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Eric D Kirby,1 Katherine Jones,2 Natasha Campbell,2 Shaun D Fickling,1,2 Ryan CN D’Arcy1– 3 1Brainnet, Faculty of Applied Sciences, Simon Fraser University, Metro Vancouver, BC, Canada; 2Centre for Neurology Studies, HealthTech Connex, Metro Vancouver, BC, Canada; 3DM Centre for Brain Health, University of British Columbia, Metro Vancouver, CanadaCorrespondence: Ryan CN D’Arcy, Centre for Neurology Studies, HealthTech Connex, Metro Vancouver, BC, Canada, Email Ryan@healthtechconnex.comIntroduction: Athletic peak performance is increasingly focused on cognitive and mental factors. In the current study, cognitive performance was measured by neurophysiological responses in elite Junior-A hockey players.Methods: Neurophysiological brain vital signs were extracted from event-related potentials (ERPs) to evaluate auditory sensation (the N100), basic attention (the P300), and cognitive processing (the N400). In total, we evaluated 348 athletes, across 17 teams, throughout different hockey arenas in British Columbia, Canada. While brain vital signs were collected to help manage concussion, the current investigation focused on a retrospective performance analysis of cognitive processing differences.Results: The results revealed three interesting findings: 1) Player position differences were detectable in sensory N100 latency, with significantly faster responses for forwards compared to defense; 2) Goalies showed significantly higher attention P300 amplitude compared to all other positions; and 3) Cognitive N400 processing differences were detectable only during competitive combine testing, showing 60ms latency differences between forwards and defense on average.Discussion: The current findings suggest that neurophysiological responses, which are also sensitive to concussion, may be used to identify sensory, attentional, and cognitive processing differences to help optimize peak performance.Keywords: electroencephalography, event-related potentials, brain vital signs, performance optimization, ice hockey

Purpose: Little research has focused on the potential impact that the environment plays in shaping cardiac rehabilitation (CR) patient sedentary time (ST) and physical activity (PA). To address this, the current study generated daily path areas (DPAs) based on the locations they visited during and after they completed CR., Methods: Patients in CR (n = 66) completed a survey and wore an accelerometer and Global Positioning System receiver for 7 days early (first month), late (last 2 weeks of program), and 3 months after completing CR., Results: Individual DPAs were approximately 24 km2 at baseline and remained stable over time. Location-based analyses showed that most patients' ST and PA time was spent at home, followed by other residential, commercial, work, and CR locations. However, the time spent in certain locations (eg, parks and recreation locations) fluctuated during and after CR by intensity., Conclusions: CR patient DPA was stable over time. Within this space, they primarily engaged in ST and PA at home. However, when not home, the distribution of location use varied across a number of locations that extended well beyond their neighborhoods. Therefore, proximity to home may not be a barrier for CR patients in relation to their ST and PA., Competing Interests: The authors declare no conflicts of interest., (Copyright © 2025 Wolters Kluwer Health, Inc. All rights reserved.)

Background: A digital adaptation of the nine-hole peg test (9HPT) was developed with the potential to provide novel disability features for patients with multiple sclerosis (PwMS)., Objectives: The objectives were to evaluate the 9HPT features based on reliability, prognosis, and discrimination between treatment groups., Methods: The MS partners Advancing Technology and Health Solutions (MS PATHS) cohort data were used to derive new features including completion time and speed. Association and reliability between features and clinical outcomes were tested by intraclass correlation coefficients (ICCs) with repeated measures. The added prognostic value of the features for a clinically meaningful decline was assessed by time-to-event analyses with likelihood ratio tests. The estimated effect size between treatment efficacy groups was acquired from linear mixed-effects models. Sample size was calculated for a hypothetical randomized clinical trial., Results: For the 10,843 PwMS, speed and completion time were associated with MS disability. Compared with time, speed showed higher reliability (ICC = 0.78 vs 0.74), added benefits in predicting disability worsening ( p < 0.001), better discrimination between high- and low-efficacy groups (effect size: 0.035 vs 0.015), and an 18% reduction in required sample size for a 1-year clinical trial., Conclusion: Integrating horizontal hand distances traveled over the 9HPT pegboard can be a more reliable measure of hand function., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: M.M. serving on scientific advisory boards for Genzyme and Genentech and research support from AHRQ, Biogen, NIH, and Novartis. R.B. received consultant fees for Biogen, Genentech, Genzyme, and Novartis; research support from Biogen, Genentech, and Novartis; and shares rights to intellectual property underlying the Multiple Sclerosis Performance Test, currently licensed to Qr8 Health and Biogen. D.O. received research support from Genentech, Genzyme, and Novartis and consulting fees from Biogen, Genentech-Roche, Genzyme, Novartis, and Merck. R.T.N. has consulted for Alexion Pharmaceuticals, Biogen, Bristol Myers Squibb, Celltrion, Genentech, Genzyme, EMD Serono, Horizon Therapeutics, Lundbeck, and TG Therapeutics. X.J. and Z.S. are the employees of and may hold stock/stock options in Biogen. N.L. is the former employee of and may hold stock/stock options in Biogen. R.H. and J.v.B are the former employees of and may hold stock/stock options in Biogen and TW1 Healthcare and consultant for International Registry for Alzheimer’s Disease and other dementias (InRAD). N.C. is the former employee of and may hold stock/stock options in Biogen and current employee of Janssen Scientific Affairs, LLC. CB. is the former employee of and may hold stock/stock options in Biogen and current employee of Novartis. J.J. and J.A. have no disclosures.

Background: The use of electronic health record (EHR) data for research is limited by a lack of structure and a standard data model. The objective of the ICAREdata (Integrating Clinical Trials and Real-World Endpoints Data) project was to structure key research data elements in EHRs using a minimal Common Oncology Data Elements (mCODE) data model to extract and transmit data., Methods: The ICAREdata project captured two EHR data elements essential to clinical trials: cancer disease status and treatment plan change. The project was implemented in clinical sites participating in Alliance for Clinical Trials in Oncology trials. Data were extracted from EHRs and sent by secure Fast Healthcare Interoperability Resource messaging (a standard for exchanging EHRs) to a database. Selected elements were compared with corresponding data from the trial's electronic data capture (EDC) system, Medidata Rave., Results: By December 2023, data were extracted and transmitted from 10 sites for 35 patients, involving 367 clinical encounters across 15 clinical trials. Data through March 2023 demonstrated that concordance for the elements treatment plan change and cancer disease status was 79% and 34%, respectively. When disease evaluation was reported by both EHR and EDC (n = 15), there was 87% agreement on cancer disease status., Conclusions: Documentation, extraction, and aggregation of structured data elements in EHRs using mCODE and ICAREdata methods is feasible in multi-institutional cancer clinical trials. EDC as a reference data set allowed assessment of the completeness of EHR data capture. Future initiatives will focus on elements with shared definitions in clinical and research environments and efficient workflows., Plain Language Summary: Clinical trials use electronic case report forms to report data, and data must be manually entered on these forms, which is costly and time consuming. ICAREdata methods use structured, organized data from clinical trials that can be more easily shared instead having to enter free text into electronic health records., (© 2024 The MITRE Corporation and The Author(s). Cancer published by Wiley Periodicals LLC on behalf of American Cancer Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.)