Отдаленные результаты хирургического лечения врожденных пороков сердца и возможные механизмы их улучшения

Highlights. Congenital heart disease (CHD) is estimated to occur nearly in one per 100 newborns and a third of these babies are in need of corrective procedures. There is a downward trend in mortality associated with advances in surgical treatment and perioperative care. An increasing number of patients with corrected CHD are accumulating in the population. This article provides a literary review of the current state of long-term outcomes of CHD corrections and possible mechanisms for improving late outcomes.Abstract The article analyzes the literature on long-term results of surgical treatment of congenital heart defects and possible mechanisms for their improvement. The bibliographic method was used. The analysis of domestic and foreign literary sources with a search depth of 20 years is carried out. The criteria for including publications were: access to full-text publications, original research, scientific and review articles. Exclusion criteria: abstracts and summaries of publications. The following search queries were formulated for the review: in English: late outcomes of corrections of congenital heart defects, in Russian: long-term results of corrections of congenital heart defects, long-term results after corrections of congenital heart defects. The used search engines are Science Direct, PubMed, Cyberleninka, E-library. The analysis of the literary data showed that the volume and duration of patients’ observation that underwent surgical correction of congenital heart defects remain controversial. In world and domestic practice modern digital technologies are used for the purpose of patients remote monitoring. Remote monitoring programs in the Russian Federation are used for such socially significant diseases as diabetes mellitus, bronchial asthma, as well as cardiac rehabilitation of adult patients. There are no similar programs for patients with congenital heart defects. There is a problem of patients remote monitoring after congenital heart defects surgical treatment. In Russia today there is no any comprehensive program for remote monitoring of children after congenital heart disease surgical correction. We believe that a universal remote monitoring system for managing this group of patients must be created.Основные положения. Врожденные пороки сердца встречаются у одного из ста новорожденных, причем треть этих детей нуждаются в корректирующих процедурах. Отмечена тенденция уменьшения смертности, связанная с достижениями в хирургическом лечении и периоперационном уходе. В популяции накапливается все больше пациентов с корригированными врожденными дефектами сердца. В статье оценены современное состояние отдаленных исходов коррекций врожденных пороков сердца и возможные механизмы улучшения поздних результатов по данным литературы.Резюме В статье проведен анализ зарубежной и отечественной литературы, посвященной отдаленным результатам хирургического лечения врожденных пороков сердца и возможным механизмам их улучшения. Глубина поиска – 20 лет. Критерии включения источников: доступ к полному тексту, оригинальные исследования и обзорные статьи. Критерии исключения: абстракты публикаций. Для обзора сформулированы следующие поисковые запросы на английском языке: late outcomes of corrections of congenital heart defects, на русском языке: «отдаленные результаты коррекции врожденных пороков сердца», «долгосрочные результаты коррекции врожденных пороков сердца». Поиск литературы выполнен в системах ScienceDirect, PubMed, «КиберЛенинка», eLIBRARY.ru. Анализ данных показал, что остаются спорными вопросы объема и длительности наблюдения пациентов, перенесших хирургическую коррекцию врожденных пороков сердца. В мировой и отечественной практике применяют современные цифровые технологии с целью дистанционного мониторинга больных. В России программы удаленного отслеживания состояния пациентов используют при таких социально значимых заболеваниях, как сахарный диабет, бронхиальная астма, а также для кардиологической реабилитации взрослых больных. Подобные программы для дистанционного наблюдения детей, перенесших хирургическую коррекцию врожденных патологий сердца, на сегодняшний день в нашей стране отсутствуют. Также актуальна проблема отдаленного контроля состояния детей после хирургического устранения врожденных дефектов сердца. Таким образом, необходимо создание комплексной универсальной системы удаленного мониторинга и ведения данной группы больных

Prediction of COVID-19 diagnosis based on openEHR artefacts

Nowadays, we are facing the worldwide pandemic caused by COVID-19. The complexity and momentum of monitoring patients infected with this virus calls for the usage of agile and scalable data structure methodologies. OpenEHR is a healthcare standard that is attracting a lot of attention in recent years due to its comprehensive and robust architecture. The importance of an open, standardized and adaptable approach to clinical data lies in extracting value to generate useful knowledge that really can help healthcare professionals make an assertive decision. This importance is even more accentuated when facing a pandemic context. Thus, in this study, a system for tracking symptoms and health conditions of suspected or confirmed SARS-CoV-2 patients from a Portuguese hospital was developed using openEHR. All data on the evolutionary status of patients in home care as well as the results of their COVID-19 test were used to train different ML algorithms, with the aim of developing a predictive model capable of identifying COVID-19 infections according to the severity of symptoms identified by patients. The CRISP-DM methodology was used to conduct this research. The results obtained were promising, with the best model achieving an accuracy of 96.25%, a precision of 99.91%, a sensitivity of 92.58%, a specificity of 99.92%, and an AUC of 0.963, using the Decision Tree algorithm and the Split Validation method. Hence, in the future, after further testing, the predictive model could be implemented in clinical decision support systems.This work is funded by "FCT-Fundacao para a Ciencia e Tecnologia" within the R &D Units Project Scope: UIDB/00319/2020. D.F. thanks the FundacAo para a Ciencia e Tecnologia (FCT), Portugal for the Grant 2021.06308.BD

FLEXOR: A support tool for efficient and seamless experiment data processing to evaluate musculo-articular stiffness

This research has been supported by the project DEP2015- 70980-R of the Spanish Ministry of Economy and Competitiveness (MINECO) and European Regional Development Fund (ERDF), as well as, received inputs from the COST Action IC1303 AAPELE

A methodology based on openEHR archetypes and software agents for developing e-health applications reusing legacy systems

Background and objective In Pervasive Healthcare, novel information and communication technologies are applied to support the provision of health services anywhere, at anytime and to anyone. Since health systems may offer their health records in different electronic formats, the openEHR Foundation prescribes the use of archetypes for describing clinical knowledge in order to achieve semantic interoperability between these systems. Software agents have been applied to simulate human skills in some healthcare procedures. This paper presents a methodology, based on the use of openEHR archetypes and agent technology, which aims to overcome the weaknesses typically found in legacy healthcare systems, thereby adding value to the systems. Methods This methodology was applied in the design of an agent-based system, which was used in a realistic healthcare scenario in which a medical staff meeting to prepare a cardiac surgery has been supported. We conducted experiments with this system in a distributed environment composed by three cardiology clinics and a center of cardiac surgery, all located in the city of Marília (São Paulo, Brazil). We evaluated this system according to the Technology Acceptance Model. Results The case study confirmed the acceptance of our agent-based system by healthcare professionals and patients, who reacted positively with respect to the usefulness of this system in particular, and with respect to task delegation to software agents in general. The case study also showed that a software agent-based interface and a tools-based alternative must be provided to the end users, which should allow them to perform the tasks themselves or to delegate these tasks to other people. Conclusions A Pervasive Healthcare model requires efficient and secure information exchange between healthcare providers. The proposed methodology allows designers to build communication systems for the message exchange among heterogeneous healthcare systems, and to shift from systems that rely on informal communication of actors to a more automated and less error-prone agent-based system. Our methodology preserves significant investment of many years in the legacy systems and allows developers to extend them adding new features to these systems, by providing proactive assistance to the end-users and increasing the user mobility with an appropriate support

A methodology based on openEHR archetypes and software agents for developing e-health applications reusing legacy systems

Background and objective In Pervasive Healthcare, novel information and communication technologies are applied to support the provision of health services anywhere, at anytime and to anyone. Since health systems may offer their health records in different electronic formats, the openEHR Foundation prescribes the use of archetypes for describing clinical knowledge in order to achieve semantic interoperability between these systems. Software agents have been applied to simulate human skills in some healthcare procedures. This paper presents a methodology, based on the use of openEHR archetypes and agent technology, which aims to overcome the weaknesses typically found in legacy healthcare systems, thereby adding value to the systems. Methods This methodology was applied in the design of an agent-based system, which was used in a realistic healthcare scenario in which a medical staff meeting to prepare a cardiac surgery has been supported. We conducted experiments with this system in a distributed environment composed by three cardiology clinics and a center of cardiac surgery, all located in the city of Marília (São Paulo, Brazil). We evaluated this system according to the Technology Acceptance Model. Results The case study confirmed the acceptance of our agent-based system by healthcare professionals and patients, who reacted positively with respect to the usefulness of this system in particular, and with respect to task delegation to software agents in general. The case study also showed that a software agent-based interface and a tools-based alternative must be provided to the end users, which should allow them to perform the tasks themselves or to delegate these tasks to other people. Conclusions A Pervasive Healthcare model requires efficient and secure information exchange between healthcare providers. The proposed methodology allows designers to build communication systems for the message exchange among heterogeneous healthcare systems, and to shift from systems that rely on informal communication of actors to a more automated and less error-prone agent-based system. Our methodology preserves significant investment of many years in the legacy systems and allows developers to extend them adding new features to these systems, by providing proactive assistance to the end-users and increasing the user mobility with an appropriate support

Metodología integral de protección de datos electrónicos médicos, aplicado al almacenamiento, acceso y análisis forense de las historias clínicas en Colombia

La Historia Clínica tiene unas características especiales que requieren un manejo diferente desde el punto de vista de la seguridad informática. Dadas las condiciones que anteceden para mantener su integridad, además de cumplir con la normatividad propia de cada país, se hace conveniente la transformación de la forma tradicional mediante manuscritos, a la utilización de las tecnologías de información. Con esta evolución, los incidentes de seguridad cibernética en un sector tan crítico como este, tienen un gran impacto en la sociedad, considerando que la información de la historia clínica podría ser usada de manera inadecuada, permitiendo el robo de identidad, ingreso no autorizado, daño de la información u alteración de los datos del paciente. Aplicando la Resolución Colombiana 1995 de 1999 [1], se desprende que la información del paciente debe registrarse cronológicamente, de la misma manera que los actos médicos, procedimientos ejecutados por el equipo de médico o cualquiera intervenga en su atención, a lo largo de los planteamientos hechos, los sistemas de salud se van volviendo cada vez más vulnerables a incidentes de seguridad informática, en consecuencia a la automatización, las tecnologías de información, los volúmenes de información y la conexión con los pacientes; Al mismo tiempo la inclusión de la seguridad en los sistemas de información de salud no es una prioridad. El resultado de esta investigación es una metodología integral que permita asegurar la accesibilidad al sistema, garantizar la integridad de los datos, además de la posibilidad de realizar un análisis forense en caso de ser vulnerado, al mismo tiempo logrando mitigar las causas, generando alertas, y factores por los cuales los datos electrónicos médicos en historias clínicas no logran ser protegidos.The Clinical History has some special characteristics that require different management from the point of view of computer security. Given the above conditions to maintain its integrity, in addition for complying with the regulations of each country, it is convenient to modify the traditional form by means of manuscripts, to the use of information technologies. With this evolution, the incidents of cybersecurity in a sector as critical as this one, have a great impact on society, such as information on history. Damage to information or alteration of patient data. Applying Colombian Resolution 1995 of 1999 [1], it follows that patient information must correspond chronologically, in the same way as medical acts, procedures performed by the doctor's team or any intervention in their care, throughout the given the facts, health systems are becoming increasingly vulnerable to computer security, automation, information technology, information and connection with patients; At the same time, the inclusion of security in health information systems is not a priority. The result of this research is a comprehensive methodology that allows accessibility in the system, the integrity of the data, the possibility of carrying out an analysis in the case of vulnerability, the same time in which mitigation of the causes is being achieved, generating alerts, electronic data in clinics cannot be protecte

Performance Evaluation of Smart Decision Support Systems on Healthcare

Medical activity requires responsibility not only from clinical knowledge and skill but also on the management of an enormous amount of information related to patient care. It is through proper treatment of information that experts can consistently build a healthy wellness policy. The primary objective for the development of decision support systems (DSSs) is to provide information to specialists when and where they are needed. These systems provide information, models, and data manipulation tools to help experts make better decisions in a variety of situations. Most of the challenges that smart DSSs face come from the great difficulty of dealing with large volumes of information, which is continuously generated by the most diverse types of devices and equipment, requiring high computational resources. This situation makes this type of system susceptible to not recovering information quickly for the decision making. As a result of this adversity, the information quality and the provision of an infrastructure capable of promoting the integration and articulation among different health information systems (HIS) become promising research topics in the field of electronic health (e-health) and that, for this same reason, are addressed in this research. The work described in this thesis is motivated by the need to propose novel approaches to deal with problems inherent to the acquisition, cleaning, integration, and aggregation of data obtained from different sources in e-health environments, as well as their analysis. To ensure the success of data integration and analysis in e-health environments, it is essential that machine-learning (ML) algorithms ensure system reliability. However, in this type of environment, it is not possible to guarantee a reliable scenario. This scenario makes intelligent SAD susceptible to predictive failures, which severely compromise overall system performance. On the other hand, systems can have their performance compromised due to the overload of information they can support. To solve some of these problems, this thesis presents several proposals and studies on the impact of ML algorithms in the monitoring and management of hypertensive disorders related to pregnancy of risk. The primary goals of the proposals presented in this thesis are to improve the overall performance of health information systems. In particular, ML-based methods are exploited to improve the prediction accuracy and optimize the use of monitoring device resources. It was demonstrated that the use of this type of strategy and methodology contributes to a significant increase in the performance of smart DSSs, not only concerning precision but also in the computational cost reduction used in the classification process. The observed results seek to contribute to the advance of state of the art in methods and strategies based on AI that aim to surpass some challenges that emerge from the integration and performance of the smart DSSs. With the use of algorithms based on AI, it is possible to quickly and automatically analyze a larger volume of complex data and focus on more accurate results, providing high-value predictions for a better decision making in real time and without human intervention.A atividade médica requer responsabilidade não apenas com base no conhecimento e na habilidade clínica, mas também na gestão de uma enorme quantidade de informações relacionadas ao atendimento ao paciente. É através do tratamento adequado das informações que os especialistas podem consistentemente construir uma política saudável de bem-estar. O principal objetivo para o desenvolvimento de sistemas de apoio à decisão (SAD) é fornecer informações aos especialistas onde e quando são necessárias. Esses sistemas fornecem informações, modelos e ferramentas de manipulação de dados para ajudar os especialistas a tomar melhores decisões em diversas situações. A maioria dos desafios que os SAD inteligentes enfrentam advêm da grande dificuldade de lidar com grandes volumes de dados, que é gerada constantemente pelos mais diversos tipos de dispositivos e equipamentos, exigindo elevados recursos computacionais. Essa situação torna este tipo de sistemas suscetível a não recuperar a informação rapidamente para a tomada de decisão. Como resultado dessa adversidade, a qualidade da informação e a provisão de uma infraestrutura capaz de promover a integração e a articulação entre diferentes sistemas de informação em saúde (SIS) tornam-se promissores tópicos de pesquisa no campo da saúde eletrônica (e-saúde) e que, por essa mesma razão, são abordadas nesta investigação. O trabalho descrito nesta tese é motivado pela necessidade de propor novas abordagens para lidar com os problemas inerentes à aquisição, limpeza, integração e agregação de dados obtidos de diferentes fontes em ambientes de e-saúde, bem como sua análise. Para garantir o sucesso da integração e análise de dados em ambientes e-saúde é importante que os algoritmos baseados em aprendizagem de máquina (AM) garantam a confiabilidade do sistema. No entanto, neste tipo de ambiente, não é possível garantir um cenário totalmente confiável. Esse cenário torna os SAD inteligentes suscetíveis à presença de falhas de predição que comprometem seriamente o desempenho geral do sistema. Por outro lado, os sistemas podem ter seu desempenho comprometido devido à sobrecarga de informações que podem suportar. Para tentar resolver alguns destes problemas, esta tese apresenta várias propostas e estudos sobre o impacto de algoritmos de AM na monitoria e gestão de transtornos hipertensivos relacionados com a gravidez (gestação) de risco. O objetivo das propostas apresentadas nesta tese é melhorar o desempenho global de sistemas de informação em saúde. Em particular, os métodos baseados em AM são explorados para melhorar a precisão da predição e otimizar o uso dos recursos dos dispositivos de monitorização. Ficou demonstrado que o uso deste tipo de estratégia e metodologia contribui para um aumento significativo do desempenho dos SAD inteligentes, não só em termos de precisão, mas também na diminuição do custo computacional utilizado no processo de classificação. Os resultados observados buscam contribuir para o avanço do estado da arte em métodos e estratégias baseadas em inteligência artificial que visam ultrapassar alguns desafios que advêm da integração e desempenho dos SAD inteligentes. Como o uso de algoritmos baseados em inteligência artificial é possível analisar de forma rápida e automática um volume maior de dados complexos e focar em resultados mais precisos, fornecendo previsões de alto valor para uma melhor tomada de decisão em tempo real e sem intervenção humana