Neurological disorders remain a major clinical burden because they affect cognition, movement, vascular function, behavior, psychological health, and long-term independence. Recent advances in imaging, biomarkers, artificial intelligence, regenerative therapy, immunotherapy, and targeted pharmacology have expanded diagnostic and therapeutic possibilities, yet the evidence remains dispersed across different neurological conditions and study designs. This review aimed to synthesize emerging advances in neurological disorders, focusing on diagnostic innovations, therapeutic strategies, and future clinical directions. A systematic literature review approach was applied using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-based screening principles. Eleven studies were included, covering ischemic stroke, glioblastoma, Alzheimer’s disease, multiple sclerosis, Parkinson’s disease, motor neuron disease, episodic migraine, transient ischemic attack, and postoperative delirium. Data were extracted on study design, condition, intervention or diagnostic method, comparator, outcomes, and key findings. Risk of bias was assessed using the Risk of Bias 2 (RoB 2) tool for randomized trials, the Risk of Bias in Non-randomized Studies of Interventions (ROBINS-I) for nonrandomized, uncontrolled, post hoc, feasibility, and biomarker-monitoring studies, and the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) for diagnostic and radiomics studies. Findings showed increasing use of radiomics, circulating tumor DNA, rhythm monitoring, vascular imaging, inflammatory markers, biologics, cell therapy, psychological intervention, and lipid-lowering therapy. Several studies reported promising clinical or biomarker signals, while others clarified treatment limitations in specific disease subtypes. Overall, the findings suggest an emerging shift toward precision-oriented neurology, but larger controlled trials, prospective biomarker validation, standardized outcomes, and longer follow-up are required before routine implementation.
Ramireddy et al. (Tue,) studied this question.