ChatGPT: opportunities and risks in the fields of medical care, teaching, and research.

ChatGPT is a virtual assistant with artificial intelligence (AI) that uses natural language to communicate, i.e., it holds conversations as those that would take place with another human being. It can be applied at all educational levels, including medical education, where it can impact medical training, research, the writing of scientific articles, clinical care, and personalized medicine. It can modify interactions between physicians and patients and thus improve the standards of healthcare quality and safety, for example, by suggesting preventive measures in a patient that sometimes are not considered by the physician for multiple reasons. ChatGPT potential uses in medical education, as a tool to support the writing of scientific articles, as a medical care assistant for patients and doctors for a more personalized medical approach, are some of the applications discussed in this article. Ethical aspects, originality, inappropriate or incorrect content, incorrect citations, cybersecurity, hallucinations, and plagiarism are some examples of situations to be considered when using AI-based tools in medicine.

ChatGPT es un asistente virtual con inteligencia artificial que utiliza lenguaje natural para comunicarse, es decir, mantiene conversaciones como las que se tendrían con otro humano. Puede aplicarse en educación a todos los niveles, que incluye la educación médica, en donde puede impactar en la formación, la investigación, la escritura de artículos científicos, la atención clínica y la medicina personalizada. Puede modificar la interacción entre médicos y pacientes para mejorar los estándares de calidad de la atención médica y la seguridad, por ejemplo, al sugerir medidas preventivas en un paciente que en ocasiones no son consideradas por el médico por múltiples causas. Los usos potenciales del ChatGPT en la educación médica, como una herramienta de ayuda en la redacción de artículos científicos, un asistente en la atención para pacientes y médicos para una práctica más personalizada, son algunas de las aplicaciones que se analizan en este artículo. Los aspectos éticos, originalidad, contenido inapropiado o incorrecto, citas incorrectas, ciberseguridad, alucinaciones y plagio son ejemplos de las situaciones a tomar en cuenta al usar las herramientas basadas en inteligencia artificial en medicina.

ChatGPT: oportunidades y riesgos en la asistencia, docencia e investigación médica / ChatGPT: opportunities and risks in the fields of medical care, teaching, and research

Resumen ChatGPT es un asistente virtual con inteligencia artificial que utiliza lenguaje natural para comunicarse, es decir, mantiene conversaciones como las que se tendrían con otro humano. Puede aplicarse en educación a todos los niveles, que incluye la educación médica, tanto para la formación, la investigación, la escritura de artículos científicos, la atención clínica y la medicina personalizada. Puede modificar la interacción entre médicos y pacientes para mejorar los estándares de calidad de la atención médica y la seguridad, por ejemplo, al sugerir medidas preventivas en un paciente que en ocasiones no son consideradas por el médico por múltiples causas. Los usos potenciales del ChatGPT en la educación médica, como una herramienta de ayuda en la redacción de artículos científicos, un asistente en la atención para pacientes y médicos para una práctica más personalizada, son algunas de las aplicaciones que se analizan en este artículo. Los aspectos éticos, originalidad, contenido inapropiado o incorrecto, citas incorrectas, ciberseguridad, alucinaciones y plagio son ejemplos de las situaciones a tomar en cuenta al usar las herramientas basadas en inteligencia artificial en medicina.

Abstract ChatGPT is a virtual assistant with artificial intelligence (AI) that uses natural language to communicate, i.e., it holds conversations as those that would take place with another human being. It can be applied at all educational levels, including medical education, where it can impact medical training, research, the writing of scientific articles, clinical care, and personalized medicine. It can modify interactions between physicians and patients and thus improve the standards of healthcare quality and safety, for example, by suggesting preventive measures in a patient that sometimes are not considered by the physician for multiple reasons. ChatGPT potential uses in medical education, as a tool to support the writing of scientific articles, as a medical care assistant for patients and doctors for a more personalized medical approach, are some of the applications discussed in this article. Ethical aspects, originality, inappropriate or incorrect content, incorrect citations, cybersecurity, hallucinations, and plagiarism are some examples of situations to be considered when using AI-based tools in medicine.

Medicine and the metaverse: current applications and future.

Innovative technologies such as the metaverse and chat GPT-4 (based on artificial intelligence) are present in the daily discourse of society; recently, they have been introduced into medical practice and are bringing about important changes. In the case of the metaverse ("beyond the universe"), various medical schools and departments around the world are beginning to use it as an innovative strategy for teaching subjects such as anatomy, histology, ophthalmology, and simulation in parallel (virtual) worlds for learning and supervision of surgeries, as well as for other applications in medical education and in the doctor-patient relationship. Although it should be regarded as an area of opportunity for the transformation of medicine, it is important to consider the various limitations and risks of the metaverse in medical practice, student training, and physicians' relationship with the health problems they have to deal with in their practice.

Las innovadoras tecnologías del metaverso y el chat GPT4 (basado en inteligencia artificial) están presentes en el discurso cotidiano de la sociedad; recientemente se han introducido en la práctica médica y están provocando importantes cambios. En cuanto al metaverso ("después del universo"), diversas escuelas y facultades de medicina del mundo comienzan a utilizarlo como una estrategia innovadora dirigida a la enseñanza de materias como anatomía, histología, oftalmología y simulación en mundos paralelos (virtuales) para el aprendizaje y supervisión de cirugías, así como para otras aplicaciones en educación médica y en la relación médico-paciente. Si bien debe tomarse en cuenta como un área de oportunidad para la transformación de la medicina, es importante considerar las diversas limitaciones y riesgos del metaverso en la práctica médica, la formación de estudiantes y la relación del médico con los problemas de salud a los que se enfrenta en su práctica.

La medicina y el metaverso: aplicaciones actuales y futuro / Medicine and the metaverse: current applications and future

Resumen Las innovadoras tecnologías del metaverso y el chat GPT4 (basado en inteligencia artificial) están presentes en el discurso cotidiano de la sociedad; recientemente se han introducido en la práctica médica y están provocando importantes cambios. En cuanto al metaverso ("después del universo"), diversas escuelas y facultades de medicina del mundo comienzan a utilizarlo como una estrategia innovadora dirigida a la enseñanza de materias como anatomía, histología, oftalmología y simulación en mundos paralelos (virtuales) para el aprendizaje y supervisión de cirugías, así como para otras aplicaciones en educación médica y en la relación médico-paciente. Si bien debe tomarse en cuenta como un área de oportunidad para la transformación de la medicina, es importante considerar las diversas limitaciones y riesgos del metaverso en la práctica médica, la formación de estudiantes y la relación del médico con los problemas de salud a los que se enfrenta en su práctica.

Abstract Innovative technologies such as the metaverse and chat GPT-4 (based on artificial intelligence) are present in the daily discourse of society; recently, they have been introduced into medical practice and are bringing about important changes. In the case of the metaverse ("beyond the universe"), various medical schools and departments around the world are beginning to use it as an innovative strategy for teaching subjects such as anatomy, histology, ophthalmology, and simulation in parallel (virtual) worlds for learning and supervision of surgeries, as well as for other applications in medical education and in the doctor-patient relationship. Although it should be regarded as an area of opportunity for the transformation of medicine, it is important to consider the various limitations and risks of the metaverse in medical practice, student training, and physicians' relationship with the health problems they have to deal with in their practice.

Factors Associated with Development of Acute Kidney Injury After Liver Transplantation.

BACKGROUND: Early post-liver transplant (LT) acute kidney injury (AKI) has been associated with worse short-term and long-term outcomes, but the incidence and risk factors in our population are unknown. METHODS: We designed a prospective, singlecenter, longitudinal cohort study to determine the incidence of AKI during the immediate postoperative period of LT, and to identify the risk factors associated with AKI after LT. Pre-operative and intraoperative variables were analyzed to determine if there was any correlation with the development of post-operative AKI. RESULTS: Eighty-six patients were included in the final analysis; from them, 45 (52%) developed AKI in the following 30 days after LT. The presence of hepatic encephalopathy prior to LT was the factor most strongly associated with the development of AKI (Relative Risk 3.67, 95% Confidence Interval 1.08-8.95). Other factors associated with AKI development were male gender and a higher serum lactate during surgery. CONCLUSION: AKI was a frequent complication that significantly worsened the prognosis of LT recipients and was associated with an increased 30-day mortality rate. The presence of hepatic encephalopathy strongly predicted the development of severe AKI.

[Artificial intelligence in medicine: present and future]. / Inteligencia artificial en medicina: presente y futuro.

Artificial intelligence (AI) promises a significant transformation of health care in all medical areas, which could represent "Gutenberg moment" for medicine. The future of medical specialties came largely from human interaction and creativity, forcing physicians to evolve and use AI as a tool in patient care. AI will offer patients safety, autonomy, and access to timely medical care in hard-to-reach areas while reducing administrative burden, screen time, and professional burnout for physicians. AI will also make it possible to reduce the frequency of medical errors and improve diagnostic accuracy through the integration, analysis, and interpretation of information by algorithms and software. The safety of repetitive activities will free up time for health personnel and will enhance the doctor-patient relationship, return to personalized attention and interaction with the patient, through accompaniment, communication, empathy, and trust during illness, activities that will never be replaced by AI. It is still necessary to standardize research in the area, which allows improving the quality of scientific evidence knowing its advantages and risks, accelerating its implementation in current medical practice.

La inteligencia artificial (IA) promete una transformación significativa del cuidado de la salud en todas las áreas médicas, lo que podría representar el «momento Gutenberg¼ para la medicina. El futuro de las especialidades médicas dependerá en gran medida de la interacción humana y la creatividad, obligando a los médicos a evolucionar y emplear la IA como una herramienta en la atención del enfermo. La IA ofrecerá a los pacientes seguridad, autonomía y posibilidad de atención médica oportuna en zonas de difícil acceso, y a los médicos les ayudará a disminuir la carga administrativa, el tiempo en pantallas y el agotamiento profesional. La IA permitirá también reducir la frecuencia de errores médicos y mejorar la precisión diagnóstica a través de la integración, el análisis y la interpretación de información por algoritmos y software. La automatización de actividades repetitivas liberará tiempo al personal de salud y potencialmente mejorará la relación médico-paciente, regresando a la atención personalizada y la interacción con el enfermo, a través del acompañamiento, la comunicación, la empatía y la confianza durante la enfermedad, actividades que nunca serán reemplazadas por la IA. Aún es necesario estandarizar la investigación en el área, que permita mejorar la calidad de la evidencia científica conociendo sus ventajas y riesgos, y acelerar su implementación en la práctica médica actual.

Inteligencia artificial en medicina: presente y futuro / Artificial intelligence in medicine: present and future

Resumen La inteligencia artificial (IA) promete una transformación significativa del cuidado de la salud en todas las áreas médicas, lo que podría representar el «momento Gutenberg¼ para la medicina. El futuro de las especialidades médicas dependerá en gran medida de la interacción humana y la creatividad, obligando a los médicos a evolucionar y emplear la IA como una herramienta en la atención del enfermo. La IA ofrecerá a los pacientes seguridad, autonomía y posibilidad de atención médica oportuna en zonas de difícil acceso, y a los médicos les ayudará a disminuir la carga administrativa, el tiempo en pantallas y el agotamiento profesional. La IA permitirá también reducir la frecuencia de errores médicos y mejorar la precisión diagnóstica a través de la integración, el análisis y la interpretación de información por algoritmos y software. La automatización de actividades repetitivas liberará tiempo al personal de salud y potencialmente mejorará la relación médico-paciente, regresando a la atención personalizada y la interacción con el enfermo, a través del acompañamiento, la comunicación, la empatía y la confianza durante la enfermedad, actividades que nunca serán reemplazadas por la IA. Aún es necesario estandarizar la investigación en el área, que permita mejorar la calidad de la evidencia científica conociendo sus ventajas y riesgos, y acelerar su implementación en la práctica médica actual.

Abstract Artificial intelligence (AI) promises a significant transformation of health care in all medical areas, which could represent "Gutenberg moment" for medicine. The future of medical specialties came largely from human interaction and creativity, forcing physicians to evolve and use AI as a tool in patient care. AI will offer patients safety, autonomy, and access to timely medical care in hard-to-reach areas while reducing administrative burden, screen time, and professional burnout for physicians. AI will also make it possible to reduce the frequency of medical errors and improve diagnostic accuracy through the integration, analysis, and interpretation of information by algorithms and software. The safety of repetitive activities will free up time for health personnel and will enhance the doctor-patient relationship, return to personalized attention and interaction with the patient, through accompaniment, communication, empathy, and trust during illness, activities that will never be replaced by AI. It is still necessary to standardize research in the area, which allows improving the quality of scientific evidence knowing its advantages and risks, accelerating its implementation in current medical practice.

TREATMENT STRATEGIES AND OUTCOME OF PARVOVIRUS B19 INFECTION IN KIDNEY TRANSPLANT RECIPIENTS: A CASE SERIES AND LITERATURE REVIEW OF 128 PATIENTS.

BACKGROUND: There is no specific antiviral treatment for parvovirus B19 (PVB19) infection. OBJECTIVE: The objective of this study was to study the treatment and outcome of PVB19 infection in kidney transplant recipients (KTR) at our institution, and cases published in the medical literature. METHODS: We conducted a retrospective review of PVB19 infection in KTR at an academic medical center over a 16-year period and summarized the data on its treatment and outcome in 120 KTR in the medical literature. RESULTS: In our cohort of eight patients, the median time to the onset of PVB19 disease was 7.2 weeks after transplantation. All patients had severe aregenerative anemia (mean hemoglobin (Hb) of 6.2 ± 1.0 g/dl); all were treated with a reduction in their immunosuppressive regimen and the administration of single-dose intravenous immunoglobulin (IVIG) (mean total dosage of 0.87 ± 0.38 g/kg). The median time to anemia improvement (Hb >10 g/dl) was 3-week post-treatment. No recurrences were documented during follow-up (median 25 months). Among 128 patients (including our cohort of 8 and 120 reported in literature), therapeutic strategies included: 43% IVIG alone, 39% IVIG and reduced immunosuppression, 9% reduction of immunosuppression, and 9% conservative therapy. Clinical relapses were observed in 35% of 71 reported cases. CONCLUSIONS: In KTR, decreasing immunosuppression and the administration of low-dose immunoglobulin seem to be not worse than the standard dose in PVB19 infection.

Treatment strategies and outcome of parvovirus b19 infection in kidney transplant recipients: a case series and literature review of 128 patients.

Abstract Background There is no specific antiviral treatment for parvovirus B19 (PVB19) infection. Objective The objective of this study was to study the treatment and outcome of PVB19 infection in kidney transplant recipients (KTR) at our institution, and cases published in the medical literature. Methods We conducted a retrospective review of PVB19 infection in KTR at an academic medical center over a 16-year period and summarized the data on its treatment and outcome in 120 KTR in the medical literature. Results In our cohort of eight patients, the median time to the onset of PVB19 disease was 7.2 weeks after transplantation. All patients had severe aregenerative anemia (mean hemoglobin (Hb) of 6.2 ± 1.0 g/dl); all were treated with a reduction in their immunosuppressive regimen and the administration of single-dose intravenous immunoglobulin (IVIG) (mean total dosage of 0.87 ± 0.38 g/kg). The median time to anemia improvement (Hb >10 g/dl) was 3-week post-treatment. No recurrences were documented during follow-up (median 25 months). Among 128 patients (including our cohort of 8 and 120 reported in literature), therapeutic strategies included: 43% IVIG alone, 39% IVIG and reduced immunosuppression, 9% reduction of immunosuppression, and 9% conservative therapy. Clinical relapses were observed in 35% of 71 reported cases. Conclusions In KTR, decreasing immunosuppression and the administration of low-dose immunoglobulin seem to be not worse than the standard dose in PVB19 infection.

SerpinA3 in the Early Recognition of Acute Kidney Injury to Chronic Kidney Disease (CKD) transition in the rat and its Potentiality in the Recognition of Patients with CKD.

Recognizing patients at early phases of chronic kidney disease (CKD) is difficult, and it is even more challenging to predict acute kidney injury (AKI) and its transition to CKD. The gold standard to timely identify renal fibrosis is the kidney biopsy, an invasive procedure not usually performed for this purpose in clinical practice. SerpinA3 was identified by high-resolution-mass-spectrometry in urines from animals with CKD. An early and progressive elevation of urinary SerpinA3 (uSerpinA3) was observed during the AKI to CKD transition together with SerpinA3 relocation from the cytoplasm to the apical tubular membrane in the rat kidney. uSerpinA3/alpha-1-antichymotrypsin was significantly increased in patients with CKD secondary to focal and segmental glomerulosclerosis (FSGS), ANCA associated vasculitis (AAV) and proliferative class III and IV lupus nephritis (LN). uSerpinA3 levels were independently and positively associated with renal fibrosis. In patients with class V LN, uSerpinA3 levels were not different from healthy volunteers. uSerpinA3 was not found in patients with systemic inflammatory diseases without renal dysfunction. Our observations suggest that uSerpinA3 can detect renal fibrosis and inflammation, with a particular potential for the early detection of AKI to CKD transition and for the differentiation among lupus nephritis classes III/IV and V.

Heat shock protein 72 (Hsp72) specific induction and temporal stability in urine samples as a reliable biomarker of acute kidney injury (AKI).

We demonstrated that urinary heat shock protein of 72 KDa (Hsp72) is a sensitive biomarker for the early detection of acute kidney injury (AKI). However, whether Hsp72 induction during an AKI episode is kidney-specific is unknown, as well as, the degree of Hsp72 stability in urine samples. In rats that underwent bilateral renal ischemia and reperfusion (I/R), Hsp72 levels were evaluated in several tissues and in collected urines under different storage and temperature conditions, as well as in variable numbers of freeze-thaw cycles. The effect of room temperature and five freeze-thaw cycles on urinary Hsp72 levels was also evaluated in urine samples from AKI patients. We found that Hsp72 increased exclusively in the renal cortex of I/R group, emphasizing its performance as an AKI biomarker. Urinary-Hsp72 remained constant at room temperature (48 h), during 9 months of storage and was not affected by five freeze/thaw cycles.