Parkinson’s disease (PD) is a neurodegenerative disorder associated with widespread aggregation of α-synuclein and dopaminergic neuronal loss in the substantia nigra pars compacta. As a result, striatal dopaminergic denervation leads to functional changes in the cortico-basal-ganglia-thalamo-cortical loop, which in turn cause most of the parkinsonian signs and symptoms. Despite tremendous advances in the field in the last two decades, the overall management (i.e., diagnosis and follow-up) of patients with PD remains largely based on clinical procedures. Accordingly, a relevant advance in the field would require the development of innovative biomarkers for PD. Recently, the development of miniaturized electrochemical sensors has opened new opportunities in the clinical management of PD thanks to wearable devices able to detect specific biological molecules from various body fluids. We here first summarize the main wearable electrochemical technologies currently available and their possible use as medical devices. Then, we critically discuss the possible strengths and weaknesses of wearable electrochemical devices in the management of chronic diseases including PD. Finally, we speculate about possible future applications of wearable electrochemical sensors in PD, such as the attractive opportunity for personalized closed-loop therapeutic approaches.

Objective: Lennox–Gastaut syndrome (LGS) is a developmental and epileptic encephalopathy defined by polymorphic seizures, intellectual disability (ID), and characteristic electroencephalographic (EEG) patterns. The applicability and biological validity of current electroclinical criteria remain debated. This study evaluated the concordance between clinical and electroclinical definitions of LGS and applied unsupervised clustering to identify data‐driven profiles within LGS. Methods: We retrospectively analyzed patients clinically fulfilling LGS criteria, with longitudinal electroclinical documentation and at least one sleep EEG. Patients meeting complete electroclinical criteria were compared with those meeting clinical criteria alone. Additionally, exploratory unsupervised K‐modes clustering and discriminant correspondence analysis were applied in adolescent and adult patients. Results: We included 105 patients (60.9% female), with a median age of 24 years (interquartile range = 16–35). Sixty‐nine patients (65.7%) met complete electroclinical criteria, yet neurodevelopmental features, seizure types, magnetic resonance imaging (MRI) findings, and treatment refractoriness were comparable to the clinically defined subgroup. K‐modes clustering ( n = 97 patients) identified three data‐driven electroclinical profiles. Cluster 1 comprised patients with the earliest seizure onset, profound intellectual and motor impairment, EEG background slowing, lower prevalence of generalized paroxysmal fast activity (GPFA), highest prevalence of structural etiologies, and lowest likelihood of meeting complete electroclinical criteria for LGS. Among clusters more frequently fulfilling complete electroclinical criteria, Cluster 2 represented an early onset profile with higher rates of ID, EEG background slowing, and high prevalence of polymorphic seizures. Cluster 3 included comparatively preserved patients, characterized by later onset, milder neurodevelopmental impairment, and higher frequency of normal MRI. Despite similar clinical severity, Cluster 1 patients had undergone fewer antiseizure medication trials. Significance: Exploratory data‐driven clustering identified clinically relevant electroclinical profiles that may help refine phenotypic stratification within clinically defined LGS. These included a severe GPFA‐underrepresented profile and two GPFA‐positive phenotypes differing in developmental severity, seizure profile, and age at onset.

Objective: Developmental and epileptic encephalopathies (DEEs) are associated with high premature mortality and increased risk of sudden unexpected death in epilepsy (SUDEP). However, epidemiological data remain limited, particularly for specific syndromes such as Dravet syndrome (DS), Lennox–Gastaut syndrome (LGS), and infantile epileptic spasms syndrome (IESS). To address this gap, we conducted a Bayesian meta‐analysis of randomized controlled trials (RCTs) and corresponding long‐term open‐label extension (OLE) studies. Methods: All‐cause mortality and SUDEP incidence rates were estimated using hierarchical Bayesian models with moderately informative priors derived from the literature. A negative binomial likelihood was used for all‐cause mortality, whereas a Poisson likelihood was used for SUDEP. Subgroup analysis were conducted for DS, LGS, and IESS. Results: Thirty‐seven RCTs and 15 OLE studies were included, comprising 3757 patients with DEEs (2221 LGS, 998 DS, 369 IESS, and 169 other DEEs). Across pooled data, 37 deaths occurred, including 2 definite, 12 probable, and 1 possible SUDEP. In the overall DEE population, the Bayesian posterior median estimated mortality rate was 8.76 per 1000 person‐years (PY; 95% credible interval [CrI], 5.50–13.89), and SUDEP rate was 4.32 per 1000 PY (95% CrI, 2.66–6.64). In LGS, mortality was 7.05 per 1000 PY and SUDEP was 3.4 per 1000 PY. In DS, mortality was 8.0 per 1000 PY, with a SUDEP rate of 7.59 per 1000 PY. In IESS, mortality was 9.41 per 1000 PY and SUDEP was 2.79 per 1000 PY. Significance: SUDEP accounted for approximately half of deaths in the overall DEE population and in LGS, with a proportionally greater contribution in DS. Potential trial‐related underestimation should be considered when interpreting these findings, as features of trial‐based datasets could have contributed to lower observed mortality and SUDEP estimates. Prospective population‐based studies are needed to more accurately define the real‐world incidence of SUDEP in DEEs.

Background: Gaucher disease (GD) is a rare lysosomal storage disorder caused by mutations in the GBA1 gene. Traditionally, GD is classified into three subtypes based on the severity of neurological involvement; however, overlapping clinical features increasingly suggest a continuum of phenotypes rather than distinct categories. In this prospective observational cohort study, we conducted a multidisciplinary assessment of patients with GD to identify and monitor neurological, cognitive, auditory, and visual impairments. Materials and Methods: A comprehensive clinical and instrumental evaluation was performed at baseline and repeated at follow-up, with a median interval of 37 months (IQR 36–38). Neurological assessments included physical examination, clinical rating scales, video-EEG, and brain MRI. Cognitive status was assessed using a standardized battery of neuropsychological tests. Detailed audiological and ophthalmological evaluations were also conducted. Paired parametric or non-parametric tests were applied as appropriate, with Bonferroni correction for cognitive outcomes (p < 0.05). Results: Of the 22 patients assessed at baseline, 18 completed the follow-up evaluation. Neurological assessments showed a worsening of subtle parkinsonian signs, with significant increases in Movement Disorder Society–Unified Parkinson’s Disease Rating Scale Part III scores (p = 0.04) and non-motor symptom scores (p = 0.01). Two of the eighteen patients developed epilepsy during follow-up. A high prevalence of sleep disturbances was confirmed, with 27.8% exhibiting excessive daytime sleepiness and 16.7% reporting REM sleep behaviour disorder on standardized questionnaires. Compared with baseline, cognitive assessments revealed a higher proportion of patients with performance below normative population scores in at least one cognitive domain, particularly memory. Sensorineural hearing loss was confirmed in 11 of 15 patients (73.3%) who underwent audiological evaluation, with progressive worsening of audiometric thresholds observed in 7 of 11 (64%). Ophthalmological evaluations showed no changes in visual acuity or OCT findings; however, multifocal electroretinography abnormalities were detected in 12 of 13 patients. Conclusions: Through in-depth phenotyping, this study identifies measurable neurological, cognitive, and sensory progressive changes in patients with GD over time, supporting the value of tailored, multidisciplinary long-term care strategies to monitor and address emerging clinical needs in this rare disease.