Recalibrating neurological examination: from binary signs to probabilistic and multidimensional assessment using mobile technologies in acute neurology

Neurological bedside signs are widely used in acute stroke evaluation as if they provide categorical evidence of focal neurological dysfunction. However, this Perspective argues that such interpretation reflects a systematic mismatch between clinical teaching and the probabilistic nature of diagnostic inference. Focusing on pronator drift and related pyramidal signs, we synthesize evidence showing that these findings generate only modest likelihood shifts and are highly sensitive to clinical context, patient state, and examiner conditions. We propose that bedside motor signs should not be interpreted as binary indicators of corticospinal tract dysfunction, but as context-dependent probabilistic signals that contribute incrementally to diagnostic reasoning. Reframing neurological examination within a Bayesian framework highlights that pre-test probability, rather than isolated signs, determines diagnostic meaning and clinical impact. This conceptual shift has direct implications for acute neurological decision-making, particularly in time-critical stroke pathways where bedside findings influence imaging and escalation decisions. We further argue that multidimensional clinical problems, including dizziness, gait instability, and fall risk, require integration of information across neurological, vestibular, musculoskeletal, visual, and behavioural domains. In this context, complementary quantitative and digital assessment approaches may provide additional functional information alongside conventional examination. By integrating probabilistic reasoning with multidimensional assessment, this Perspective challenges persistent categorical thinking in clinical neurology and proposes a framework for recalibrating how bedside signs are taught, interpreted, and supported by emerging digital technologies in acute care.