Source Data Verification (SDV) quality in clinical research: A scoping review.

Introduction: The value of Source Data Verification (SDV) has been a common theme in the applied Clinical Translational Science literature. Yet, few published assessments of SDV quality exist even though they are needed to design risk-based and reduced monitoring schemes. This review was conducted to identify reports of SDV quality, with a specific focus on accuracy.

Association of the Cervical Canal Area With Disability and Progression in People With Multiple Sclerosis.

Background And Objectives: In multiple sclerosis (MS), brain reserve serves as a protective factor against cognitive impairment. Previous research has suggested a structural counterpart in the spine-spinal cord reserve-seemed to be associated with physical disability. This study aimed to investigate the potential of the cervical canal area (CCaA) as a proxy for spinal cord reserve in a multicentric cohort of people with MS (PwMS).

Patient-Reported Outcomes Associated With "Completely Better" Status at 2 Years After Hip Arthroscopy.

Background: Measures such as the Patient Acceptable Symptom State and minimum clinically important difference have been used to contextualize patient-reported outcomes (PROs). Assessment of patients' perception of being "completely better" (CB) after hip arthroscopy has not been studied.

Purposes: To (1) determine the prevalence and characteristics of patients who report being CB at 2 years after hip arthroscopy; (2) determine whether PROs measuring function, pain, and mental health are associated with CB status; and (3) determine threshold values for PROs predictive of achieving CB status.

Motor styles in action: Developing a computational framework for operationalization of motor distances.

Aside from some common movement regularities, significant inter-individual and inter-trial variation within the same individual exists in motor system output. However, there is still a lack of a robust and widely adopted solution for quantifying the degree of similarity between movements. We therefore developed an innovative approach based on the Procrustes transformation to compute 'motor distance' between pairs of kinematic data.