Risk Factors Associated With Bleeding in Children With Cardiac Disease Receiving Extracorporeal Membrane Oxygenation: A Multi-Center Data Linkage Analysis

Background: Bleeding is a common complication of extracorporeal membrane oxygenation (ECMO) for pediatric cardiac patients. We aimed to identify anticoagulation practices, cardiac diagnoses, and surgical variables associated with bleeding during pediatric cardiac ECMO by combining two established databases, the Collaborative Pediatric Critical Care Research Network (CPCCRN) Bleeding and Thrombosis in ECMO (BATE) and the Extracorporeal Life Support Organization (ELSO) Registry.Methods: All children (<19 years) with a primary cardiac diagnosis managed on ECMO included in BATE from six centers were analyzed. ELSO Registry criteria for bleeding events included pulmonary or intracranial bleeding, or red blood cell transfusion >80 ml/kg on any ECMO day. Bleeding odds were assessed on ECMO Day 1 and from ECMO Day 2 onwards with multivariable logistic regression.Results: There were 187 children with 114 (61%) bleeding events in the study cohort. Biventricular congenital heart disease (94/187, 50%) and cardiac medical diagnoses (75/187, 40%) were most common, and 48 (26%) patients were cannulated directly from cardiopulmonary bypass (CPB). Bleeding events were not associated with achieving pre-specified therapeutic ranges of activated clotting time (ACT) or platelet levels. In multivariable analysis, elevated INR and fibrinogen were associated with bleeding events (OR 1.1, CI 1.0–1.3, p = 0.02; OR 0.77, CI 0.6–0.9, p = 0.004). Bleeding events were also associated with clinical site (OR 4.8, CI 2.0–11.1, p < 0.001) and central cannulation (OR 1.75, CI 1.0–3.1, p = 0.05) but not with cardiac diagnosis, surgical complexity, or cannulation from CPB. Bleeding odds on ECMO day 1 were increased in patients with central cannulation (OR 2.82, 95% CI 1.15–7.08, p = 0.023) and those cannulated directly from CPB (OR 3.32, 95% CI 1.02–11.61, p = 0.047).Conclusions: Bleeding events in children with cardiac diagnoses supported on ECMO were associated with central cannulation strategy and coagulopathy, but were not modulated by achieving pre-specified therapeutic ranges of monitoring assays.

Precision Medicine for Hypertension Patients with Type 2 Diabetes via Reinforcement Learning

Precision medicine is a new approach to understanding health and disease based on patient-specific data such as medical diagnoses; clinical phenotype; biologic investigations such as laboratory studies and imaging; and environmental, demographic, and lifestyle factors. The importance of machine learning techniques in healthcare has expanded quickly in the last decade owing to the rising availability of vast multi-modality data and developed computational models and algorithms. Reinforcement learning is an appealing method for developing efficient policies in various healthcare areas where the decision-making process is typically defined by a long period or a sequential process. In our research, we leverage the power of reinforcement learning and electronic health records of South Koreans to dynamically recommend treatment prescriptions, which are personalized based on patient information of hypertension. Our proposed reinforcement learning-based treatment recommendation system decides whether to use mono, dual, or triple therapy according to the state of the hypertension patients. We evaluated the performance of our personalized treatment recommendation model by lowering the occurrence of hypertension-related complications and blood pressure levels of patients who followed our model’s recommendation. With our findings, we believe that our proposed hypertension treatment recommendation model could assist doctors in prescribing appropriate antihypertensive medications.

Körper | Kultur | Konflikt

Society's view of dying and death no longer corresponds to the fixed images with which the corresponding areas of knowledge were associated until a few years ago. For a long time, the supposedly ›unambiguous‹ levels of meaning of this complex issue were stable enough to paralyse social scientific research. For some time now, however, discourses have been emerging that (re)question the normative elements of funeral culture, the treatment of dead bodies and cremation ashes, the labelling of medical diagnoses, and the determination of the boundary between life and death. Today, there is a—quite productive—tension between real practices and cultural guidelines.

What is morally at stake when using algorithms to make medical diagnoses? Expanding the discussion beyond risks and harms

In this paper, we examine the qualitative moral impact of machine learning-based clinical decision support systems in the process of medical diagnosis. To date, discussions about machine learning in this context have focused on problems that can be measured and assessed quantitatively, such as by estimating the extent of potential harm or calculating incurred risks. We maintain that such discussions neglect the qualitative moral impact of these technologies. Drawing on the philosophical approaches of technomoral change and technological mediation theory, which explore the interplay between technologies and morality, we present an analysis of concerns related to the adoption of machine learning-aided medical diagnosis. We analyze anticipated moral issues that machine learning systems pose for different stakeholders, such as bias and opacity in the way that models are trained to produce diagnoses, changes to how health care providers, patients, and developers understand their roles and professions, and challenges to existing forms of medical legislation. Albeit preliminary in nature, the insights offered by the technomoral change and the technological mediation approaches expand and enrich the current discussion about machine learning in diagnostic practices, bringing distinct and currently underexplored areas of concern to the forefront. These insights can contribute to a more encompassing and better informed decision-making process when adapting machine learning techniques to medical diagnosis, while acknowledging the interests of multiple stakeholders and the active role that technologies play in generating, perpetuating, and modifying ethical concerns in health care.

Uncertainty expression in surgical patients of organ removal: a cross-sectional study

Introduction: The surgical treatment of organ removal seems to meet a number of pathologies that emerge as health needs of populations. In this context, the state of uncertainty is installed.Objective: To investigate the uncertainty in illness in surgical patients of organ removal.Method: Cross-sectional study developed with patients admitted to the surgical outpatient clinic of a university hospital. Sociodemographic and clinical variables were collected, in addition to applying Mishel uncertainty in illness scale.Results: The profile of medical diagnoses in the 60 participants showed that the most frequent diseases were the neoplasms. As for the scale application, 68% of the participants presented scores greater than or equal to 80 points. The value found for the Cronbach’s Alpha was 0.842. The surgical procedures abdominal hysterectomy and mastectomy, which were the most prevalent for the participants, are associated with uncertainty domains.Conclusions: High levels of uncertainty demonstrated the need for the management of this condition. The psychosocial aspects of surgical treatments are disregarded at the expense of the clinical restoration, circumstances that neglect the patient’s emotional suffering. The improvement of communication between the health professional and the patient can influence to prevent the manifestation of the lack of information, one of the forms of expressing uncertainty. Aspects such as the patient’s socioeconomic profile, educational level and income must be taken into account in the surgical treatment of organ removal. The uncertainty experienced by these patients needs to be better known and widely disseminated to gain prominence in the health care setting. Introducción: El tratamiento quirúrgico de la extirpación de órganos parece satisfacer una serie de patologías que surgen como necesidades de salud de las poblaciones. En este contexto, se instala el estado de incertidumbre.Objetivo: Investigar la incertidumbre de la extracción de un órgano en pacientes quirúrgicos.Método: Estudio transversal realizado con pacientes hospitalizados en la clínica quirúrgica de un hospital universitario. Variables sociodemográficas y clínicas fueron recogidas, además, se aplicó la escala de incertidumbre en la enfermedad de Mishel.Resultados: El perfil de diagnósticos médicos en los 60 participantes mostró que las enfermedades más frecuentes fueron las neoplasias. Con relación a la aplicación de la escala, el 68% de los participantes presentaron puntuaciones mayores o iguales a 80 puntos. El valor hallado para el alfa de Cronbach fue de 0,842. Los procedimientos quirúrgicos histerectomía abdominal y mastectomía, que fueron los más frecuentes para los participantes, están asociados con áreas de incertidumbre.Conclusiones: Los altos niveles de incertidumbre demostraron la necesidad de la gestión de esta condición. Los aspectos psicosociales de los tratamientos quirúrgicos son desconsiderados a expensas de la restauración clínica, circunstancias en que se descuida el sufrimiento emocional del paciente. La mejora de la comunicación entre los profesionales de la salud y el paciente puede influir para prevenir la manifestación de la falta de información, una de las formas de la expresión de la incertidumbre. Aspectos como el perfil socioeconómico del paciente, el nivel educativo y los ingresos deben tenerse en cuenta en el tratamiento quirúrgico de la extracción de órganos. La incertidumbre experimentada por estos pacientes debe conocerse mejor y difundirse ampliamente para que estos aspectos se destaquen en el entorno de la atención médica. Introdução: O tratamento cirúrgico de retirada de órgãos surge para atender a uma diversidade de patologias que emergem como necessidade de saúde apresentadas pelas populações, sendo considerado um procedimento que provoca no paciente sentimentos de incerteza.Objetivo: Investigar a incerteza na doença, em pacientes cirúrgicos submetidos à retirada de órgão.Método: Estudo transversal desenvolvido com pacientes internados na clínica cirúrgica de um hospital universitário. Coletaram-se as variáveis sociodemográficas e clínicas e aplicou-se a escala da incerteza na doença de Mishel (MUIS).Resultados: O perfil de diagnósticos médicos nos 60 participantes revelou que as doenças mais frequentes foram as neoplasias. Quanto a aplicação da escala, 68% dos participantes apresentaram escores maiores ou iguais a 80 pontos. O valor encontrado para o Alpha de Cronbach foi de 0,842. Os procedimentos cirúrgicos, histerectomia via abdominal e mastectomia, os quais foram os mais prevalentes para os participantes, se associam aos domínios da incerteza.Conclusões: Elevados níveis de incerteza evidenciaram a necessidade do manejo dessa condição. Os aspectos psicossociais dos tratamentos cirúrgicos acabam secundarizados em detrimento do reestabelecimento clínico, circunstância em que se negligencia o sofrimento emocional do paciente. A melhora da comunicação entre o profissional da saúde e o paciente pode influenciar para que não ocorra a manifestação da falta de informação, uma das formas de expressão da incerteza. Aspectos como perfil socioeconômico do paciente, escolaridade e renda devem ser levados em consideração no tratamento cirúrgico de retirada de órgãos. A incerteza vivenciada por esses pacientes precisa ser mais conhecida e amplamente disseminada para ganhar destaque no ambiente de saúde.

Legal Urgency on Designing The Legislation for The Use of Artificial Intelligence in Indonesian Medical Practice

Artificial intelligence (AI) offers the potential for a great improvement in patient care, both in diagnose and disease treatment, and a consequential reduction in healthcare costs, a part of opportunities and challenge are ahead. The use of AI in medicine was significantly developed in some countries. Indonesia as a modern country also has a great change in promoting the use of AI. The study aims to propose on designing the legislation for the use of AI in Indonesian medical practices. The method used in this research is normative juridical approaches with descriptive analysis. The data used are primary legal material namely the Indonesian Penal Code and Law No. 36 of 2009 on Health Law. Meanwhile, the secondary legal material used are books, journals, and other legal documents. The results show that designing the new legislation as the guidance and basis for the use of AI shall give a good impact on the development of health services as practices among other countries. Moreover, Health Act 2009 clearly supported the use of advance technology’s product in medicine. Yet, the application of AI facilitates interpretation follows with high accuracy and speed for medical diagnoses.

General Anxiety Disorder-7 Questionnaire as a marker of low socioeconomic status and inequity

Background: The General Anxiety Disorder-7 (GAD-7) questionnaire is a standard tool used for screening and follow-up of patients with Generalized Anxiety Disorder (GAD). Although it is generally accepted that anxiety correlates with clinical and psychosocial stressors, precise quantitative data is limited on the relations among GAD-7, traditional biomarkers, and other measures of health. Even less is known about how GAD-7 relates to race, ethnicity, and socioeconomic status (SES).We determined how multiple demographic and socioeconomic data correlate with the participant's GAD-7 results when compared with laboratory, physical function, clinical, and other biological markers. Methods: The Project Baseline Health Study (BHS) is a prospective cohort of adults representing several populations in the USA. We analyzed a deeply phenotyped group of 2502 participants from that study. Measures of interest included: clinical markers or history of medical diagnoses; physical function markers including gait, grip strength, balance time, daily steps, and echocardiographic parameters; psychometric measurements; activities of daily living; socioeconomic characteristics; and laboratory results. Results: Higher GAD-7 scores were associated with female sex, younger age, and Hispanic ethnicity. Measures of low SES were also associated with higher scores, including unemployment, income ≤$25,000, and ≤12 years of education. After adjustment for 166 demographic, clinical, laboratory, and symptom characteristics, unemployment and overall higher SES risk scores were highly correlated with anxiety scores. Protective factors included Black race and older age. Limitations: Correlations identified in this cross-sectional study cannot be used to infer causal relationships; further, we were not able to account for possible use of anxiety treatments by study participants. Conclusions: These findings highlight the importance of understanding anxiety as a biopsychosocial entity. Clinicians and provider organizations need to consider both the physical manifestations of the disorder and their patients' social determinants of health when considering treatment pathways and designing interventions.

Nonlinear Optical Investigation of Biochemical Analytes in Blood Serum via Z-Scan Technique

Background and Aims: Biomolecules' optical and nonlinear optical properties are widely used for different medical diagnoses and applications in biophotonic devices. These properties are essential in studying biological processes in living tissues. Aside from biomolecules' linear optical characteristics, their nonlinear optical characteristics have lately been considered. Materials and Methods: In this paper, the nonlinear optical responses of three biochemical analytes in blood serum, including glucose, triglycerides, and cholesterol are examined using the laser-based Z-Scan technique. Hence, different laboratory samples of blood serum with various concentrations of biochemical analytes are taken from patients for this purpose. Results: The normalized transmission curves were taken and analyzed in a closed aperture configuration of the Z-Scan technique and led to evaluating the nonlinear refractive index (n2) as an indicator of nonlinear responses of samples. The results show significant nonlinear optical behaviors of the samples under a strong electrical field of the laser, which leads to the measurement of the nonlinear refractive index (n2) of the samples with an error of less than ̴ 0.5 × 10-8 cm2/w. It is found that the values of nonlinear refractive index (n2) vary proportionally as a function of their concentration in blood serum. Conclusion: The findings of this study imply that the above sample's nonlinear optical response and, probable, those of other biological tissues might be used in medical diagnoses. In addition, the Z-Scan technique might be considered as a complementary method with other conventional diagnostic procedures due to its simplicity and quick experimental approach.

An effective simulation- and measurement-based workflow for enhanced diagnostics in rhinology

Physics-based analyses have the potential to consolidate and substantiate medical diagnoses in rhinology. Such methods are frequently subject to intense investigations in research. However, they are not used in clinical applications, yet. One issue preventing their direct integration is that these methods are commonly developed as isolated solutions which do not consider the whole chain of data processing from initial medical to higher valued data. This manuscript presents a workflow that incorporates the whole data processing pipeline based on a environment. Therefore, medical image data are fully automatically pre-processed by machine learning algorithms. The resulting geometries employed for the simulations on high-performance computing systems reach an accuracy of up to 99.5% compared to manually segmented geometries. Additionally, the user is enabled to upload and visualize 4-phase rhinomanometry data. Subsequent analysis and visualization of the simulation outcome extend the results of standardized diagnostic methods by a physically sound interpretation. Along with a detailed presentation of the methodologies, the capabilities of the workflow are demonstrated by evaluating an exemplary medical case. The pipeline output is compared to 4-phase rhinomanometry data. The comparison underlines the functionality of the pipeline. However, it also illustrates the influence of mucosa swelling on the simulation.

Impact of Common Dizziness Associated Symptoms on Dizziness Handicap in Older Adults

Background: A cross-sectional observational study was designed to determine the impact of dizziness associated symptoms on the dizziness handicap inventory (DHI) in older adults (≥60 years).Methods: In total, 785 individuals referred to a multidisciplinary dizziness unit were assessed. Participants completed self-report questionnaires with general questions about symptoms of dizziness as well as the DHI. The DHI subscores (physical, functional, emotional) were calculated. Medical diagnoses were collected from the medical records of the patients. One-way MANOVA and networking analysis were used to analyze the impact of dizziness associated symptoms on dizziness handicap.Results: Most patients reported swaying dizziness (60.6%) and feeling of unsteadiness (59.8%) with substantial overlap between the types of dizziness. Most frequent dizziness associated symptoms were ear noise/tinnitus, visual problems, and nausea/vomiting. Network analysis revealed that visual disturbances, headache, and hearing impairment were associated with higher DHI and explained 12% of the DHI variance in the linear regression. In the one-way MANOVA visual problems and headache had an effect on all three DHI subscores, while hearing impairment was associated with the functional and emotional subscores of DHI.Conclusion: Distinct dizziness associated symptoms have substantial impact on dizziness handicap in older adults. A multifactorial assessment including these symptoms may assist in tailoring therapies to alleviate dizziness handicap in this group.