Ayudando a la toma de decisiones en el diagnóstico, tratamiento y seguimiento de úlceras de etiología vascular mediante el empleo de una aplicación móvil / A mobile decision support system for diagnosis, treatment and follow-up of vascular ulcers

Introducción y objetivo: los sistemas de ayuda a la decisión médica (SADM) son sistemas computacionales que utilizan dispositivos inteligentes, lo que facilita el diagnóstico y el tratamiento de múltiples patologías, transformando la atención sanitaria en un sistema dinámico y de precisión. Las úlceras de etiología vascular representan un importante problema de salud que suponen un gran consumo de recursos. La transformación digital puede mejorarla calidad de los diagnósticos, de los tratamientos y de los seguimiento de los pacientes, mejorando la eficacia y la eficiencia de la asistencia sanitaria. El objetivo es desarrollar una aplicación móvil que facilite el diagnóstico y el tratamiento de úlceras de etiología vascular. Métodos: para desarrollar este SADM se elaboraron algoritmos para los diagnósticos y los tratamientos capaces de generar una respuesta correcta, guiando al usuario hacia un diagnóstico más probable o a la aplicación del tratamiento específico. En Android se empleó el entorno de programación Android Studio y el lenguaje de programación JAVA, y para el desarrollo en iOS se empleó XCode y el lenguaje de programación Swift. El diagnóstico de úlceras de etiología vascular incluye: úlcera neuropática, isquémica, neuroisquémica, venosa o flebostática, úlceramixta y úlcera hipertensiva o de Martorell. Resultados: UlcerAPP es visual e intuitiva. Orientará en el diagnóstico en respuesta a los algoritmos desarrollados. Además, podrá accederse al tratamiento específico de cada una de ellas. Incluirá recomendaciones de seguimiento y criterios de derivación. Conclusiones: UlcerAPP es un proyecto desarrollado para mejorar el manejo clínico de las úlceras en el entorno de la Atención Primaria y potenciar el conocimiento de la patología vascular y del tratamiento de las úlceras de dicha etiología. (AU)

Introduction and objective: decision support systems (DSS) are computer systems that use computer devicesor smartphones, facilitating the diagnosis and properly treatment of multiple pathologies, transforming healthcare into a dynamic, preventive and precision system. Vascular ulcers represent an important health problem, witha great consumption of resources. Digital transformation can improve the quality of diagnoses, treatments andpatient follow-up, and therefore improve the effectiveness and efficiency of healthcare. This paper aims to develop UlcerApp, a totally new mobile DSS for vascular ulcers management, which facilitates the diagnosis, treatment andmonitoring of ulcers of vascular etiology, in the primary health care. Methods: for achieving the main purpose of this research work, a decision algorithm will be developed and implemented by an Android (Android Studio- JAVA) and iOS (XCode- Switf ) mobile applications. Results: the App developed which implements the algorithms UlcerApp is capable of diagnose 6 kind of vascularulcers: neuropathic, ischemic, neuroischemic, venous ulcer, mixed ulcer and hypertensive or Martorell ulcer. UlcerAPP is a visual and intuitive application that will guide the user to correct diagnosis. After them, users will be able to access the specific treatment. It will include follow-up recommendations as well as referral criteria. Conclusions: UlcerAPP is a project developed to improve the clinical management of vascular ulcers in the primary health care, enhance knowledge of vascular pathology and treatment of ulcers of said etiology. (AU)

Systematic Review of Telemedicine and eHealth Systems Applied to Vascular Surgery.

OBJECTIVE: The objective of this paper is to review and analyze the current state of telemedicine and ehealth in the field of vascular surgery. METHODS: This paper collects the relevant information obtained after reviewing the articles related to telemedicine in vascular surgery, published from 2012 to 2022 contained in scientific databases. In addition, the results obtained are statistically studied based on various factors, such as the year of publication or the search engine. In this way, we obtain a complete vision of the current state of telemedicine in the field of vascular surgery. RESULTS: After performing this search and applying selection criteria, 29 articles were obtained for subsequent study and discussion, of which 20 were published in the second half of the decade, representing 70% of the results. In the analysis carried out according to the search criteria used, it can be seen that using the word telemedicine we obtained 69% of the articles while with the criteria mHealth and eHealth we only obtained 22% and 9% of the results, respectively. It can be seen that the filter with the most potential content articles was "vascular surgery AND telemedicine". In the analysis performed according to the search engine, it was observed that the Google Scholar database contains 93% of the articles found in the massive search and the relevant articles contained therein represent 52% of the total. CONCLUSION: An upward trend has been observed in recent years, with a clear increase in the number of publications and much lower figures in the first years. One aspect to highlight is that 47.8% of the articles analyzed focus only on postoperative treatment, which may be due to the help provided by telemedicine in detecting surgical site infections by sending images and videos, this being one of the most common postoperative complications. The analyzed works show the importance of telemedicine in vascular surgery and identify possible future lines of research. In the analysis carried out on the origin of the selected relevant papers, an important interest of the US in this topic is demonstrated since more than 50% of the research contains authors from this country, it is also observed that there is no research from Spain, so this research would be an initial step to determine the weaknesses of telemedicine in this field of medicine and a good opportunity to open a research gap in this branch.

Modelo de riesgo de mortalidad en pacientes con sospecha de enfermedad por COVID-19 basado en información del centro coordinador de urgencias / Mortality risk model for patients with suspected COVID-19 based on information available from an emergency dispatch center

Objetivo: Derivar y validar una escala basada en variables recogidas durante la llamada a un centro coordinador de urgencias (CCU) que permita estratificar el riesgo de mortalidad a 2 días en pacientes con sospecha de enfermedad por COVID-19. Método: Estudio multicéntrico retrospectivo que incluyó a los pacientes consecutivos $ 18 años durante 3 meses, catalogados como caso sospechoso de COVID-19 después de la entrevista telefónica del CCU y que precisaron evacuación. Se analizaron variables clínico-epidemiológicas, comorbilidades y resultado de muerte a los 2 días. Se derivó una escala con las variables categóricas asociadas de forma independiente con la mortalidad a 2 días mediante regresión logística, en la cohorte de derivación. La escala se validó mediante una cohorte de validación y otra de revalidación obtenida en una provincia distinta.Resultados. Se incluyeron 2.320 pacientes (edad mediana 79 años, 49,8% mujeres). La mortalidad global fue del 22,6% (376 casos en pacientes con SARS-CoV-2). El modelo incluyó edad, localización (zona rural como variable protectora), institucionalización, desaturación, roncus, taquipnea y alteración del nivel de conciencia. El área bajo la curva (ABC) para la mortalidad a 2 días fue de 0,763 (IC 95%: 0,725-0,802; p < 0,001). La mortalidad en los pacientes de alto riesgo (> 2,4 puntos) fue del 60%. Conclusiones: La escala, derivada a través de información obtenida con datos del CCU, es aplicable a pacientes con sospecha de infección por COVID-19, estratifica el riesgo de mortalidad precoz (menos de 2 días) y puede ser una herramienta que ayude en la toma de decisiones, referidas a su evacuación, destino o vector de transporte. (AU)

Objectives: To develop and validate a scale to stratify risk of 2-day mortality based on data collected during calls to an emergency dispatch center from patients with suspected coronavirus disease 2019 (COVID-19). Material and methods: Retrospective multicenter study of consecutive patients over the age of 18 years with suspected COVID-19 who were transported from home over the course of 3 months after telephone interviews with dispatchers. We analyzed clinical and epidemiologic variables and comorbidities in relation to death within 2 days of the call. Using data from the development cohort, we built a risk model by means of logistic regression analysis of categorical variables that were independently associated with 2-day mortality. The scale was validated first in a validation cohort in the same province and then in a cohort in a different province. Results: A total of 2320 patients were included. The mean age was 79 years, and 49.8% were women. The overall 2-day mortality rate was 22.6% (376 deaths of patients with severe acute respiratory syndrome coronavirus 2 infection). The model included the following factors: age, location (rural location as a protective factor), institutionalization, desaturation, lung sounds (rhonchi), and altered mental status. The area under the receiver operating characteristic curve for death within 2 days was 0.763 (95% CI, 0.725-0.802; P .001). Mortality in patients at high risk (more than 2.4 points on the scale) was 60%. Conclusion: This risk scale derived from information available to an emergency dispatch center is applicable to patients with suspected COVID-19. It can stratify patients by risk of early death (within 2 days), possibly helping with decision making regarding whether to transport from home or what means of transport to use, and destination. (AU)