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BACKGROUND AND OBJECTIVE: Termination of pregnancy in patients with rheumatic diseases is controversial and a bioethical analysis is rarely performed. In this study we analysed the case of a pregnant patient with lupus nephritis unresponsive to treatment, for whom termination of pregnancy is considered. METHODS: The integrative model was applied combining different normative ethical theories. RESULTS: From a utilitarian perspective, termination of pregnancy is justifiable, seeking the greatest benefit for the greatest number of stakeholders. Deontology justifies both terminating and continuing the pregnancy, focusing on the action itself and on autonomy. In virtue ethics the importance of decisions rests with the person who performs the action seeking flourishing; termination of pregnancy would be justifiable. DISCUSSION AND CONCLUSIONS: Interruption of pregnancy is a justifiable solution following the integrative model. Bioethical analysis of paradigmatic cases is essential to ensure the best possible action and as a precedent for future similar situations in rheumatology.
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Aborto Inducido , Nefritis Lúpica , Femenino , Humanos , Embarazo , Aborto Inducido/éticaRESUMEN
The attitudes toward emerging COVID-19 vaccines have been of great interest worldwide, especially among vulnerable populations such as patients with rheumatic and musculoskeletal diseases (RMDs). The aim of this study was to analyze the relationship between the nationwide number of COVID-19 cases and deaths, and vaccine acceptance or hesitancy of patients with RMDs from four patient care centers in Mexico. Furthermore, we explored differences in acceptance according to specific diagnoses: rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE). This ecological study was a secondary analysis of a cross-sectional study using a validated questionnaire to measure vaccine acceptance. We generated a global Likert scale to evaluate overall attitudes toward the COVID-19 vaccine. We analyzed data from 1336 patients from March to September 2021: 85.13% (1169) were women, with a mean age of 47.87 (SD 14.14) years. The most frequent diagnoses were RA (42.85%, 559) and SLE (27.08%, 393). 635(47.52%) patients were unvaccinated, 253(18.93%) had one dose and 478(35.77%) had two doses. Of all participating patients, 94% were accepting toward the COVID-19 vaccine. Vaccine acceptance remained consistently high throughout the study. However, differences in vaccine acceptance are identified when comparing diagnoses. The peak of the national epidemic curve coincided with an increase in hesitancy among patients with RA. Contrastingly, patients with SLE became more accepting as the epidemic curve peaked. Mexican patients show high acceptance of the COVID-19 vaccine, influenced in part by a patient's specific diagnosis. Furthermore, vaccine acceptance increased mirroring the curve of COVID-19 cases and deaths in the country. This should be taken into consideration when updating recommendations for clinical practice.
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Artritis Reumatoide , COVID-19 , Lupus Eritematoso Sistémico , Enfermedades Reumáticas , Vacunas , Humanos , Femenino , Persona de Mediana Edad , Masculino , Vacunas contra la COVID-19 , COVID-19/epidemiología , COVID-19/prevención & control , Estudios Transversales , Enfermedades Reumáticas/epidemiología , Artritis Reumatoide/epidemiología , Lupus Eritematoso Sistémico/epidemiología , VacunaciónRESUMEN
Health informatics and biomedical computing have introduced the use of computer methods to analyze clinical information and provide tools to assist clinicians during the diagnosis and treatment of diverse clinical conditions. With the amount of information that can be obtained in the healthcare setting, new methods to acquire, organize, and analyze the data are being developed each day, including new applications in the world of big data and machine learning. In this review, first we present the most basic concepts in data science, including the structural hierarchy of information and how it is managed. A section is dedicated to discussing topics relevant to the acquisition of data, importantly the availability and use of online resources such as survey software and cloud computing services. Along with digital datasets, these tools make it possible to create more diverse models and facilitate collaboration. After, we describe concepts and techniques in machine learning used to process and analyze health data, especially those most widely applied in rheumatology. Overall, the objective of this review is to aid in the comprehension of how data science is used in health, with a special emphasis on the relevance to the field of rheumatology. It provides clinicians with basic tools on how to approach and understand new trends in health informatics analysis currently being used in rheumatology practice. If clinicians understand the potential use and limitations of health informatics, this will facilitate interdisciplinary conversations and continued projects relating to data, big data, and machine learning.
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Macrodatos , Informática Médica , Atención a la Salud , Humanos , Aprendizaje Automático , Programas InformáticosRESUMEN
In Mexico, significant ethical and social issues have been raised by the COVID-19 pandemic. Some of the most pressing issues are the extent of restrictive measures, the reciprocal duties to healthcare workers, the allocation of scarce resources, and the need for research. While policy and ethical frameworks are being developed to face these problems, the gender perspective has been largely overlooked in most of the issues at stake. Domestic violence is the most prevalent form of violence against women, which can be exacerbated during a pandemic: stress and economic uncertainty are triggers for abuse, and confinement limits access to support networks. Confinement also exacerbates the unfair distribution of unpaid labor, which is disproportionately assigned to women and girls, and highlights inequality in the overall labor market. Lack of security measures has resulted in attacks towards health workers, particularly female nurses, due to fear of contamination. Finally, resource results in lack of access to other health necessities, including sexual and reproductive health services. Research across all disciplines to face-and to learn from-this crisis should be done through a gender lens, because understanding the realities of women is essential to understand the pandemic's true effects in Mexico and the world.
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COVID-19/epidemiología , Accesibilidad a los Servicios de Salud/ética , Sexismo/ética , Violencia Doméstica/estadística & datos numéricos , Empleo/estadística & datos numéricos , Femenino , Humanos , México/epidemiología , Pandemias , SARS-CoV-2 , Factores SexualesRESUMEN
Big data analytics and processing through artificial intelligence (AI) are increasingly being used in the health sector. This includes both clinical and research settings, and newly in specialties like rheumatology. It is, however, important to consider how these new methodologies are used, and particularly the sensitivities associated with personal information. Based on current applications in rheumatology, this article provides a narrative review of the bioethical perspectives of big data. It presents examples of databases, data analytic methods, and AI in this specialty to address four main ethical issues: privacy and confidentiality, informed consent, the impact on the medical profession, and justice. The use of big data and AI processing in healthcare has great potential to improve the quality of clinical care, including through better diagnosis, treatment, and prognosis. They may also increase patient and societal participation and engagement in healthcare and research. Developing these methodologies and using the information generated from them in line with ethical standards could positively affect the design of global health policies and introduce a new phase in the democratization of health.Key Points⢠Current applications of big data, data analytics, and AI in rheumatology-including registries, machine learning algorithms, and consumer-facing platforms-raise issues in four main bioethical areas: privacy and confidentiality, informed consent, the impact on the medical profession, and justice.⢠Bioethical concerns about rheumatology registries require careful consideration of privacy provisions, set within the context of local, national, and regional law.⢠Machine learning and big data aid diagnosis, treatment, and prognosis, but the final decision about the use of information from algorithms should be left to rheumatology specialists to maintain the promise of fiduciary obligations in the physician-patient relationship.⢠International collaboration in big data projects and increased patient engagement could be ways to counteract health inequalities in the practice of rheumatology, even on a global scale.
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Macrodatos , Discusiones Bioéticas , Reumatología , Inteligencia Artificial , Confidencialidad , Medicina Basada en la Evidencia , Humanos , Difusión de la Información , Almacenamiento y Recuperación de la Información , Aprendizaje AutomáticoRESUMEN
Scorpions are predator arachnids of ancient origin and worldwide distribution. Two scorpion species, Vaejovis smithi and Centruroides limpidus, were found to harbor two different Mollicutes phylotypes: a Scorpion Mycoplasma Clade (SMC) and Scorpion Group 1 (SG1). Here we investigated, using a targeted gene sequencing strategy, whether these Mollicutes were present in 23 scorpion morphospecies belonging to the Vaejovidae, Carboctonidae, Euscorpiidae, Diplocentridae, and Buthidae families. Our results revealed that SMC is found in a species-specific association with Vaejovidae and Buthidae, whereas SG1 is uniquely found in Vaejovidae. SMC and SG1 co-occur only in Vaejovis smithi where 43% of the individuals host both phylotypes. A phylogenetic analysis of Mollicutes 16S rRNA showed that SMC and SG1 constitute well-delineated phylotypes. Additionally, we found that SMC and scorpion phylogenies are significantly congruent, supporting the observation that a cospeciation process may have occurred. This study highlights the phylogenetic diversity of the scorpion associated Mollicutes through different species revealing a possible cospeciation pattern.
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Mycoplasma/genética , ARN Ribosómico 16S/genética , Escorpiones/microbiología , Animales , Marcación de Gen , Especificidad de la EspecieRESUMEN
Genome-wide association studies have revolutionized our understanding of the genetic architecture of complex traits and diseases over the last decade. This knowledge is enabling clinicians, researchers, and direct-to-consumer genetics companies to conduct disease susceptibility testing based on powerful methods such as polygenic risk scoring. However, these technologies raise a set of complex ethical, legal, social, and policy considerations. Here we review and discuss a series of ethical dilemmas associated with susceptibility genetic testing for the two most common late-onset neurodegenerative diseases, Alzheimer's and Parkinson's disease, including testing in asymptomatic individuals. Among others, these include informed consent, disclosure of results and unexpected findings, mandatory screening, privacy and confidentiality, and stigma and genetic discrimination. Importantly, appropriate counseling is a deciding factor for the ethical soundness of genetic testing, which poses a challenge for the regulation of these tests and the training of healthcare professionals. As genetic knowledge about these diseases continues growing and genetic testing becomes more widespread, it is increasingly important to raise awareness among researchers, medical practitioners, genetic counselors, and decision makers about the ethical, legal, and social issues associated with genetic testing for polygenic diseases.