Central nervous system involvement in systemic lupus erythematosus: data from the Spanish Society of Rheumatology Lupus Register (RELESSER)

Objectives: To analyze the prevalence, incidence, survival and contribution on mortality of major central nervous system (CNS) involvement in systemic lupus erythematosus (SLE). Methods: Patients fulfilling the SLE 1997 ACR classification criteria from the multicentre, retrospective RELESSER-TRANS (Spanish Society of Rheumatology Lupus Register) were included. Prevalence, incidence and survival rates of major CNS neuropsychiatric (NP)-SLE as a group and the individual NP manifestations cere-brovascular disease (CVD), seizure, psychosis, organic brain syndrome and transverse myelitis were calculated. Furthermore, the contribution of these manifestations on mortality was analysed in Cox regression models adjusted for confounders. Results: A total of 3591 SLE patients were included. Of them, 412 (11.5%) developed a total of 522 major CNS NP-SLE manifestations. 61 patients (12%) with major CNS NP-SLE died. The annual mortality rate for patients with and without ever major CNS NP-SLE was 10.8% vs 3.8%, respectively. Individually, CVD (14%) and organic brain syndrome (15.5%) showed the highest mortality rates. The 10% mortality rate for patients with and without ever major CNS NP-SLE was reached after 12.3 vs 22.8 years, respectively. CVD (9.8 years) and organic brain syndrome (7.1 years) reached the 10% mortality rate earlier than other major CNS NP-SLE manifestations. Major CNS NP-SLE (HR 1.85, 1.29-2.67) and more specifically CVD (HR 2.17, 1.41-3.33) and organic brain syndrome (HR 2.11, 1.19-3.74) accounted as independent prognostic factors for poor survival. Conclusion: The presentation of major CNS NP-SLE during the disease course contributes to a higher mortality, which may differ depending on the individual NP manifestation. CVD and organic brain syndrome are associated with the highest mortality rates.Pathophysiology and treatment of rheumatic disease

Cut-offs and response criteria for the Hospital Universitario la Princesa Index (HUPI) and their comparison to widely-used indices of disease activity in rheumatoid arthritis

Objective To estimate cut-off points and to establish response criteria for the Hospital Universitario La Princesa Index (HUPI) in patients with chronic polyarthritis. Methods Two cohorts, one of early arthritis (Princesa Early Arthritis Register Longitudinal PEARL] study) and other of long-term rheumatoid arthritis (Estudio de la Morbilidad y Expresión Clínica de la Artritis Reumatoide EMECAR]) including altogether 1200 patients were used to determine cut-off values for remission, and for low, moderate and high activity through receiver operating curve (ROC) analysis. The areas under ROC (AUC) were compared to those of validated indexes (SDAI, CDAI, DAS28). ROC analysis was also applied to establish minimal and relevant clinical improvement for HUPI. Results The best cut-off points for HUPI are 2, 5 and 9, classifying RA activity as remission if =2, low disease activity if >2 and =5), moderate if >5 and <9 and high if =9. HUPI''s AUC to discriminate between low-moderate activity was 0.909 and between moderate-high activity 0.887. DAS28''s AUCs were 0.887 and 0.846, respectively; both indices had higher accuracy than SDAI (AUCs: 0.832 and 0.756) and CDAI (AUCs: 0.789 and 0.728). HUPI discriminates remission better than DAS28-ESR in early arthritis, but similarly to SDAI. The HUPI cut-off for minimal clinical improvement was established at 2 and for relevant clinical improvement at 4. Response criteria were established based on these cut-off values. Conclusions The cut-offs proposed for HUPI perform adequately in patients with either early or long term arthritis

Omecamtiv mecarbil in chronic heart failure with reduced ejection fraction, GALACTIC‐HF: baseline characteristics and comparison with contemporary clinical trials

Aims: The safety and efficacy of the novel selective cardiac myosin activator, omecamtiv mecarbil, in patients with heart failure with reduced ejection fraction (HFrEF) is tested in the Global Approach to Lowering Adverse Cardiac outcomes Through Improving Contractility in Heart Failure (GALACTIC‐HF) trial. Here we describe the baseline characteristics of participants in GALACTIC‐HF and how these compare with other contemporary trials. Methods and Results: Adults with established HFrEF, New York Heart Association functional class (NYHA) ≥ II, EF ≤35%, elevated natriuretic peptides and either current hospitalization for HF or history of hospitalization/ emergency department visit for HF within a year were randomized to either placebo or omecamtiv mecarbil (pharmacokinetic‐guided dosing: 25, 37.5 or 50 mg bid). 8256 patients [male (79%), non‐white (22%), mean age 65 years] were enrolled with a mean EF 27%, ischemic etiology in 54%, NYHA II 53% and III/IV 47%, and median NT‐proBNP 1971 pg/mL. HF therapies at baseline were among the most effectively employed in contemporary HF trials. GALACTIC‐HF randomized patients representative of recent HF registries and trials with substantial numbers of patients also having characteristics understudied in previous trials including more from North America (n = 1386), enrolled as inpatients (n = 2084), systolic blood pressure &lt; 100 mmHg (n = 1127), estimated glomerular filtration rate &lt; 30 mL/min/1.73 m2 (n = 528), and treated with sacubitril‐valsartan at baseline (n = 1594). Conclusions: GALACTIC‐HF enrolled a well‐treated, high‐risk population from both inpatient and outpatient settings, which will provide a definitive evaluation of the efficacy and safety of this novel therapy, as well as informing its potential future implementation

Latin America: situation and preparedness facing the multi-country human monkeypox outbreak

Fundación Universitaria Autónoma de las Américas. Faculty of Medicine. Grupo de Investigación Biomedicina. Pereira, Risaralda, Colombia / Universidad Científica del Sur. Master of Clinical Epidemiology and Biostatistics. Lima, Peru / Latin American network of Monkeypox Virus Research. Pereira, Risaralda, ColombiaUniversity of Buenos Aires. Cátedra de Enfermedades Infecciosas. Buenos Aires, Argentina.Hospital Britanico de Buenos Aires. Servicio de Infectología. Buenos Aires, Argentina.University of Buenos Aires. Cátedra de Enfermedades Infecciosas. Buenos Aires, Argentina / Hospital de Enfermedades Infecciosas F. J. Muniz. Buenos Aires, Argentina.University of Buenos Aires. Cátedra de Enfermedades Infecciosas. Buenos Aires, Argentina / Hospital de Enfermedades Infecciosas F. J. Muniz. Buenos Aires, Argentina.Hospital Clínico Viedma. Cochabamba, Bolivia.Gobierno Autonomo Municipal de Cochabamba. Secretaría de Salud. Centros de Salud de Primer Nivel. Direction. Cochabamba, Bolivia.Franz Tamayo University. National Research Coordination. La Paz, Bolivia.Paulista State University Júlio de Mesquita Filho. Botucatu Medical School. Infectious Diseases Department. São Paulo, SP, Brazil / Brazilian Society for Infectious Diseases. Sãao Paulo, SP, Brazil.Universidade de São Paulo. Faculdade de Saúde Pública. Departamento de Epidemiologia. São Paulo, SP, Brazil.Institute of Infectious Diseases Emilio Ribas. São Paulo, Brazil.Ministério da Saúde. Secretaria de Ciência, Tecnologia, Inovação e Insumos Estratégicos. Instituto Evandro Chagas. Ananindeua, PA, Brasil.Centro de Referencia de Salud Dr. Salvador Allende Gossens. Policlínico Neurología. Unidad Procedimientos. Santiago de Chile, Chile.Pontificia Universidad Católica de Chile. School of Medicine. Department of Pediatric Infectious Diseases and Immunology. Santiago de Chile, Chile.Universidad Austral de Chile. Facultad de Medicina. Instituto de Salud Publica. Valdivia, Chile.Ministerio de Salud. Hospital de San Fernando. San Fernando, VI Region, Chile.Fundación Universitaria Autónoma de las Américas. Faculty of Medicine. Grupo de Investigación Biomedicina. Pereira, Risaralda, Colombia.Universidad Nacional de Colombia. Department of Pediatrics. Bogota, DC, Colombia / Hospital Pediatrico La Misericordia. Division of Infectious Diseases. Bogota, DC, Colombia.Hemera Unidad de Infectología IPS SAS. Bogota, Colombia.Hospital San Vicente Fundacion. Rionegro, Antioquia, Colombia.Clinica Imbanaco Grupo Quironsalud. Cali, Colombia / Universidad Santiago de Cali. Cali, Colombia / Clinica de Occidente. Cali, Colombia / Clinica Sebastian de Belalcazar. Valle del Cauca, Colombia.National Institute of Gastroenterology. Epidemiology Unit. La Habana, CubaHospital Salvador Bienvenido Gautier. Santo Domingo, Dominican Republic.Pontificia Universidad Catolica Madre y Maestra. Santiago, Dominican Republic.International University of Ecuador. School of Medicine. Quito, Ecuador.Universidad Tecnica de Ambato. Ambato, Ecuador.Hospital Roosevelt. Guatemala City, Guatemala.Universidad Nacional Autonoma de Honduras. Faculty of Medical Sciences. School of Medical. Unit of Scientific Research. Tegucigalpa, Honduras.Hospital Infantil de Mexico. Federico Gomez, Mexico City, Mexico.Hospital General de Tijuana. Departamento de Infectología. Tijuana, Mexico.Hospital General de Tijuana. Departamento de Infectología. Tijuana, Mexico.Asociacion de Microbiólogos y Químicos Clínicos de Nicaragua. Managua, Nicaragua.Hospital Santo Tomas. Medicine Department-Infectious Diseases Service. Panama City, Panama / Instituto Oncologico Nacional. Panama city, Panama.University of Arizona College of Medicine-Phoenix. Division of Endocrinology. Department of Medicine. Phoenix, AZ, USA / Indian School Rd. Phoenix, AZ, USA.Dirección Nacional de Vigilancia Sanitaria. Dirección de Investigación. Asunción, Paraguay.Universidad Nacional de Asuncion. Faculty of Medical Sciences. Division of Dermatology. Asuncion, Paraguay.Instituto Nacional de Salud del Nino San Borja. Infectious Diseases Division. Lima, Peru / Universidad Privada de Tacna. Facultad de Ciencias de la Salud. Tacna, Peru.Universidad San Juan Bautista. Lima, Peru.Universidad San Ignacio de Loyola. Vicerrectorado de Investigación. Unidad de Investigación para la Generación y Síntesis de Evidencias en Salud. Lima, Peru.Hospital Evangelico de Montevideo. Montevideo, Uruguay.Icahn School of Medicine at Mount Sinai. Molecular and Cell-based Medicine. Department of Pathology. Molecular Microbiology Laboratory. New York, USA / Universidad del Rosario. Facultad de Ciencias Naturales. Centro de Investigaciones en Microbiología y Biotecnología-UR. Bogota, Colombia.Hospital Evangélico de Montevideo. Montevideo, Uruguay / Venezuelan Science Incubator and the Zoonosis and Emerging Pathogens Regional Collaborative Network. Infectious Diseases Research Branch. Cabudare, Lara, Venezuela.Universidad Central de Venezuela. Faculty of Medicine. Caracas, Venezuela.Universidad Central de Venezuela. Faculty of Medicine. Caracas, Venezuela / Biomedical Research and Therapeutic Vaccines Institute. Ciudad Bolivar, Venezuela.Universidad Central de Venezuela. Tropical Medicine Institute, Infectious Diseases Section. Caracas, Venezuela.Instituto Conmemorativo Gorgas de Estudios de la Salud. Clinical Research Department. Investigador SNI Senacyt Panama. Panama City, Panama

Mitogen-activated protein kinases as therapeutic targets for rheumatoid arthritis

Rheumatoid arthritis (RA) is a chronic autoimmune disease in which imbalances in pro- and anti-inflammatory cytokines promote the induction of autoimmunity, inflammation and joint destruction. Methotrexate, the standard disease-modifying anti-rheumatic drug (DMARD), has shown a gradual loss of efficacy in a significant proportion of patients, probably due to the onset of drug resistance, and thus it was hoped that the development of biologics would revolutionise RA management. Even though biologics have improved the therapy of patients refractive to DMARDs, they require parenteral administration and may leave patients open to serious infection and cancer. Therefore, attention has also been focused on inhibitors of mitogen-activated protein kinases (MAPKs), signalling enzymes that play key roles in pathogenic cytokine production, and their downstream effector pathways, in order to create safe and effective oral drugs. This article therefore provides an overview of the structure and function of MAPKs and their role in the pathogenesis of RA as context to describing the advances in the development of specific, druggable MAPK inhibitors. Their potential as therapies in the management of RA is also discussed

Regulation of tumour necrosis factor signalling: live or let die

peer reviewedTumour necrosis factor (TNF) is a pro-inflammatory cytokine that has important roles in mammalian immunity and cellular homeostasis. Deregulation of TNF receptor (TNFR) signalling is associated with many inflammatory disorders, including various types of arthritis and inflammatory bowel disease, and targeting TNF has been an effective therapeutic strategy in these diseases. This Review focuses on the recent advances that have been made in understanding TNFR signalling and the consequences of its deregulation for cellular survival, apoptosis and regulated necrosis. We discuss how TNF-induced survival signals are distinguished from those that lead to cell death. Finally, we provide a brief overview of the role of TNF in inflammatory and autoimmune diseases, and we discuss up-to-date and future treatment strategies for these disorders

The comparative responsiveness of Hospital Universitario Princesa Index and other composite indices for assessing rheumatoid arthritis activity

Objective To evaluate the responsiveness in terms of correlation of the Hospital Universitario La Princesa Index (HUPI) comparatively to the traditional composite indices used to assess disease activity in rheumatoid arthritis (RA), and to compare the performance of HUPI-based response criteria with that of the EULAR response criteria. Methods Secondary data analysis from the following studies: ACT-RAY (clinical trial), PROAR (early RA cohort) and EMECAR (pre-biologic era long term RA cohort). Responsiveness was evaluated by: 1) comparing change from baseline (Delta) of HUPI with Delta in other scores by calculating correlation coefficients; 2) calculating standardised effect sizes. The accuracy of response by HUPI and by EULAR criteria was analyzed using linear regressions in which the dependent variable was change in global assessment by physician (Delta GDA-Phy). Results Delta HUPI correlation with change in all other indices ranged from 0.387 to 0.791); HUPI's standardized effect size was larger than those from the other indices in each database used. In ACT-RAY, depending on visit, between 65 and 80% of patients were equally classified by HUPI and EULAR response criteria. However, HUPI criteria were slightly more stringent, with higher percentage of patients classified as non-responder, especially at early visits. HUPI response criteria showed a slightly higher accuracy than EULAR response criteria when using Delta GDA-Phy as gold standard. Conclusion HUPI shows good responsiveness in terms of correlation in each studied scenario (clinical trial, early RA cohort, and established RA cohort). Response criteria by HUPI seem more stringent than EULAR's