Lazzaro di Biase

Improvement of Refractory Restless Legs Syndrome in a Parkinson’s Disease Patient After Semaglutide Treatment: A Novel Clinical Observation

Background: The Movement Disorder Society‐Unified Parkinson's Disease Rating Scale‐Part III (MDS‐UPDRS‐III) is subjective and insensitive to subtle changes in patients with Parkinson's disease (PD). Computer vision (CV) can extract objective kinematics from routine outpatient videos, potentially augmenting the accuracy of the motor assessment. Objective: We set out to (1) Identify CV‐derived finger‐tapping features that discriminate PD from healthy controls (HC); and (2) Quantify the relationship of these extracted features with clinical and Dopamine Transporter Single‐photon Emission Computed Tomography (DAT‐SPECT) anchors in PD patients. Methods: We retrospectively analyzed outpatient finger‐tapping videos from PD patients with DAT‐SPECT positivity within one year from videos and HC. A Mediapipe‐based pipeline quantified tapping velocity, changes in amplitude, and variability in amplitude and rhythm. Diagnostic performance was estimated with Receiver Operating Characteristic Area Under the Curves (ROC AUC) and 95% Confidence Interval (CI). Spearman assessed the relationship between tapping features, MDS‐UPDRS‐III, item 3.4 (finger tapping), and disease duration. Results: Thirty‐two PD patients and ten controls were included. Amplitude variability (AUCs, 0.93; 95% CI, 0.84–0.99, P < 0.001), and rhythm variability (AUC, 0.83; 95% CI, 0.69–0.94, P < 0.001) exhibited the best discriminatory capacity for a PD diagnosis. MDS‐UPDRS‐III correlated positively with amplitude variability (ρ = 0.55, p = 0.001) and amplitude decrement (ρ = 0.414, P = 0.009), and negatively with tapping velocity (ρ = −0.34, P = 0.05). Amplitude variability (ρ = 0.387, P = 0.014), and rhythm variability (ρ = 0.304, P = 0.045) directly correlated with item 3.4, while amplitude variability positively correlated with disease duration (ρ = 0.39, P = 0.026). Conclusion: CV‐derived tapping variability features objectively discriminated PD from healthy subjects and tracked motor severity.

Catechol-O-methyltransferase (COMT) inhibitors—Tolcapone, Entacapone, and Opicapone—are adjunct therapies for advanced Parkinson’s disease (PD), improving motor control. Their distinct safety profiles may influence clinical decisions and patient adherence. This study provides a comprehensive descriptive analysis of adverse events (AEs) reported for these drugs and a comparative safety assessment based on post-marketing AE reports and drug sales data from 2018 to 2023. A retrospective analysis was conducted using data from the FDA Adverse Event Reporting System (FAERS). AEs were categorized by severity and compared across COMT-inhibitors. Drug utilization trends were evaluated through retail and hospital sales data, expressed as standard units and market share. AE incidence was normalized for drug exposure using the median number of pills per day. Statistical comparisons were performed using Fisher’s exact test to assess differences in AE rates. Entacapone was sold 100 times more than Opicapone and 1000 times more than Tolcapone. When normalized for drug exposure, total AEs were significantly lower for Entacapone than Opicapone (OR = 0.0435, p < 0.001) and Tolcapone (OR = 0.1397, p < 0.001). Tolcapone also exhibited a significantly lower AE risk than Opicapone (OR = 0.3119, p < 0.001). Similarly, Entacapone had significantly fewer serious AEs than Opicapone (OR = 0.0732, p < 0.001) and Tolcapone (OR = 0.0872, p < 0.001), indicating a more favorable safety profile. This is the first study directly comparing the safety profiles of COMT-inhibitors head-to-head. Entacapone appears to be the safest long-term COMT-inhibitor, with the lowest risk of both serious and non-serious AEs. A long-term, prospective clinical trial is warranted to overcome retrospective limitations and confirm these findings.

Background. Clinical assessment of Parkinson’s disease (PD) is limited by high subjectivity and inter-rater variability. Markerless video analysis, namely Computer Vision (CV), offers objective and scalable characterization of motor signs. We systematically reviewed CV technologies suited for PD diagnosis, symptom monitoring, and treatment management. Methods. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, we searched PubMed for articles published between 1 January 1984 and 9 May 2025. We used the following search strategy: (“Parkinson Disease” [MeSH Terms] OR “parkinson’s disease” OR “parkinson disease”) AND (“computer vision” OR “video analysis” OR “pose estimation” OR “OpenPose” OR “DeepLabCut” OR “OpenFace” OR “YOLO” OR “MediaPipe” OR “markerless motion capture” OR “skeleton tracking”). Results. Out of 154 identified studies, 45 met eligibility criteria and were synthesized. Gait was assessed in 42% of studies, followed by bradykinesia items (17.7%). OpenPose and custom CV solutions were each used in 36% of studies, followed by MediaPipe (16%), DeepLabCut (9%), YOLO (4%). Across aims, CV pipelines consistently showed diagnostic discrimination and severity tracking aligned with expert ratings. Conclusions. CV non-invasively quantifies PD motor impairment, holding potential for objective diagnosis, longitudinal monitoring, and therapy response. Guidelines for standardized video-recording protocols and software usage are needed for real-world applications.

Ischemic stroke, caused by obstructed cerebral blood flow, remains a leading cause of mortality and disability, necessitating precise magnetic resonance imaging (MRI)-based lesion detection. This paper proposes Swin-BSSeg (brain symmetry segmentation) algorithm, an enhanced version of the brain symmetry segmentation network (BSSNet), for improved stroke lesion segmentation. Swin-BSSeg integrates Swin Transformers to capture global context and long-range dependencies through a hierarchical attention mechanism. The encoder replaces traditional convolutions with depth-wise separable convolution (DWSC) blocks comprising three cascaded depth-wise convolutional layers for efficient feature extraction and parameter reduction. Feature transfer to the decoder is accomplished via concatenation operations. The decoder also employs DWSC blocks to reduce computational demands and incorporates attention-guided connections (AGC) to refine the contextual diversity—defined as model’s ability to capture varied and spatially distributed lesion features. The model was evaluated on the public datasets (Anatomical Tracings of Lesions after Stroke) and ISLES (Ischemic Stroke Lesion Segmentation), which achieved a Dice Coefficient of 0.842 and an accuracy of 0.87 on the ATLAS dataset, while a Dice Coefficient of 0.8049 and an accuracy of 0.84 on ISLES, outperforming BSSNet in contextual understanding and boundary precision. The improvements on the ATLAS dataset were statistically significant (p < 0.05), confirming the reliability of the proposed enhancements.

Introduction Uric acid has been supposed to have a protective role in Parkinson's disease with controversial findings. This relationship has not been validated with pathology-confirmed diagnoses. This study aims to compare uric acid levels between pathology-confirmed and clinically-misdiagnosed Parkinson’s disease patients over time. Methods 65 patients with an in-vivo clinical diagnosis of Parkinson’s disease were enrolled from the UK Brain Bank. 33 were confirmed with post-mortem pathology analysis, while 32 were clinically misdiagnosed patients. Chart review explored uric acid levels at two timepoints (NO and N1). A repeated-measures ANOVA evaluated uric acid level variation over time and determined differences between the groups, including timespan between samples, disease duration, age at death, age of onset and sex as covariates. Results Average uric acid levels at N0 were 5.83 mg/dl (SD ± 1.99) and 5.94 mg/dl (SD ± 1.87) for respectively true and false positives. At N1, the values were 7.61 mg/dl (SD ± 2.35) and 7.36 mg/dl (SD ± 2.86) for respectively true and false positives. A significant main effect of time on uric acid levels was found (F(1, 58) = 4.303, p = 0.042, η²_p = 0.069). The interaction between time and the covariates was not significant, suggesting that these variables did not influence uric acid level variation over time. No influence of the diagnostic confirmation and covariates on uric acid levels between groups was found. Conclusion While uric acid levels increase over time in Parkinson's disease patients, this increase does not differ significantly between those with confirmed and unconfirmed diagnoses, nor it is influenced by disease duration, age at death, age of onset or sex.

Background: Advances in STN-DBS technology, among which directional stimulation, improved Parkinson's disease (PD) treatment efficacy, while increasing the clinical programming complexity. Lead localization software may aid the stimulation contact selection process. Objective: We aimed to assess the concordance between imaging-suggested (IGP) and conventional-programming (CP) selected stimulation contacts one year after surgery and its impact on motor outcomes. Methods: Sixty-four PD patients with bilateral STN-DBS were enrolled. Lead localization was reconstructed with Brainlab ^TM software. For each electrode, the vertical contact level and, when applicable, the directionality predicted by the lead reconstruction software to be the most effective were established and compared to the stimulation parameters clinically activated one-year post-surgery. IGP/CP concordance ratio was calculated for both stimulation level and directional contacts. Post-operative modifications of PD motor symptoms severity were compared among groups of concordant and discordant IGP/CP programming. Results: One-year post-surgery, IGP/CP concordance was 80% for active stimulation vertical contact level and 51% for directionality. No significant difference in motor outcomes was found between IGP/CP concordant and discordant patients for contact level activation, whereas patients with concordant IGP/CP active directional stimulation (c-Direction) showed superior motor outcomes at one-year follow-up than those discordant (d-Direction) (UPDRS-III stimulation-induced improvement: c-Direction = −25.66 ± 13.74 vs. d-Direction = −12.54 ± 11.86; p = 0.011). Conclusions: Visual reconstruction software correctly predicted the most clinically effective stimulation contact levels in most patients. Imaging therefore facilitates classic STN-DBS clinical programming while assuring similar outcomes. Moreover, better motor outcomes were reached by patients with concordant IGP/CP directional parameters, suggesting that visualization can represent an added value in particular for directional stimulation programming.