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Kristin Kostka,1,2 Talita Duarte-Salles,3 Albert Prats-Uribe,4 Anthony G Sena,5,6 Andrea Pistillo,3 Sara Khalid,4 Lana YH Lai,7 Asieh Golozar,8,9 Thamir M Alshammari,10 Dalia M Dawoud,11 Fredrik Nyberg,12 Adam B Wilcox,13,14 Alan Andryc,5 Andrew Williams,15 Anna Ostropolets,16 Carlos Areia,17 Chi Young Jung,18 Christopher A Harle,19 Christian G Reich,1,2 Clair Blacketer,5,6 Daniel R Morales,20 David A Dorr,21 Edward Burn,3,4 Elena Roel,3,22 Eng Hooi Tan,4 Evan Minty,23 Frank DeFalco,5 Gabriel de Maeztu,24 Gigi Lipori,19 Hiba Alghoul,25 Hong Zhu,26 Jason A Thomas,13 Jiang Bian,19 Jimyung Park,27 Jordi Martínez Roldán,28 Jose D Posada,29 Juan M Banda,30 Juan P Horcajada,31 Julianna Kohler,32 Karishma Shah,33 Karthik Natarajan,16,34 Kristine E Lynch,35,36 Li Liu,37 Lisa M Schilling,38 Martina Recalde,3,22 Matthew Spotnitz,14 Mengchun Gong,39 Michael E Matheny,40,41 Neus Valveny,42 Nicole G Weiskopf,21 Nigam Shah,29 Osaid Alser,43 Paula Casajust,42 Rae Woong Park,27,44 Robert Schuff,21 Sarah Seager,1 Scott L DuVall,35,36 Seng Chan You,45 Seokyoung Song,46 Sergio Fernández-Bertolín,3 Stephen Fortin,5 Tanja Magoc,19 Thomas Falconer,16 Vignesh Subbian,47 Vojtech Huser,48 Waheed-Ul-Rahman Ahmed,33,49 William Carter,38 Yin Guan,50 Yankuic Galvan,19 Xing He,19 Peter R Rijnbeek,6 George Hripcsak,16,34 Patrick B Ryan,5,16 Marc A Suchard,51 Daniel Prieto-Alhambra4 1IQVIA, Cambridge, MA, USA; 2OHDSI Center at The Roux Institute, Northeastern University, Portland, ME, USA; 3Fundació Institut Universitari per a la recerca a l’Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain; 4Centre for Statistics in Medicine, NDORMS, University of Oxford, Oxford, UK; 5Janssen Research & Development, Titusville, NJ, USA; 6Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands; 7School of Medical Sciences, University of Manchester, Manchester, UK; 8Regeneron Pharmaceuticals, Tarrytown, NY, USA; 9Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; 10College of Pharmacy, Riyadh Elm University, Riyadh, Saudi Arabia; 11National Institute for Health and Care Excellence, London, UK; 12School of Public Health and Community Medicine, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; 13Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA, USA; 14Unviersity of Washington Medicine, Seattle, WA, USA; 15Tufts Institute for Clinical Research and Health Policy Studies, Boston, MA, USA; 16Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY, USA; 17Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; 18Division of Respiratory and Critical Care Medicine, Department of Internal Medicine, Daegu Catholic University Medical Center, Daegu, South Korea; 19University of Florida Health, Gainesville, FL, USA; 20Division of Population Health and Genomics, University of Dundee, Dundee, UK; 21Department of Medical Informatics & Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA; 22Universitat Autònoma de Barcelona, Barcelona, Spain; 23O’Brien Institute for Public Health, Faculty of Medicine, University of Calgary, Calgary, Canada; 24IOMED, Barcelona, Spain; 25Faculty of Medicine, Islamic University of Gaza, Gaza, Palestine; 26Nanfang Hospital, Southern Medical University, Guangzhou, People’s Republic of China; 27Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, South Korea; 28Director of Innovation and Digital Transformation, Hospital del Mar, Barcelona, Spain; 29Department of Medicine, School of Medicine, Stanford University, Redwood City, CA, USA; 30Georgia State University, Department of Computer Science, Atlanta, GA, USA; 31Department of Infectious Diseases, Hospital del Mar, Institut Hospital del Mar d’Investigació Mèdica (IMIM), Universitat Autònoma de Barcelona, Universitat Pompeu Fabra, Barcelona, Spain; 32United States Agency for International Development, Washington, DC, USA; 33Botnar Research Centre, NDORMS, University of Oxford, Oxford, UK; 34New York-Presbyterian Hospital, New York, NY, USA; 35VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA; 36Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA; 37Biomedical Big Data Center, Nanfang Hospital, Southern Medical University, Guangzhou, People’s Republic of China; 38Data Science to Patient Value Program, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; 39Institute of Health Management, Southern Medical University, Guangzhou, People’s Republic of China; 40Tennessee Valley Healthcare System, Veterans Affairs Medical Center, Nashville, TN, USA; 41Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA; 42Real-World Evidence, TFS, Barcelona, Spain; 43Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; 44Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, South Korea; 45Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, South Korea; 46Department of Anesthesiology and Pain Medicine, Catholic University of Daegu, School of Medicine, Daegu, South Korea; 47College of Engineering, The University of Arizona, Tucson, AZ, USA; 48National Library of Medicine, National Institutes of Health, Bethesda, MD, USA; 49College of Medicine and Health, University of Exeter, St Luke’s Campus, Exeter, UK; 50DHC Technologies Co. Ltd., Beijing, People’s Republic of China; 51Departments of Biostatistics, Computational Medicine, and Human Genetics, University of California, Los Angeles, CA, USACorrespondence: Daniel Prieto-Alhambra, Botnar Research Centre, Windmill Road, Oxford, OX37LD, UK, Email daniel.prietoalhambra@ndorms.ox.ac.ukPurpose: Routinely collected real world data (RWD) have great utility in aiding the novel coronavirus disease (COVID-19) pandemic response. Here we present the international Observational Health Data Sciences and Informatics (OHDSI) Characterizing Health Associated Risks and Your Baseline Disease In SARS-COV-2 (CHARYBDIS) framework for standardisation and analysis of COVID-19 RWD.Patients and Methods: We conducted a descriptive retrospective database study using a federated network of data partners in the United States, Europe (the Netherlands, Spain, the UK, Germany, France and Italy) and Asia (South Korea and China). The study protocol and analytical package were released on 11th June 2020 and are iteratively updated via GitHub. We identified three non-mutually exclusive cohorts of 4,537,153 individuals with a clinical COVID-19 diagnosis or positive test, 886,193 hospitalized with COVID-19, and 113,627 hospitalized with COVID-19 requiring intensive services.Results: We aggregated over 22,000 unique characteristics describing patients with COVID-19. All comorbidities, symptoms, medications, and outcomes are described by cohort in aggregate counts and are readily available online. Globally, we observed similarities in the USA and Europe: more women diagnosed than men but more men hospitalized than women, most diagnosed cases between 25 and 60 years of age versus most hospitalized cases between 60 and 80 years of age. South Korea differed with more women than men hospitalized. Common comorbidities included type 2 diabetes, hypertension, chronic kidney disease and heart disease. Common presenting symptoms were dyspnea, cough and fever. Symptom data availability was more common in hospitalized cohorts than diagnosed.Conclusion: We constructed a global, multi-centre view to describe trends in COVID-19 progression, management and evolution over time. By characterising baseline variability in patients and geography, our work provides critical context that may otherwise be misconstrued as data quality issues. This is important as we perform studies on adverse events of special interest in COVID-19 vaccine surveillance.Keywords: OHDSI, OMOP CDM, descriptive epidemiology, real world data, real world evidence, open science

En investigaciones sobre escritura se ha señalado que revisar y corregir los textos son aspectos fundamentales cuando se escribe. Se considera también que la manera en que escriben las personas puede estudiarse por medio de la habilitación lingüística, definida como la facilitación de un desempeño en modo lingüístico activo (señalar, escribir o hablar) como resultado de la exposición previa a un modo lingüístico reactivo (observar, leer o escuchar). Por ello, el objetivo de este estudio fue evaluar la exposición de estudiantes universitarios a los modos reactivos, sobre la habilitación lingüística del modo activo escribir y sobre la revisión y corrección cuando se les presenta de nueva cuenta el texto escrito. Los participantes, asignados a uno de tres grupos, primero escribieron un texto sobre el ciclo del agua, después fueron expuestos a uno de los tres modos lingüísticos reactivos, por último, se les presentó el texto escrito previamente sobre el ciclo del agua para su revisión y corrección. Los resultados mostraron puntajes más altos para los grupos expuestos a los modos leer y escuchar, seguidos por el grupo donde debían observar; no se encontró corrección de los textos. Los resultados se discuten en relación con investigaciones de habilitación lingüística y con aspectos necesarios para la revisión y corrección de textos.

El objetivo de la presente investigación fue identificar si existe correlación entre las diferentes situaciones que provocan miedo y ansiedad y las estrategias de afrontamiento en el caso específico de los estudiantes universitarios mexicanos. Método: El tipo de estudio fue no experimental, de tipo transversal con múltiples variables continuas. Participaron 1,557 universitarios mexicanos (47.8% mujeres y 52.2% hombres), media de edad = 21.56 (DE = 3.23). Con la ayuda de un instrumento se midió la intensidad del miedo (α = 0.90) ante siete tipos de situaciones. En orden descendente, las situaciones en que se registró más intensidad fueron las siguientes: ser víctima de la violencia, la violencia social, experiencias de muerte o paranormales, aislamiento social, animales, experiencias escolares desagradables y experiencias de asistencia médica. Para el caso de la ansiedad se utilizó el Inventario de Ansiedad de Beck (2001), validado para población mexicana (α = 0.84). Por medio de preguntas abiertas se cuestionó a los participantes sobre qué harían ante cada una de esas siete situaciones que provocan miedo, con el fin de identificar los tipos de afrontamiento que utilizan. Resultados: el miedo y la ansiedad se correlacionaron de manera significativa (0.01) y positiva, tanto en la muestra total como en los grupos de hombres y mujeres separadamente. En cuanto a las estrategias de afrontamiento ante situaciones que provocan miedo, las más utilizadas fueron aquellas que abordan directamente el problema, seguidas por no hacer nada, estrategias de evitación, desahogo emocional, distracción, agresivas y búsqueda de apoyo. Las correlaciones entre las dos primeras fueron altas, significativas y negativas, tanto en la muestra general como en hombres y mujeres.

I Purpose or Learning Objective: i Lumbar facet synovial cysts are seen in degenerative arthropathy and can cause disabling radiculopathy. We compared radiologic parameters of patients who presented with significant clinical improvement after CT-guided synovial cyst rupture with those who did not, to establish possible prognostic factors. A low-risk nonsurgical and minimally invasive management option includes computed tomography (CT)-guided injection of diluted contrast and anesthesia/corticosteroid for its rupture. [Extracted from the article]

La estructura renal es sensible a la acción de fármacos, especialmente en el túbulo proximal y distal, que están constituidos por células especializadas con gran actividad metabólica dedicada al transporte de solutos. En esta comunicación se describen diversos fármacos que interfieren con el túbulo-intersticio renal en forma aguda o crónica, se explican los mecanismos de daño renal y las formas de evitarlos en el momento del uso clínico de nefrotóxicos. También se hace referencia a aquellos fármacos cuya eliminación es principalmente por filtración glomerular, por lo que su administración debe ajustarse al cálculo de esta variable funcional para evitar toxicidades en órganos y tejidos, incluido el riñón.

El Centro de Trasplante de Clínica Las Condes se formó en 1994, doce años después de fundada la institución, con el objetivo de aplicar las técnicas de los trasplantes de órganos sólidos a receptores con insuficiencia de variados órganos abdominales y torácicos. Quince años después se pueden mostrar resultados que considerados en su conjuntos son inéditos en el país: 212 trasplantes hepáticos, 179 trasplantes renales, 60 trasplantes de pulmón, 20 trasplantes cardiacos, 13 trasplantes combinados de páncreas y riñón, 2 de intestino y uno de islotes de páncreas. Los resultados clínicos son comparables a los de centros especializados de países desarrollados. Además, se han procurado órganos dentro y fuera de la institución, se ha realizado docencia de post grado en Trasplante para médicos y enfermeras, se ha hecho investigación básica y clínica en alianza con la Universidad de Chile, se ha innovado tecnológicamente para ofrecer una terapia actualizada y segura. Todo ello ha sido posible por la constitución de un sólido equipo de trabajo asentado en una institución eficiente que estimula el progreso y el perfeccionamiento.

En el trasplante de órganos siempre hay un donante y receptor cuyas voluntades deben ser respetadas y que deben ser estrictamente evaluados desde el punto de vista médico, social, psicológico y moral para determinar la idoneidad de cada uno para recibir la acción médica. En el presente artículo se describen las pautas para estudiar a un potencial donante renal vivo o cadavérico y a los potenciales receptores de un trasplante renal para evitar yerros que compliquen el trasplante o atenten contra normas éticas y científicas básicas universalmente aceptadas que se aplican al trasplante de órganos sólidos en general y de riñón en particular.

Long-acting β2-agonist (LABA) monotherapy is contraindicated in asthma following reports of serious adverse events. Anonymised Scottish health data were used to determine the prevalence of LABA prescribing and LABA monotherapy (sustained and episodic) in asthma during 2006. Of 73 486 asthma patients identified, 5592 (7.6%; 95% CI 7.4% to 7.8%) were prescribed LABAs as a separate inhaler of which 991 patients had LABA monotherapy (17.7% (95% CI 16.7% to 18.7%) of patients at risk). Asthma reviews were associated with reductions in sustained (OR 0.44; 95% CI 0.32 to 0.61) but not episodic monotherapy (OR 1.16; 95% CI 0.85 to 1.57). These findings support recent changes in UK asthma guidelines recommending LABAs in fixed-dose combination inhalers. [ABSTRACT FROM AUTHOR]

Background: Sodium-glucose cotransporter 2 inhibitors (SGLT2is) and glucagon-like peptide-1 receptor agonists (GLP-1 RAs) reduce the risk of major adverse cardiovascular events (MACE) in patients with type 2 diabetes mellitus (T2DM). However, their effectiveness relative to each other and other second-line antihyperglycemic agents is unknown, without any major ongoing head-to-head clinical trials., Objectives: The aim of this study was to compare the cardiovascular effectiveness of SGLT2is, GLP-1 RAs, dipeptidyl peptidase-4 inhibitors (DPP4is), and clinical sulfonylureas (SUs) as second-line antihyperglycemic agents in T2DM., Methods: Across the LEGEND-T2DM (Large-Scale Evidence Generation and Evaluation Across a Network of Databases for Type 2 Diabetes Mellitus) network, 10 federated international data sources were included, spanning 1992 to 2021. In total, 1,492,855 patients with T2DM and cardiovascular disease (CVD) on metformin monotherapy were identified who initiated 1 of 4 second-line agents (SGLT2is, GLP-1 RAs, DPP4is, or SUs). Large-scale propensity score models were used to conduct an active-comparator target trial emulation for pairwise comparisons. After evaluating empirical equipoise and population generalizability, on-treatment Cox proportional hazards models were fit for 3-point MACE (myocardial infarction, stroke, and death) and 4-point MACE (3-point MACE plus heart failure hospitalization) risk and HR estimates were combined using random-effects meta-analysis., Results: Over 5.2 million patient-years of follow-up and 489 million patient-days of time at risk, patients experienced 25,982 3-point MACE and 41,447 4-point MACE. SGLT2is and GLP-1 RAs were associated with lower 3-point MACE risk than DPP4is (HR: 0.89 [95% CI: 0.79-1.00] and 0.83 [95% CI: 0.70-0.98]) and SUs (HR: 0.76 [95% CI: 0.65-0.89] and 0.72 [95% CI: 0.58-0.88]). DPP4is were associated with lower 3-point MACE risk than SUs (HR: 0.87; 95% CI: 0.79-0.95). The pattern for 3-point MACE was also observed for the 4-point MACE outcome. There were no significant differences between SGLT2is and GLP-1 RAs for 3-point or 4-point MACE (HR: 1.06 [95% CI: 0.96-1.17] and 1.05 [95% CI: 0.97-1.13])., Conclusions: In patients with T2DM and CVD, comparable cardiovascular risk reduction was found with SGLT2is and GLP-1 RAs, with both agents more effective than DPP4is, which in turn were more effective than SUs. These findings suggest that the use of SGLT2is and GLP-1 RAs should be prioritized as second-line agents in those with established CVD., Competing Interests: Funding Support and Author Disclosures This study was partially funded through National Institutes of Health grants R01 HL167858, K23 HL153775, R01 LM006910, R01 HG006139, and R01 HL169954 and the U.S. Department of Veterans Affairs under the research priority to “Put VA Data to Work for Veterans” (VA ORD 22-D4V). The funders had no role in the design and conduct of the protocol; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Dr Khera is an associate editor at JAMA; and has received support from the National Heart, Lung, and Blood Institute of the National Institutes of Health (awards R01 HL167858 and K23 HL153775) and the Doris Duke Charitable Foundation (award 2022060); has received research support, through Yale University, from Bristol Myers Squibb, Novo Nordisk, and BridgeBio; is a coinventor of U.S. provisional patent applications WO2023230345A1, US20220336048A1, 63/346,610, 63/428,569, 63/484,426, 63/508,315, 63/580,137, 63/606,203, 63/619,241, and 63/562,335, unrelated to the present work; and is a cofounder of Evidence2Health and Ensight-AI, precision health platforms to improve evidence-based cardiovascular care and cardiovascular diagnostics. Dr DuVall has received grants from Alnylam Pharmaceuticals, AstraZeneca Pharmaceuticals, Biodesix, Celgene, Cerner Enviza, GlaxoSmithKline, Janssen Pharmaceuticals, Novartis International, and Parexel International through the University of Utah or the Western Institute for Veteran Research (outside the submitted work). Dr Man has received support from the C.W. Maplethorpe Fellowship, the National Institute of Health Research, European Commission Framework Horizon 2020, the Hong Kong Research Grant Council, and the Innovation and Technology Commission of the Hong Kong Special Administration Region Government outside the submitted work). Dr Morales is supported by a Wellcome Trust Clinical Research Fellowship (214588/Z/18/Z). In the past 3 years, Dr Krumholz has received expenses and/or personal fees from UnitedHealth, Element Science, Aetna, Reality Labs, Tesseract/4Catalyst, F-Prime, the Siegfried and Jensen Law Firm, the Arnold and Porter Law Firm, and the Martin/Baughman Law Firm; is a cofounder of Refactor Health, HugoHealth, and Ensight-AI; and is associated with contracts, through Yale New Haven Hospital, from the Centers for Medicare and Medicaid Services and, through Yale University, from Johnson & Johnson. Dr You is chief technology officer of PHI Digital Healthcare. Dr Ross has received research support through Yale University from Johnson & Johnson to develop methods of clinical trial data sharing, from the Food and Drug Administration for the Yale-Mayo Clinic Center for Excellence in Regulatory Science and Innovation program (grant U01 FD005938), from the Agency for Healthcare Research and Quality (grant R01 HS022882), and from Arnold Ventures; has received research support from the Medical Device Innovation Consortium as part of the National Evaluation System for Health Technology and from the National Heart, Lung, and Blood Institute of the National Institutes of Health (grants R01 HS025164 and R01 HL144644); and was an expert witness at the request of the relator’s attorneys, the Greene Law Firm, in a qui tam suit alleging violations of the False Claims Act and Anti-Kickback Statute against Biogen that was settled September 2022. Dr Thangaraj is a coinventor on provisional patent 63/606,203, unrelated to the present work, and is funded by grant 5T32 HL155000-03. Ms Blacketer, Dr Ostropolets, and Dr Ryan are employees of Johnson & Johnson. Dr Schuemie is an employee and shareholder of Johnson & Johnson. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2024 American College of Cardiology Foundation. All rights reserved.)

Objective: Multiple treatment options are recommended for Systemic Lupus Erythematosus (SLE) by clinical guidelines. This study aimed to explore SLE treatment patterns as there is limited real-world data of SLE medication utilisation, especially in childhood-onset SLE (cSLE)., Methods: We conducted a longitudinal cohort study using five routinely collected healthcare databases from four European countries (United Kingdom, France, Germany, and Spain). We described the characteristics of adult and paediatric patients at time of SLE diagnosis. We calculated the percentage of patients commencing SLE treatments in the first month and year after diagnosis, reported number of prescriptions, starting dose, cumulative dose, and duration of each treatment, and characterised the line of therapy., Results: We characterised 11,255 patients with a first diagnosis of SLE and included 5718 in our medication utilisation analyses. The majority of adult SLE patients were female (range 80-88 %), with median age of 49 to 54 years at diagnosis. In the paediatric cohort (n = 378), 66-83 % of SLE patients were female, with median age of 12 to 16 years at diagnosis. Hydroxychloroquine and glucocorticoids were common first-line treatments in both adults and children, with second-line treatments including mycophenolate mofetil and methotrexate. Few cases of monoclonal antibody use were seen in either cohort. Initial glucocorticoid dosing in paediatric patients was often higher than in adults., Conclusion: Treatment choices for adult SLE patients across four European countries were in line with recent therapeutic consensus guidelines. High glucocorticoid prescriptions in paediatric patients suggests the need for steroid-sparing treatment alternatives and paediatric specific guidelines., Competing Interests: Declarations of competing interest DPA's department has received grant/s from Amgen, Chiesi-Taylor, Lilly, Janssen, Novartis, and UCB Biopharma. His research group has received consultancy fees from Astra Zeneca and UCB Biopharma. Amgen, Astellas, Janssen, Synapse Management Partners and UCB Biopharma have funded or supported training programmes organised by DPA's department. James Brash and Hanne van Ballegooijen are employees of IQVIA. All other authors have no conflicts of interest to declare., (Copyright © 2024. Published by Elsevier B.V.)

Purpose: The European Medicines Agency's (EMA) Pharmacovigilance Risk Assessment Committee (PRAC) launched a strategy to examine the public health impact of major regulatory interventions aimed at minimising risks of medicinal products. We conducted a lessons learnt analysis of impact studies completed between 2015 and 2023., Methods: We surveyed PRAC Sponsors and (Co-)Rapporteurs involved in the evaluation of 12 impact studies (10 commissioned by EMA and 2 conducted collaboratively by Member States) to explore how these support regulatory decision-making. Questions covered achievement of study objectives, risk minimisation effectiveness, added value for regulatory decision-making, and recommendations for future impact studies. Themes were generated using thematic content analysis., Results: Survey responses from 15 PRAC Sponsors and (Co-)Rapporteurs from 10 European Union Member States were included in the analysis. Among four cross-sectional surveys and eight drug utilisation studies, 50% achieved all objectives, the other studies partially due to limitations. Two studies concluded that risk minimisation measures were overall effective, two were effective with variation across countries, two were partially effective and four studies showed limited effectiveness. Two studies were deemed inconclusive due to limitations. The reasons for the limited effectiveness of risk minimisation may be explored using mixed-method approaches. Assessment of study feasibility and a priori discussion of effectiveness measurements is important., Conclusion: Despite limitations, impact research adds value to regulatory decision-making by addressing knowledge gaps and providing additional information on unintended consequences of regulatory interventions. Our recommendations will help to improve planning, conducting and interpretating future impact studies., (© 2024 The Author(s). Pharmacoepidemiology and Drug Safety published by John Wiley & Sons Ltd.)

Objectives: To quantify prevalence, harms, and NHS costs in England of problematic oral non-steroidal anti-inflammatory drug (NSAID) prescribing in high risk groups., Design: Population based cohort and economic modelling study., Setting: Economic models estimating patient harm associated with NSAID specific hazardous prescribing events, and cost to the English NHS, over a 10 year period, were combined with trends of hazardous prescribing event to estimate national levels of patient harm and NHS costs., Participants: Eligible participants were prescribed oral NSAIDs and were in five high risk groups: older adults (≥65 years) with no gastroprotection; people who concurrently took oral anticoagulants; or those with heart failure, chronic kidney disease, or a history of peptic ulcer., Main Outcome Measures: Prevalence of hazardous prescribing events, by each event and overall, discounted quality adjusted life years (QALYs) lost, and cost to the NHS in England of managing harm., Results: QALY losses and cost increases were observed for each hazardous prescribing event ( v no hazardous prescribing event). Mean QALYs per person were between 0.01 (95% credibility interval (CI) 0.01 to 0.02) lower with history of peptic ulcer, to 0.11 (0.04 to 0.19) lower with chronic kidney disease. Mean cost increases ranged from a non-statistically significant £14 (€17; $18) (95% CI -£71 to £98) in heart failure, to a statistically significant £1097 (£236 to £2542) in people concurrently taking anticoagulants. Prevalence of hazardous prescribing events per 1000 patients ranged from 0.11 in people who have had a peptic ulcer to 1.70 in older adults. Nationally, the most common hazardous prescribing event (older adults with no gastroprotection) resulted in 1929 (1416 to 2452) QALYs lost, costing £2.46m (£0.65m to £4.68m). The greatest impact was in people concurrently taking oral anticoagulants: 2143 (894 to 4073) QALYs lost, costing £25.41m (£5.25m to £60.01m). Over 10 years, total QALYs lost were estimated to be 6335 (4471 to 8658) and an NHS cost for England of £31.43m (£9.28m to £67.11m)., Conclusions: NSAIDs continue to be a source of avoidable harm and healthcare cost in these five high risk populations, especially in inducing an acute event in people with chronic condition and people taking oral anticoagulants., Competing Interests: Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/disclosure-of-interest/ and declare: Funding from the NIHR; DMA reports research grants from NIHR, AbbVie, Almirall, Celgene, Eli Lilly, Janssen, Novartis, UCB, and the Leo Foundation. AC, EC, BG, DM, LP, and GR report research grants from NIHR. AC reports research grants from NIHR, UKRI, and Industrial Challenge Fund. AJA reports research grants from NIHR and was National Clinical Director for NHS England at the time of the study. RAE reports research grants from NIHR and Abbott., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY. No commercial re-use. See rights and permissions. Published by BMJ.)

Introduction: The objective of this study was to explore the approach to patients with psychiatric symptoms by nursing professionals in general hospitalisation units in the city of Medellín, Colombia., Methods: A qualitative study with the method of interpretive phenomenology. 11 nursing professionals from general hospitalisation units in the city of Medellín, Colombia participated. The information analysis was processed according to the Phenomenological Interpretive Analysis method and with the support of the NVIVO Plus 12 software., Results: The nurses' experience is described through three themes: representations of the patient with psychiatric symptoms, the patient as aggressive, violent and unpredictable; feeling fearful while providing care, caring for others in the midst of prevention, fear and stress, and being in a chaotic situation, a circumstance that gets out of control and alters the dynamics of the hospitalisation unit., Conclusions: Caring for patients with psychiatric symptoms is stressful, especially when nursing professionals perceive a lack of support from other colleagues and from the hospital administration. The above favours the development of alterations in the professional's physical and mental health., (Copyright © 2024. Published by Elsevier España, S.L.U.)

Aims: Norway and Sweden had different early pandemic responses that may have impacted mental health management. The aim was to assess the impact of the early COVID-19 pandemic on mental health-related care., Methods: We used national registries in Norway and Sweden (1 January 2018-31 December 2020) to define 2 cohorts: (i) general adult population; and (ii) mental health adult population. Interrupted times series regression analyses evaluated step and slope changes compared to prepandemic levels for monthly rates of medications (antidepressants, antipsychotics, anxiolytics, hypnotics/sedatives, lithium, opioid analgesics, psychostimulants), hospitalizations (for anxiety, bipolar, depressive/mood, eating and schizophrenia/delusional disorders) and specialist outpatient visits., Results: In Norway, immediate reductions occurred in the general population for medications (-12% antidepressants to -7% hypnotics/sedatives) except for antipsychotics; and hospitalizations (-33% anxiety disorders to -17% bipolar disorders). Increasing slope change occurred for all medications except psychostimulants (+1.1%/month hypnotics/sedatives to +1.7%/month antidepressants); and hospitalization for anxiety disorders (+5.5%/month), depressive/mood disorders (+1.7%/month) and schizophrenia/delusional disorders (+2%/month). In Sweden, immediate reductions occurred for antidepressants (-7%) and opioids (-10%) and depressive/mood disorder hospitalizations (-11%) only with increasing slope change in psychostimulant prescribing of (0.9%/month). In contrast to Norway, increasing slope changes occurred in specialist outpatient visits for depressive/mood disorders, eating disorders and schizophrenia/delusional disorders (+1.5, +1.9 and +2.3%/month, respectively). Similar changes occurred in the pre-existing mental health cohorts., Conclusion: Differences in early COVID-19 policy response may have contributed to differences in adult mental healthcare provision in Norway and Sweden., (© 2024 The Authors. British Journal of Clinical Pharmacology published by John Wiley & Sons Ltd on behalf of British Pharmacological Society.)

Background: Clinical guidelines commonly recommend preventative treatments for people above a risk threshold. Therefore, decision-makers must have faith in risk prediction tools and model-based cost-effectiveness analyses for people at different levels of risk. Two problems that arise are inadequate handling of competing risks of death and failing to account for direct treatment disutility (i.e. the hassle of taking treatments). We explored these issues using two case studies: primary prevention of cardiovascular disease using statins and osteoporotic fracture using bisphosphonates., Objectives: Externally validate three risk prediction tools [QRISK®3, QRISK®-Lifetime, QFracture-2012 (ClinRisk Ltd, Leeds, UK)]; derive and internally validate new risk prediction tools for cardiovascular disease [competing mortality risk model with Charlson Comorbidity Index (CRISK-CCI)] and fracture (CFracture), accounting for competing-cause death; quantify direct treatment disutility for statins and bisphosphonates; and examine the effect of competing risks and direct treatment disutility on the cost-effectiveness of preventative treatments., Design, Participants, Main Outcome Measures, Data Sources: Discrimination and calibration of risk prediction models (Clinical Practice Research Datalink participants: aged 25-84 years for cardiovascular disease and aged 30-99 years for fractures); direct treatment disutility was elicited in online stated-preference surveys (people with/people without experience of statins/bisphosphonates); costs and quality-adjusted life-years were determined from decision-analytic modelling (updated models used in National Institute for Health and Care Excellence decision-making)., Results: CRISK-CCI has excellent discrimination, similar to that of QRISK3 (Harrell's c = 0.864 vs. 0.865, respectively, for women; and 0.819 vs. 0.834, respectively, for men). CRISK-CCI has systematically better calibration, although both models overpredict in high-risk subgroups. People recommended for treatment (10-year risk of ≥ 10%) are younger when using QRISK-Lifetime than when using QRISK3, and have fewer observed events in a 10-year follow-up (4.0% vs. 11.9%, respectively, for women; and 4.3% vs. 10.8%, respectively, for men). QFracture-2012 underpredicts fractures, owing to under-ascertainment of events in its derivation. However, there is major overprediction among people aged 85-99 years and/or with multiple long-term conditions. CFracture is better calibrated, although it also overpredicts among older people. In a time trade-off exercise ( n = 879), statins exhibited direct treatment disutility of 0.034; for bisphosphonates, it was greater, at 0.067. Inconvenience also influenced preferences in best-worst scaling ( n = 631). Updated cost-effectiveness analysis generates more quality-adjusted life-years among people with below-average cardiovascular risk and fewer among people with above-average risk. If people experience disutility when taking statins, the cardiovascular risk threshold at which benefits outweigh harms rises with age (≥ 8% 10-year risk at 40 years of age; ≥ 38% 10-year risk at 80 years of age). Assuming that everyone experiences population-average direct treatment disutility with oral bisphosphonates, treatment is net harmful at all levels of risk., Limitations: Treating data as missing at random is a strong assumption in risk prediction model derivation. Disentangling the effect of statins from secular trends in cardiovascular disease in the previous two decades is challenging. Validating lifetime risk prediction is impossible without using very historical data. Respondents to our stated-preference survey may not be representative of the population. There is no consensus on which direct treatment disutilities should be used for cost-effectiveness analyses. Not all the inputs to the cost-effectiveness models could be updated., Conclusions: Ignoring competing mortality in risk prediction overestimates the risk of cardiovascular events and fracture, especially among older people and those with multimorbidity. Adjustment for competing risk does not meaningfully alter cost-effectiveness of these preventative interventions, but direct treatment disutility is measurable and has the potential to alter the balance of benefits and harms. We argue that this is best addressed in individual-level shared decision-making., Study Registration: This study is registered as PROSPERO CRD42021249959., Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 15/12/22) and is published in full in Health and Social Care Delivery Research ; Vol. 12, No. 4. See the NIHR Funding and Awards website for further award information.

Objective: To assess the uptake of second line antihyperglycaemic drugs among patients with type 2 diabetes mellitus who are receiving metformin., Design: Federated pharmacoepidemiological evaluation in LEGEND-T2DM., Setting: 10 US and seven non-US electronic health record and administrative claims databases in the Observational Health Data Sciences and Informatics network in eight countries from 2011 to the end of 2021., Participants: 4.8 million patients (≥18 years) across US and non-US based databases with type 2 diabetes mellitus who had received metformin monotherapy and had initiated second line treatments., Exposure: The exposure used to evaluate each database was calendar year trends, with the years in the study that were specific to each cohort., Main Outcomes Measures: The outcome was the incidence of second line antihyperglycaemic drug use (ie, glucagon-like peptide-1 receptor agonists, sodium-glucose cotransporter-2 inhibitors, dipeptidyl peptidase-4 inhibitors, and sulfonylureas) among individuals who were already receiving treatment with metformin. The relative drug class level uptake across cardiovascular risk groups was also evaluated., Results: 4.6 million patients were identified in US databases, 61 382 from Spain, 32 442 from Germany, 25 173 from the UK, 13 270 from France, 5580 from Scotland, 4614 from Hong Kong, and 2322 from Australia. During 2011-21, the combined proportional initiation of the cardioprotective antihyperglycaemic drugs (glucagon-like peptide-1 receptor agonists and sodium-glucose cotransporter-2 inhibitors) increased across all data sources, with the combined initiation of these drugs as second line drugs in 2021 ranging from 35.2% to 68.2% in the US databases, 15.4% in France, 34.7% in Spain, 50.1% in Germany, and 54.8% in Scotland. From 2016 to 2021, in some US and non-US databases, uptake of glucagon-like peptide-1 receptor agonists and sodium-glucose cotransporter-2 inhibitors increased more significantly among populations with no cardiovascular disease compared with patients with established cardiovascular disease. No data source provided evidence of a greater increase in the uptake of these two drug classes in populations with cardiovascular disease compared with no cardiovascular disease., Conclusions: Despite the increase in overall uptake of cardioprotective antihyperglycaemic drugs as second line treatments for type 2 diabetes mellitus, their uptake was lower in patients with cardiovascular disease than in people with no cardiovascular disease over the past decade. A strategy is needed to ensure that medication use is concordant with guideline recommendations to improve outcomes of patients with type 2 diabetes mellitus., Competing Interests: Competing interests: This study is undertaken within Observational Health Data Sciences and Informatics, an open collaboration. RK received support from the National Heart, Lung, and Blood Institute of the National Institutes of Health (under award K23HL153775) and the Doris Duke Charitable Foundation (under award, 2022060). He is an Associate Editor of JAMA. He also receives research support, through Yale, from Bristol-Myers Squibb. He is a coinventor of US Provisional Patent Applications 63/177,117 and 63/346,610, unrelated to current work. He is also a founder of Evidence2Health, a precision health platform to improve evidence-based cardiovascular care. TD-S acknowledges receiving financial support from the Instituto de Salud Carlos III (ISCIII; Miguel Servet 2021: CP21/00023). KKCM reports grants from C W Maplethorpe Fellowship, grants from National Institute of Health Research, UK, grants from European Commission Framwork Horizon 2020, grants from Hong Kong Research Grant Council, grants from Innovation and Technology Commission of the Hong Kong Special Administration Region Government, and personal fees from IQVIA outside of the submitted work. DRM was supported by a Wellcome Trust Clinical Research Fellowship (214588/Z/18/Z). MJS is an employee and shareholder of Johnson & Johnson. HK received expenses and/or personal fees from UnitedHealth, Element Science, Aetna, Reality Labs, Tesseract/4Catalyst, F-Prime, the Siegfried and Jensen Law Firm, Arnold and Porter Law Firm, and Martin/Baughman Law Firm. He is a co-founder of Refactor Health and HugoHealth, and is associated with contracts, through Yale New Haven Hospital, from the Centers for Medicare and Medicaid Services and through Yale University from Johnson & Johnson. MAS receives contracts and grants from the National Institutes of Health, the US Department of Veterans Affairs, the US Food and Drug Administration and Janssen Research and Development, the latter two of which are outside the scope of this work. Other authors declare no competing interests., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

RNA, like DNA and proteins, can undergo modifications. To date, over 170 RNA modifications have been identified, leading to the emergence of a new research area known as epitranscriptomics. RNA editing is the most frequent RNA modification in mammalian transcriptomes, and two types have been identified: (1) the most frequent, adenosine to inosine (A-to-I); and (2) the less frequent, cysteine to uracil (C-to-U) RNA editing. Unlike other epitranscriptomic marks, RNA editing can be readily detected from RNA sequencing (RNA-seq) data without any chemical conversions of RNA before sequencing library preparation. Furthermore, analyzing RNA editing patterns from transcriptomic data provides an additional layer of information about the epitranscriptome. As the significance of epitranscriptomics, particularly RNA editing, gains recognition in various fields of biology and medicine, there is a growing interest in detecting RNA editing sites (RES) by analyzing RNA-seq data. To cope with this increased interest, several bioinformatic tools are available. However, each tool has its advantages and disadvantages, which makes the choice of the most appropriate tool for bench scientists and clinicians difficult. Here, we have benchmarked bioinformatic tools to detect RES from RNA-seq data. We provide a comprehensive view of each tool and its performance using previously published RNA-seq data to suggest recommendations on the most appropriate for utilization in future studies.

Background: Concerns have been raised that antipsychotic drug prescribing, which has been associated with increased mortality in people with dementia, might have increased during the COVID-19 pandemic due to social restrictions imposed to limit the spread of SARS-CoV-2. We used multisource, routinely collected health-care data from Wales, UK to investigate prescribing and mortality variations in people with dementia before and during the COVID-19 pandemic., Methods: In this retrospective cohort study, we used individual-level, anonymised, population-scale linked health data to identify adults aged 60 years and older with a diagnosis of dementia in Wales, UK. We used the CVD-COVID-UK initiative to access Welsh routinely collected electronic health record data from the Secure Anonymised Information Linkage (SAIL) Databank. Patients who were alive and registered with a SAIL general practice on Jan 1, 2016, and who received a dementia diagnosis before the age of 60 years and before or during the study period were included. We explored antipsychotic drug prescribing rate changes over 67 months, between Jan 1, 2016, and Aug 1, 2021, overall and stratified by age and dementia subtype. We used time-series analyses to examine all-cause and myocardial infarction and stroke mortality over the study period and identified the leading causes of death in people with dementia between Jan 1, 2020, and Aug 1, 2021., Findings: Of 3 106 690 participants in SAIL between Jan 1, 2016 and Aug 1, 2021, 57 396 people (35 148 [61·2%] women and 22 248 [38·8%] men) met inclusion criteria for this study and contributed 101 428 person-years of follow-up. Of the 57 396 people with dementia, 11 929 (20·8%) were prescribed an antipsychotic drug at any point during follow-up. Accounting for seasonality, antipsychotic drug prescribing increased during the second half of 2019 and throughout 2020. However, the absolute difference in prescribing rates was small, ranging from 1253 prescriptions per 10 000 person-months in March, 2019, to 1305 per 10 000 person-months in September, 2020. All-cause mortality and stroke mortality increased throughout 2020, while myocardial infarction mortality declined. From Jan 1, 2020, to Aug 1, 2021, 1286 (17·1%) of 7508 participants who died had COVID-19 recorded as the underlying cause of death., Interpretation: During the COVID-19 pandemic, antipsychotic drug prescribing in people with dementia in the UK increased slightly; however, it is unlikely that this was solely related to the pandemic and this increase was unlikely to be a major factor in the substantial increase in mortality during 2020. The long-term increase in antipsychotic drug prescribing in younger people and in those with Alzheimer's disease warrants further investigation using resources with access to more granular clinical data. Although deprescribing antipsychotic medications remains an essential aspect of dementia care, the results of this study suggest that changes in prescribing and deprescribing practices as a result of the COVID-19 pandemic are not required., Funding: British Heart Foundation (via the British Heart Foundation Data Science Centre led by Health Data Research UK), and the Scottish Neurological Research Fund., Competing Interests: Declaration of interests CLMS reports a £10 million research grant from 2020 to 2024 to enable set-up of the British Heart Foundation Data Science Centre within Health Data Research UK, the UK's institute for health data science, which as part of its activities has worked with Secure Anonymised Information Linkage Wales (including a small investment of about £130 000 to enable access to the data relevant to this study); and is the Director of the British Heart Foundation Data Science Centre. CS was a co-investigator on a grant paid by the Benter Foundation to the University of Edinburgh, Edinburgh, UK, for dementia research. All other authors declare no competing interests., (Copyright © 2023 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Background: Although morbidity and mortality from COVID-19 have been widely reported, the indirect effects of the pandemic beyond 2020 on other major diseases and health service activity have not been well described., Methods and Results: Analyses used national administrative electronic hospital records in England, Scotland, and Wales for 2016-21. Admissions and procedures during the pandemic (2020-21) related to six major cardiovascular conditions [acute coronary syndrome (ACS), heart failure (HF), stroke/transient ischaemic attack (TIA), peripheral arterial disease (PAD), aortic aneurysm (AA), and venous thromboembolism(VTE)] were compared with the annual average in the pre-pandemic period (2016-19). Differences were assessed by time period and urgency of care.In 2020, there were 31 064 (-6%) fewer hospital admissions [14 506 (-4%) fewer emergencies, 16 560 (-23%) fewer elective admissions] compared with 2016-19 for the six major cardiovascular diseases (CVDs) combined. The proportional reduction in admissions was similar in all three countries. Overall, hospital admissions returned to pre-pandemic levels in 2021. Elective admissions remained substantially below expected levels for almost all conditions in all three countries [-10 996 (-15%) fewer admissions]. However, these reductions were offset by higher than expected total emergency admissions [+25 878 (+6%) higher admissions], notably for HF and stroke in England, and for VTE in all three countries. Analyses for procedures showed similar temporal variations to admissions., Conclusion: The present study highlights increasing emergency cardiovascular admissions during the pandemic, in the context of a substantial and sustained reduction in elective admissions and procedures. This is likely to increase further the demands on cardiovascular services over the coming years., (© The Author(s) 2022. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Objective: To assess the real-world cardiovascular (CV) safety for sulfonylureas (SU), in comparison with dipeptidyl peptidase 4 inhibitors (DPP4i) and thiazolidinediones (TZD), through development of robust methodology for causal inference in a whole nation study., Research Design and Methods: A cohort study was performed including people with type 2 diabetes diagnosed in Scotland before 31 December 2017, who failed to reach HbA1c 48 mmol/mol despite metformin monotherapy and initiated second-line pharmacotherapy (SU/DPP4i/TZD) on or after 1 January 2010. The primary outcome was composite major adverse cardiovascular events (MACE), including hospitalization for myocardial infarction, ischemic stroke, heart failure, and CV death. Secondary outcomes were each individual end point and all-cause death. Multivariable Cox proportional hazards regression and an instrumental variable (IV) approach were used to control confounding in a similar way to the randomization process in a randomized control trial., Results: Comparing SU to non-SU (DPP4i/TZD), the hazard ratio (HR) for MACE was 1.00 (95% CI: 0.91-1.09) from the multivariable Cox regression and 1.02 (0.91-1.13) and 1.03 (0.91-1.16) using two different IVs. For all-cause death, the HR from Cox regression and the two IV analyses was 1.03 (0.94-1.13), 1.04 (0.93-1.17), and 1.03 (0.90-1.17)., Conclusions: Our findings contribute to the understanding that second-line SU for glucose lowering are unlikely to increase CV risk or all-cause mortality. Given their potent efficacy, microvascular benefits, cost effectiveness, and widespread use, this study supports that SU should remain a part of the global diabetes treatment portfolio., (© 2023 by the American Diabetes Association.)