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      Incidence of adverse drug reactions in COVID-19 hospitalised patients through the minimum basic data set

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          Abstract

          Abstract Background: At the beginning of the COVID-19 pandemic many drugs were used with an uncertain benefit/risk profile that needed to be evaluated. The goal of this study was to analyse the incidence of adverse drug reactions (ADRs) and describe the drugs used in COVID-19 hospitalised patients at the beginning of the COVID-19 pandemic through the minimum basic data set (MBDS). Methods: Retrospective observational study that included hospitalised patients with COVID-19 at our centre between March and May 2020 who had ADRs coded in discharge/death medical reports according to the International Classification of Diseases (ICD-10). Those patients with ADRs ascribed to COVID therapy were selected and the causal relationship was evaluated using the Naranjo algorithm. Descriptive statistical analysis was used. Results: We identified 141 ADRs in 110 cases of hospitalisation due to COVID-19 that entailed an incidence of 9.66% (141/1459), CI95% 8.25-11.29. From the ADRs analysed, 60.3% (85/141) were ascribed to COVID therapy. Lopinavir/ritonavir represented 38.8% (33/85) of ADRs, glucocorticoids 23.5% (20/85) and hydroxychloroquine 9.4% (8/85) Out of the ADRs, 31.8% (27/85) were gastrointestinal disorders (probable lopinavir/ritonavir), 27.0% (23/85) blood glucose disorders (probable glucocorticoid) and 17.6% (15/85) hypertransaminasaemia (probable azithromycin, possible lopinavir/ritonavir, possible hydroxychloroquine, possible interferon). Regarding intensity, 64.7% (55/85) were mild cases, 29.4% (25/85) moderate and 5.9% (5/85) severe. The percentage of ADRs that did not require intervention were 24.7% (21/85), 32.9% (28/85) required pharmacological treatment, 40.0% (34/85) suspension of the drug, 1.2% (1/85) close monitoring and 1.2% (1/85) dose reduction. Conclusions: The incidence of ADR in COVID population that required admission at the beginning of the pandemic seems to be higher than in the general population. The MBDS proves to be a useful tool to trace ADRs.

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          Resumen Introducción: La llegada de la pandemia de COVID-19 supuso la utilización de muchos fármacos con un perfil de riesgo/beneficio incierto que debe ser evaluado. El objetivo de este estudio fue analizar la incidencia de reacciones adversas a medicamentos (RAM) y describir los medicamentos utilizados en pacientes hospitalizados por COVID-19 al comienzo de la pandemia a través del conjunto mínimo básico de datos (CMBD). Materiales y métodos: Estudio observacional retrospectivo que incluyó pacientes hospitalizados por COVID-19 en nuestro centro entre marzo y mayo de 2020 que presentaban RAM codificadas en los informes médicos de alta/exitus según la Clasificación Internacional de Enfermedades (CIE-10). Se seleccionaron los pacientes con RAM atribuidas a la terapia COVID-19 y se evaluó la relación causal mediante el algoritmo de Naranjo. Se realizó un análisis estadístico descriptivo. Resultados: Identificamos 141 RAM en 110 casos de hospitalización por COVID19 lo que supone una incidencia del 9,66% (141/1459), IC95% 8,25-11,29. De las RAM analizadas el 60,3% (85/141) se atribuyeron a la terapia COVID. Lopinavir/ritonavir representó el 38,8% (33/85) de las RAM, los glucocorticoides el 23,5% (20/85) y la hidroxicloroquina el 9,4% (8/85). De todas las RAM, el 31,8% (27/85) fueron trastornos gastrointestinales (probable lopinavir /ritonavir), el 27,0% (23/85) trastornos de la glucemia (probable glucocorticoide) y el 17,6% (15/85) hipertransaminasemia (probable azitromicina, posible lopinavir /ritonavir, posible hidroxicloroquina, posible interferón). En cuanto a la intensidad, el 64,7% (55/85) de las RAM fueron casos leves, el 29,4% (25/85) moderados y el 5,9% (5/85) graves. El porcentaje de RAM que no requirió intervención fue 24,7% (21/85), 32,9% (28/85) requirió tratamiento farmacológico, 40,0% (34/85) suspensión del fármaco, 1,2% (1/85) seguimiento estrecho y 1,2% (1/85) reducción de dosis. Conclusiones: La incidencia de RAM en la población con COVID-19 que requirió ingreso al inicio de la pandemia parece ser mayor que en la población general. El CMBD demuestra ser una herramienta útil para rastrear RAM.

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          Under-reporting of adverse drug reactions : a systematic review.

          The purpose of this review was to estimate the extent of under-reporting of adverse drug reactions (ADRs) to spontaneous reporting systems and to investigate whether there are differences between different types of ADRs. A systematic literature search was carried out to identify studies providing a numerical estimate of under-reporting. Studies were included regardless of the methodology used or the setting, e.g. hospital versus general practice. Estimates of under-reporting were either extracted directly from the published study or calculated from the study data. These were expressed as the percentage of ADRs detected from intensive data collection that were not reported to the relevant local, regional or national spontaneous reporting systems. The median under-reporting rate was calculated across all studies and within subcategories of studies using different methods or settings. In total, 37 studies using a wide variety of surveillance methods were identified from 12 countries. These generated 43 numerical estimates of under-reporting. The median under-reporting rate across the 37 studies was 94% (interquartile range 82-98%). There was no significant difference in the median under-reporting rates calculated for general practice and hospital-based studies. Five of the ten general practice studies provided evidence of a higher median under-reporting rate for all ADRs compared with more serious or severe ADRs (95% and 80%, respectively). In comparison, for five of the eight hospital-based studies the median under-reporting rate for more serious or severe ADRs remained high (95%). The median under-reporting rate was lower for 19 studies investigating specific serious/severe ADR-drug combinations but was still high at 85%. This systematic review provides evidence of significant and widespread under-reporting of ADRs to spontaneous reporting systems including serious or severe ADRs. Further work is required to assess the impact of under-reporting on public health decisions and the effects of initiatives to improve reporting such as internet reporting, pharmacist/nurse reporting and direct patient reporting as well as improved education and training of healthcare professionals.
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            Framework for Managing the COVID-19 Infodemic: Methods and Results of an Online, Crowdsourced WHO Technical Consultation

            Background An infodemic is an overabundance of information—some accurate and some not—that occurs during an epidemic. In a similar manner to an epidemic, it spreads between humans via digital and physical information systems. It makes it hard for people to find trustworthy sources and reliable guidance when they need it. Objective A World Health Organization (WHO) technical consultation on responding to the infodemic related to the coronavirus disease (COVID-19) pandemic was held, entirely online, to crowdsource suggested actions for a framework for infodemic management. Methods A group of policy makers, public health professionals, researchers, students, and other concerned stakeholders was joined by representatives of the media, social media platforms, various private sector organizations, and civil society to suggest and discuss actions for all parts of society, and multiple related professional and scientific disciplines, methods, and technologies. A total of 594 ideas for actions were crowdsourced online during the discussions and consolidated into suggestions for an infodemic management framework. Results The analysis team distilled the suggestions into a set of 50 proposed actions for a framework for managing infodemics in health emergencies. The consultation revealed six policy implications to consider. First, interventions and messages must be based on science and evidence, and must reach citizens and enable them to make informed decisions on how to protect themselves and their communities in a health emergency. Second, knowledge should be translated into actionable behavior-change messages, presented in ways that are understood by and accessible to all individuals in all parts of all societies. Third, governments should reach out to key communities to ensure their concerns and information needs are understood, tailoring advice and messages to address the audiences they represent. Fourth, to strengthen the analysis and amplification of information impact, strategic partnerships should be formed across all sectors, including but not limited to the social media and technology sectors, academia, and civil society. Fifth, health authorities should ensure that these actions are informed by reliable information that helps them understand the circulating narratives and changes in the flow of information, questions, and misinformation in communities. Sixth, following experiences to date in responding to the COVID-19 infodemic and the lessons from other disease outbreaks, infodemic management approaches should be further developed to support preparedness and response, and to inform risk mitigation, and be enhanced through data science and sociobehavioral and other research. Conclusions The first version of this framework proposes five action areas in which WHO Member States and actors within society can apply, according to their mandate, an infodemic management approach adapted to national contexts and practices. Responses to the COVID-19 pandemic and the related infodemic require swift, regular, systematic, and coordinated action from multiple sectors of society and government. It remains crucial that we promote trusted information and fight misinformation, thereby helping save lives.
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              How to Fight an Infodemic: The Four Pillars of Infodemic Management

              In this issue of the Journal of Medical Internet Research, the World Health Organization (WHO) is presenting a framework for managing the coronavirus disease (COVID-19) infodemic. Infodemiology is now acknowledged by public health organizations and the WHO as an important emerging scientific field and critical area of practice during a pandemic. From the perspective of being the first “infodemiolgist” who originally coined the term almost two decades ago, I am positing four pillars of infodemic management: (1) information monitoring (infoveillance); (2) building eHealth Literacy and science literacy capacity; (3) encouraging knowledge refinement and quality improvement processes such as fact checking and peer-review; and (4) accurate and timely knowledge translation, minimizing distorting factors such as political or commercial influences. In the current COVID-19 pandemic, the United Nations has advocated that facts and science should be promoted and that these constitute the antidote to the current infodemic. This is in stark contrast to the realities of infodemic mismanagement and misguided upstream filtering, where social media platforms such as Twitter have advertising policies that sideline science organizations and science publishers, treating peer-reviewed science as “inappropriate content.”
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                Author and article information

                Journal
                ofil
                Revista de la OFIL
                Rev. OFIL·ILAPHAR
                Organización de Farmacéuticos Ibero-Latinoamericanos (Madrid, Madrid, Spain )
                1131-9429
                1699-714X
                June 2023
                : 33
                : 2
                : 161-168
                Affiliations
                [2] orgnameHospital Universitario Fundación Alcorcón orgdiv1Quality and Management Department España
                [1] orgnameHospital Universitario Fundación Alcorcón orgdiv1Pharmacy Departament España
                Article
                S1699-714X2023000200011 S1699-714X(23)03300200011
                10.4321/s1699-714x2023000200011
                bde73dc0-7a09-4edd-a200-7b25b2fb27b8

                This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

                History
                : 15 September 2021
                : 03 August 2021
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 45, Pages: 8
                Product

                SciELO Spain

                Categories
                Originals

                terapia COVID-19,algoritmo de Naranjo,relación de causalidad,Minimum basic data set (MBDS),adverse drug reaction (ADR),COVID-19 therapy,Naranjo algorithm,causality relationship,Conjunto mínimo básico de datos (CMBD),reacción adversa a medicamento (RAM)

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