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Introduction: The Spasticity-Plus Syndrome (SPS) in multiple sclerosis (MS) refers to a combination of spasticity and other signs/symptoms such as spasms, cramps, bladder dysfunction, tremor, sleep disorder, pain, and fatigue. The main purpose is to develop a user-friendly tool that could help neurologists to detect SPS in MS patients as soon as possible., Methods: A survey research based on a conjoint analysis approach was used. An orthogonal factorial design was employed to form 12 patient profiles combining, at random, the eight principal SPS signs/symptoms. Expert neurologists evaluated in a survey and a logistic regression model determined the weight of each SPS sign/symptom, classifying profiles as SPS or not., Results: 72 neurologists participated in the survey answering the conjoint exercise. Logistic regression results of the survey showed the relative contribution of each sign/symptom to the classification as SPS. Spasticity was the most influential sign, followed by spasms, tremor, cramps, and bladder dysfunction. The goodness of fit of the model was appropriate (AUC = 0.816). Concordance between the experts' evaluation vs. model estimation showed strong Pearson's ( r  = 0.936) and Spearman's ( r  = 0.893) correlation coefficients. The application of the algorithm provides with a probability of showing SPS and the following ranges are proposed to interpret the results: high (> 60%), moderate (30-60%), or low (< 30%) probability of SPS., Discussion: This study offers an algorithmic tool to help healthcare professionals to identify SPS in MS patients. The use of this tool could simplify the management of SPS, reducing side effects related with polypharmacotherapy., Competing Interests: ÓF has received honoraria in the past as consultant in advisory boards, and as chairmen or lecturer in meetings, and has also participated or participates at present in clinical trials and other research projects promoted by Biogen, Bayer, Merck-Serono, Teva, Novartis, Actelion, Almirall, Roche, Allergan, Horizon, and Ala Diagnostics. LC-F has served at scientific advisory boards, participated in meetings sponsored by and received speaking honoraria or travel funding or research grants from Biogen, Bristol-Myers Squibb, Janssen, Horizon, Merck-Serono, Novartis, Roche and Sanofi. MM has received honoraria as speaker, consultant in advisory boards, travel support or research grants from Merck, Biogen, Novartis, Sanofi-Genzyme, Almirall, Viatris, Horizon, Bristol-Myers Squibb, Roche, Sandoz and Janssen. PM has received compensation for consulting services and speaking fees from Allergan, Almirall, Biogen, Merz and Sanofi. JP has served as consultant, speaker and/or moderator for Bayer Pharmaceuticals, Biogen, Bristol-Myers Squibb, Daiichi Sankyo, Genzyme Corporation, Janssen, Merck Serono, Novartis, Sanofi, Sandoz, Teva, Roche Pharma, Almirall and Celgene. LR-T has received compensation for consulting services and speaking fees from Biogen, Novartis, Bayer, Merck, Sanofi, Genzyme, Roche, Bristol-Myers Squibb, Teva and Janssen. AM has received honoraria for scientific and commercial activities from Biogen, Teva, Merck, Sanofi, Novartis, Roche, Almirall, and Mylan. YA has received research grants, travel support and lecturing and consulting fees from Bayer, Biogen, Roche, Merck, Novartis, Almirall, Sanofi-Genzyme, Janssen and Bristol-Myers Squibb. AA has received honoraria as a speaker or advisor from Almirall, Biogen, Bristol-Myers Squibb, Janssen, Merck, Novartis, Roche and Sanofi. EÁ has received collaborations and fees for participation in advisories, scientific and educational activities from Almirall, Biogen, Janssen Cilag, Sanofi-Genzyme, Merck, Novartis, Roche and Teva. AL-F reports no disclosures relevant to the manuscript. LL has received collaborations and fees for participation in advisories, scientific and educational activities, from Almirall, Bayer, Biogen, Bristol-Myers Squibb, Sanofi-Genzyme, Merck, Novartis, UCB Pharma, Roche and Teva. EM has received honoraria as consultant in advisory boards, and or as chairperson or lecturer in meetings, attendance to congresses and has also participated in clinical trials and other research projects promoted by Almirall, Bayer, Biogen, Bristol Myers Squibb, Janssen, Merck, Teva, Novartis, Roche, Sandoz and Sanofi-Genzyme. PO-N has received collaborations and fees for participation in advisories, scientific and educational activities from Almirall, Biogen, Bristol-Myers Squibb, Sanofi-Genzyme, Merck, Novartis, UCB Pharma, Roche and Teva., (Copyright © 2024 Fernández Fernández, Costa-Frossard, Martínez Ginés, Montero Escribano, Prieto González, Ramió-Torrentà, Aladro, Alonso Torres, Álvarez Rodríguez, Labiano-Fontcuberta, Landete Pascual, Miralles Martínez, Moral Torres and Oliva-Nacarino.)

Overview: We assessed the role of age and disease activity as new factors contributing to establish the risk of progressive multifocal leucoencephalopathy in multiple sclerosis patients treated with natalizumab in 36 University Hospitals in Europe. We performed the study in 1,307 multiple sclerosis patients (70.8% anti-John Cunninghan virus positive antibodies) treated with natalizumab for a median time of 3.28 years. Epidemiological, clinical, and laboratory variables were collected. Lipid-specific IgM oligoclonal band status was available in 277 patients. Factors associated with progressive multifocal leucoencephalopathy onset were explored by uni- and multivariate logistic regression. Results: Thirty-five patients developed progressive multifocal leucoencephalopathy. The multivariate analysis identified anti-John Cunninghan virus antibody indices and relapse rate as the best predictors for the onset of this serious opportunistic infection in the whole cohort. They allowed to stratify progressive multifocal leucoencephalopathy risk before natalizumab initiation in individual patients [area under the curve (AUC) = 0.85]. The risk ranged from <1/3,300 in patients with anti-John Cunninghan virus antibody indices <0.9 and relapse rate >0.5, to 1/50 in the opposite case. In patients with lipid-specific IgM oligoclonal bands assessment, age at natalizumab onset, anti-John Cunninghan virus antibody indices, and lipid-specific IgM oligoclonal band status predicted progressive multifocal leucoencephalopathy risk (AUC = 0.92). The absence of lipid-specific IgM oligoclonal bands was the best individual predictor (OR = 40.94). The individual risk ranged from <1/10,000 in patients younger than 45 years at natalizumab initiation, who showed anti John Cunningham virus antibody indices <0.9 and lipid-specific IgM oligoclonal bands to 1/33 in the opposite case. Conclusions: In a perspective of personalized medicine, disease activity, anti-lipid specific IgM oligoclonal bands, anti Jonh Cunninghan virus antibody levels, and age can help tailor natalizumab therapy in multiple sclerosis patients, as predictors of progressive multifocal leucoencephalopathy., Competing Interests: LV received a research grant from Biogen. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2020 Toboso, Tejeda-Velarde, Alvarez-Lafuente, Arroyo, Hegen, Deisenhammer, Sainz de la Maza, Alvarez-Cermeño, Izquierdo, Paramo, Oliva, Casanova, Agüera-Morales, Franciotta, Gastaldi, Fernández, Urbaneja, Garcia-Dominguez, Romero, Laroni, Uccelli, Perez-Sempere, Saiz, Blanco, Galimberti, Scarpini, Espejo, Montalban, Rasche, Paul, González, Álvarez, Ramo, Caminero, Aladro, Calles, Eguía, Belenguer-Benavides, Ramió-Torrentà, Quintana, Martínez-Rodríguez, Oterino, López de Silanes, Casanova, Landete, Frederiksen, Bsteh, Mulero, Comabella, Hernández, Espiño, Prieto, Pérez, Otano, Padilla, García-Merino, Navarro, Muriel, Frossard and Villar.)

Introduction: Essential tremor (ET) shows amplitude fluctuations throughout the day, presenting challenges in both clinical and treatment monitoring. Tremor severity is currently evaluated by validated rating scales, which only provide a timely and subjective assessment during a clinical visit. Motor sensors have shown favorable performances in quantifying tremor objectively., Methods: A new highly portable system was used to monitor tremor continuously during daily lives. It consists of a smartwatch with a triaxial accelerometer, a smartphone, and a remote server. An experiment was conducted involving eight ET patients. The average effective data collection time per patient was 26 (±6.05) hours. Fahn-Tolosa-Marin Tremor Rating Scale (FTMTRS) was adopted as the gold standard to classify tremor and to validate the performance of the system. Quantitative analysis of tremor severity on different time scales is validated., Results: Significant correlations were observed between neurologist's FTMTRS and patient's FTMTRS auto-assessment scores ( r  = 0.84; p  = 0.009), between the device quantitative measures and the scores from the standardized assessments of neurologists ( r  = 0.80; p  = 0.005) and patient's auto-evaluation ( r  = 0.97; p  = 0.032), and between patient's FTMTRS auto-assessment scores day-to-day ( r  = 0.87; p  < 0.001). A graphical representation of four patients with different degrees of tremor was presented, and a representative system is proposed to summarize the tremor scoring at different time scales., Conclusion: This study demonstrates the feasibility of prolonged and continuous monitoring of tremor severity during daily activities by a highly portable non-restrictive system, a useful tool to analyze efficacy and effectiveness of treatment.