alone agreed in 77%. When the typical readers read the scan in conjunction with the software, agreement improved to 78% (P0.0001, test of proportions). The software program alone achieved correlations for total ASPECT scores that were similar to the expert readers who had access to the follow-up MRI scan to help enhance the quality of their reads.Typical readers had statistically significant improvement in their scoring of scans when the scan was read in conjunction with the automated software, achieving agreement rates that were comparable to neuroradiologists.

The complexity of neural dynamics stems in part from the complexity of the underlying anatomy. Yet how white matter structure constrains how the brain transitions from one cognitive state to another remains unknown. Here we address this question by drawing on recent advances in network control theory to model the underlying mechanisms of brain state transitions as elicited by the collective control of region sets. We find that previously identified attention and executive control systems are poised to affect a broad array of state transitions that cannot easily be classified by traditional engineering-based notions of control. This theoretical versatility comes with a vulnerability to injury. In patients with mild traumatic brain injury, we observe a loss of specificity in putative control processes, suggesting greater susceptibility to neurophysiological noise. These results offer fundamental insights into the mechanisms driving brain state transitions in healthy cognition and their alteration following injury.

Background Cost-utility models are frequently used to compare treatments intended to prevent or delay the onset of cardiovascular events. Most published utilities represent post-event health states without incorporating the disutility of the event or reporting the time between the event and utility assessment. Therefore, this study estimated health state utilities representing cardiovascular conditions while distinguishing between acute impact including the cardiovascular event and the chronic post-event impact. Methods Health states were drafted and refined based on literature review, clinician interviews, and a pilot study. Three cardiovascular conditions were described: stroke, acute coronary syndrome (ACS), and heart failure. One-year acute health states represented the event and its immediate impact, and post-event health states represented chronic impact. UK general population respondents valued the health states in time trade-off tasks with time horizons of one year for acute states and ten years for chronic states. Results A total of 200 participants completed interviews (55% female; mean age = 46.6 y). Among acute health states, stroke had the lowest utility (0.33), followed by heart failure (0.60) and ACS (0.67). Utility scores for chronic health states followed the same pattern: stroke (0.52), heart failure (0.57), and ACS (0.82). For stroke and ACS, acute utilities were significantly lower than chronic post-event utilities (difference = 0.20 and 0.15, respectively; both p