Explore the vast range of titles available.

Introduction MS patients are at increased risk of comorbidities and use more healthcare resources. Multimorbidity approached as the number of conditions is flawed by classifying patients with different needs as equal. We aimed to explore how comorbidities cluster and their impact on healthcare resource usage. Methods We used latent‐class models of up to 10 clusters in a population‐based sample of MS patients. The optimal number of clusters was determined using model metrics and similarity/entropy measures, and cluster stability was assessed by bootstrapping. Sociodemographic characteristics and healthcare‐resource usage according to the clusters assigned were compared to each other and to patients without comorbidities using univariable and adjusted linear regression models. Results In 5548 MS cases, of which 60% had comorbidities, the optimal number of comorbidity clusters was two, comprising a high frequency of cardiovascular comorbidities and psychiatric disorders. Patients in the cardiovascular cluster were older, and in the psychiatric cluster were more frequently female. After adjusting for sociodemographic variables, healthcare resource usage was higher for patients with comorbidities, particularly for nurse (1.1 more average yearly visit; [95% CI 0.41–1.8]; p = 0.002), primary care (1.8 more visits; [95% CI 1.4–2.1]; p < 0.001), and medication dispensation (336 more dosage units; [95% CI 260–402]; p < 0.001) in the cardiovascular cluster, and annual sick‐leave days (3.8 more days; [95% CI 0.25–7.3]; p = 0.036) in the psychiatric cluster. Discussion We observed clustering of comorbidities around cardiovascular comorbidities and mental disorders, which impacted healthcare resource usage differently. Further research is needed to assess the influence of these clusters on the prognosis of MS. Using latent‐class models in a population‐based sample of MS patients, cardiovascular and psychiatric clusters were identified. Nurse visits and medication dispensation were higher in the cardiovascular cluster, and annual sick‐leave days were higher in the psychiatric cluster.

IntroductionTo evaluate the impact of the COVID-19 pandemic on (1) number of clinical visits, (2) magnetic resonance (MR) scans, and (3) treatment prescriptions in a multiple sclerosis (MS) referral centre. MethodsRetrospective study covering January 2018 to May 2021.ResultsThe monthly mean (standard deviation [SD]) of visits performed in 2020 (814[137.6]) was similar to 2018 (741[99.7]; p = 0.153), and 2019 (797[116.3]; p = 0.747). During the COVID-19 period (2020 year), 36.3% of the activity was performed through telemedicine. The number of MR scans performed dropped by 76.6% during the “first wave” (March 14 to June 21, 2020) compared to the mean monthly activity in 2020 (183.5[68.9]), with a recovery during the subsequent two months. The monthly mean of treatment prescriptions approved in 2020 (24.1[7.0]) was lower than in 2019 (30[7.0]; p = 0.049), but similar to 2018 (23.8[8.0]; p = 0.727). Natalizumab prescriptions increased in the “first wave” and onwards, whereas anti-CD20 prescriptions decreased during the COVID-19 period.ConclusionMaintenance of the number of clinical visits was likely due to telemedicine adoption. Although the number of MR dramatically dropped during the “first wave”, an early recovery was observed. Treatment prescriptions suffered a slight quantitative decrease during 2020, whereas substantial qualitative changes were found in specific treatments.

Background Effective interventions for Multiple Sclerosis require timely treatment optimization which usually involves switching disease modifying therapies. The patterns of prescription and the reasons for changing treatment in people with MS, especially in low prevalence populations, are unknown. Objectives To describe the persistence, reasons of DMT switches and prescription patterns in a cohort of Colombian people with MS. Methods We conducted a retrospective observational study including patients with confirmed MS with at least one visit at our centre. We estimated the overall incidence rate of medication changes and assessed the persistence on medication with Kaplan–Meier survival estimates for individual medications and according to efficacy and mode of administration. The factors associated with changing medications were assessed using adjusted Cox proportional-hazards models. The reasons for switching medication changes were described, and the prescription patterns were assessed using network analysis, with measures of centrality. Results Seven hundred one patients with MS were included. Mean age was 44.3 years, and 67.9% were female. Mean disease duration was 11.3 years and 84.5% had relapsing MS at onset, with median EDSS of 1.0. Treatment was started in 659 (94%) of the patients after a mean of 3 years after MS symptom onset. Among them, 39.5% maintained their initial DMT, 29.9% experienced a single DMT change, while 18.7% went through two, and 11.9% had three or more DMT changes until the final follow-up. The total number of treatment modifications reached 720, resulting in an incidence rate of 1.09 (95% confidence interval: 1.01–1.17) per patient per year The median time to change after the first DMT was 3.75 years, and was not different according to the mode of administration or efficacy classification. The main reasons for changing DMT were MS activity (relapses, 56.7%; MRI activity, 18.6%), followed by non-serious adverse events (15.3%) and disability (11.1%). Younger age at MS onset, care under our centre and insurer status were the main determinants of treatment change. Network analysis showed that interferons and fingolimod were the most influential DMTs. Conclusions A majority of patients switch medications, mostly due to disease activity, and in association with age and insurer status.

Purpose This work presents an automatic characterization of the Alzheimer's disease describing the illness as a multidirectional departure from a baseline defining the control state, being these directions determined by a distance between functional‐equivalent anatomical regions. Methods After a brain parcellation, a region is described by its histogram of gray levels, and the Earth mover's distance establishes how close or far these regions are. The medoid of the control group is set as the reference and any brain is characterized by its set of distances to this medoid. Evaluation This hypothesis was assessed by separating groups of patients with mild Alzheimer's disease and mild cognitive impairment from control subjects, using a subset of the Open Access Series of Imaging Studies (OASIS) database. An additional experiment evaluated the method generalization and consisted in training with the OASIS data and testing with the Minimal Interval Resonance Imaging in Alzheimer's disease (MIRIAD) database. Results Classification between controls and patients with AD resulted in an equal error rate of 0.1 (90% of sensitivity and specificity at the same time). The automatic ranking of regions resulting is in strong agreement with those regions described as important in clinical practice. Classification with different databases results in a sensitivity of 85% and a specificity of 91%. Conclusions This method automatically finds out a multidimensional expression of the AD, which is directly related to the anatomical changes in specific areas such as the hippocampus, the amygdala, the planum temporale, and thalamus. This paper presents an automatic method that compares brains using a distance between anatomical regions sharing similar functions. The proposed metric is tested in two classification tasks consisting in separating patients with mild Alzheimer's disease and mild cognitive impairment from control individuals.

Background The COVID-19 pandemic raised concern amongst clinicians that disease-modifying therapies (DMT), particularly anti-CD20 monoclonal antibodies (mAb) and fingolimod, could worsen COVID-19 in people with multiple sclerosis (pwMS). This study aimed to examine DMT prescribing trends pre- and post-pandemic onset. Methods A multi-centre longitudinal study with 8,771 participants from MSBase was conducted. Two time periods were defined: pre-pandemic (March 11 2018–March 10 2020) and post-pandemic onset (March 11 2020–11 March 2022). The association between time and prescribing trends was analysed using multivariable mixed-effects logistic regression. DMT initiation refers to first initiation of any DMT, whilst DMT switches indicate changing regimen within 6 months of last use. Results Post-pandemic onset, there was a significant increase in DMT initiation/switching to natalizumab and cladribine [(Natalizumab-initiation: OR 1.72, 95% CI 1.39–2.13; switching: OR 1.66, 95% CI 1.40–1.98), (Cladribine-initiation: OR 1.43, 95% CI 1.09–1.87; switching: OR 1.67, 95% CI 1.41–1.98)]. Anti-CD20mAb initiation/switching decreased in the year of the pandemic, but recovered in the second year, such that overall odds increased slightly post-pandemic (initiation: OR 1.26, 95% CI 1.06–1.49; Switching: OR 1.15, 95% CI 1.02–1.29. Initiation/switching of fingolimod, interferon-beta, and alemtuzumab significantly decreased [(Fingolimod-initiation: OR 0.55, 95% CI 0.41–0.73; switching: OR 0.49, 95% CI 0.41–0.58), (Interferon-gamma-initiation: OR 0.48, 95% CI 0.41–0.57; switching: OR 0.78, 95% CI 0.62–0.99), (Alemtuzumab-initiation: OR 0.27, 95% CI 0.15–0.48; switching: OR 0.27, 95% CI 0.17–0.44)]. Conclusions Post-pandemic onset, clinicians preferentially prescribed natalizumab and cladribine over anti-CD20 mAbs and fingolimod, likely to preserve efficacy but reduce perceived immunosuppressive risks. This could have implications for disease progression in pwMS. Our findings highlight the significance of equitable DMT access globally, and the importance of evidence-based decision-making in global health challenges.

Introducción: la enfermedad asociada a anticuerpos contra la glicoproteína de mielina del oligodendrocito (MOGAD, por sus siglas en inglés) es una entidad clínica recientemente identificada. La frecuencia de presentación del MOGAD es desconocida, pero se considera baja con respecto a otras enfermedades inflamatorias desmielinizantes.  Materiales y métodos: revisión narrativa de la literatura. Resultados: las manifestaciones clínicas de esta condición son heterogéneas e incluyen neuritis óptica, mielitis, desmielinización multifocal del sistema nervioso central y encefalitis cortical. Se han descrito algunos hallazgos radiológicos que aumentan la sospecha diagnóstica, como el realce perineural del nervio óptico, el signo de la H en el cordón espinal y la resolución de lesiones T2 con el tiempo. El diagnóstico se basa en la detección de inmunoglobulinas G específicas contra MOG, en el contexto clínico adecuado. El tratamiento consiste en manejo de los ataques agudos con dosis altas de corticoides y en algunos casos se deberá considerar la inmunosupresión crónica (pacientes con recurrencia o con discapacidad severa residual tras el primer evento). Conclusiones: en esta revisión narrativa se resumen los aspectos clave con respecto a la fisiopatología, las manifestaciones, el diagnóstico y el tratamiento de la MOGAD.

Background/ObjectivesThe COVID-19 pandemic raised concern amongst clinicians that disease-modifying therapy (DMT), particularly anti-CD20 monoclonal antibodies (mAB) and fingolimod, could worsen COVID-19 in people with multiple sclerosis (pwMS). This study aimed to examine DMT prescribing trends pre- and post-pandemic.MethodsA multi-centre longitudinal study with 8,771 participants was conducted using data from the MSBase COVID-19 sub-study. Trends in DMT prescribing between 2018–2022 were analysed using multivariable mixed-effects logistic regression. DMT-initiation referred to the first prescription of any DMT in that timeframe, DMT-switches denoted a change in DMT regimen within 6 months of last DMT use.ResultsPost-pandemic, there was a significant increase in DMT initiation/switching to natalizumab and cladribine ([Natalizumab-Initiation:OR 1.72, 95% CI 1.39–2.13;Switching:OR 1.66, 95% CI 1.40–1.98],[Cladribine-Initiation:OR 1.43, 95% CI 1.09–1.87;Switching:OR 1.67, 95% CI 1.41–1.98]). Anti-CD20 mABs initiation decreased during-pandemic but recovered post-pandemic. Overall, anti-CD20 mABs initiation/switching increased, however less than other high-efficacy DMTs(Initiation:OR 1.26, 95% CI 1.06–1.49;Switching:OR 1.15, 95% CI 1.02–1.29). Initiation/switching of fingolimod, interferon-beta, and alemtuzumab significantly decreased([Fingolimod-Initiation:OR 0.55, 95% CI 0.41–0.73;Switching:OR 0.49, 95% CI 0.41–0.58],[Interferon-Initiation:OR 0.48, 95% CI 0.41–0.57; Switching:OR 0.78, 95% CI 0.62–0.99],[Alemtuzumab-Initiation:OR 0.27, 95% CI 0.15–0.48;Switching:OR 0.27, 95% CI 0.17–0.44]). Dimethyl fumarate initiation increased, while switching decreased(Initiation: OR 1.76, 95% CI 1.49–2.09;Switching:OR 0.85, 95% CI 0.69–1.05).ConclusionPost-pandemic, clinicians preferentially prescribed natalizumab and cladribine over anti-CD20 mABs and fingolimod, likely to preserve efficacy but reduce perceived risk of immunosuppression. This has clinical implications for disease progression and highlights the importance of equitable access to DMTs and COVID-19 treatment in a pandemic to ensure continued use of high-efficacy DMTs.

Introducción: en Colombia, la información sobre la frecuencia de presentación de la enfermedad por COVID-19 y sus desenlaces en personas con esclerosis múltiple (EM) es prácticamente inexistente. El objetivo de este estudio es describir la frecuencia, las características y los factores relacionados con la infección por COVID-19 en una muestra de pacientes con EM en Colombia. Materiales y métodos: análisis descriptivo y retrospectivo de pacientes diagnosticados con criterios de esclerosis múltiple que acudieron a nuestro centro entre junio y octubre del año 2021. Los pacientes proporcionaron información sobre la infección por SARS-CoV-2 y su vacunación. Se analizaron los factores relacionados con la infección por COVID-19 mediante modelos de regresión logística binomial uni y multivariable. Resultados: se analizaron 240 pacientes, de los cuales el 71?% eran mujeres, con una edad promedio de 34 años. La mayoría estaban en tratamiento con terapias modificadoras de la enfermedad y más del 80?% estaban vacunados. Sesenta y nueve pacientes declararon haber tenido COVID-19. En los modelos multivariables, la edad (OR 0,96; IC 95?% 0,93-0,99) fue el único factor asociado con una menor probabilidad de infección por COVID-19. Discusión: la infección por COVID-19 en pacientes con EM en Colombia parece ser independiente de las variables clínicas y de tratamiento y parece estar asociada con la menor edad. Conclusiones: se requieren más estudios para evaluar el comportamiento del COVID-19 en pacientes con EM en el contexto colombiano.

Introducción: la esclerosis múltiple es una enfermedad crónica, neurodegenerativa y autoinmune del sistema nervioso central. En Colombia, se considera como la enfermedad huérfana-rara más común, con 3224 casos reportados entre los años 2016 y 2021. El tratamiento se basa en una variedad de terapias modificadoras de la enfermedad que busca reducir las recaídas, disminuir la actividad en imágenes y retrasar la progresión de la discapacidad; sin embargo, el manejo clínico presenta desafíos debido a la falta de definiciones claras sobre el fallo de las terapias modificadoras y la falta de guías claras para el cambio de tratamiento. Objetivo: elaborar una definición de fallo terapéutico y diseñar un algoritmo para su manejo en pacientes con esclerosis múltiple recurrente en Colombia. Materiales y métodos: se llevó a cabo un consenso de expertos mediante la metodología Delphi en dos rondas virtuales con diez expertos. Además, se hizo una revisión de la literatura para obtener información destinada al diseño de la definición y al algoritmo del fallo terapéutico. Resultados: se elaboró una definición de fallo terapéutico compuesta por una introducción y la descripción de las variables clínicas que se utilizarán para determinar si un paciente presenta fallo terapéutico, y también se diseñó un algoritmo con una estrategia de optimización terapéutica, considerando las necesidades individuales de cada paciente según la definición diseñada previamente. Conclusiones: se desarrolló una definición y un algoritmo de manejo específico para Colombia basados en evidencia, experiencia clínica y recomendaciones de expertos. Estas herramientas facilitarán la toma de decisiones, el seguimiento y la eficiencia de los tratamientos, y se actualizarán periódicamente para reflejar avances científicos y mejores prácticas.