Tecnologias em saúde da hanseníase no âmbito da Atenção Primária à Saúde: revisão de escopo / Leprosy health technologies in Primary Health Care: a scoping review / Tecnologías en salud de la lepra en el ámbito de la Atención Primaria a la Salud: revisión del alcance

Objetivo: mapear as tecnologias em saúde para manejo no cuidado à pessoa com hanseníase na Atenção Primária à Saúde. Método: revisão de escopo baseada na metodologia do JBI, em seis bases de dados, seguindo a checklist Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews. Foram incluídos estudos publicados em qualquer idioma, com diferentes abordagens metodológicas. Resultados: os 14 estudos incluídos na revisão mostram que a aplicabilidade de tecnologias para o manejo do cuidado a pessoa com hanseníase na Atenção Primária à Saúde, possibilitam a confirmação de diagnóstico, acompanhamento, monitoramento e prevenção de incapacidades. Conclusão: nota-se que tecnologia em saúde se apresentam como ferramentas que auxiliam no processo de cuidado na assistência a pessoas com hanseníase, a fim de permitir aos profissionais de saúde conhecimento sobre a doença, proporcionando qualidade na sua prática de saúde.

Objective: to map health technologies for managing the care of people with leprosy in Primary Health Care. Method: scoping review based on the JBI methodology in six databases, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist. Studies published in any language were included, with different methodological approaches. Results: the 14 studies included in the review show that the applicability of technologies for the management of care for people with leprosy in Primary Health Care makes it possible to confirm diagnosis, follow-up, monitoring, and prevention of disabilities. Conclusion: it has been noted that health technologies are tools that help in the process of caring for people with leprosy, to provide health professionals with knowledge about the disease, improving quality of health practice.

Objetivo: mapear las tecnologías en salud para el manejo en el cuidado a la persona con lepra en la Atención Primaria a la Salud. Método: revisión del alcance basada en la metodología del JBI, en seis bases de datos, siguiendo la checklist Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for Scoping Reviews. Se han incluido estudios publicados en cualquier idioma, con diferentes enfoques metodológicos. Resultados: los 14 estudios incluidos en la revisión muestran que la aplicabilidad de tecnologías para el manejo del cuidado a la persona con lepra en la Atención Primaria a la Salud posibilita la confirmación de diagnóstico, seguimiento, monitoreo y prevención de incapacidades. Conclusión: se percibe que las tecnologías en salud se presentan como herramientas que ayudan en el proceso de cuidado en la asistencia a personas con lepra, con fines de permitir a los profesionales de salud el acceso al conocimiento sobre la enfermedad, proporcionando calidad en su práctica de salud.

Supporting evidence-based judicial decisions on health care in Brazil: an experience report / Apoio técnico-científico à tomada de decisão judicial em saúde no Brasil: um relato de experiência / Apoyo técnico-científico a la toma de decisiones judiciales en salud en Brasil: un relato de experiencia

Objective: The main objective of this study is to report on the implementation and results of the "Supporting Health-Related Judicial Decisions in Brazil" project conducted at the Health Technology Assessment Center, Hospital Sírio-Libanês through the "Programa de Apoio ao Desenvolvimento Institucional do Sistema Único de Saúde", in Brazil. Methods: This study is an experience report of a project conducted at the Health Technology Assessment Center, Hospital Sírio-Libanês. Results: The activities of the project occurred in 2023 and included two online training courses on primary studies and systematic reviews, 11 one-day workshops with technical-scientific content for members of the Technical Support Centers for the Judiciary (NATJus), 40 online technical-scientific consultations for magistrates on a digital platform, 11 technical-scientific reports addressing the most legally claimed technologies in Brazil; two methodological tools, a national forum (hybrid event), 10 chat-based mentorships for NATJus members; and the maintenance of an open-access blog, by publishing news on relevant topics on law and health. Discussion and conclusion: This project has contributed to the improvement of the judicial decision-making process by providing a range of activities aimed at aiding the prioritization of health technologies that are clearly effective and safe over those that are ineffective, harmful, or have uncertain effects.

Objetivo: O objetivo principal deste estudo é relatar a implementação e os resultados do projeto "Apoio técnico-científico à tomada de decisão judicial em Saúde no Brasil" realizado no Hospital Sírio-Libanês por meio do "Programa de Apoio ao Desenvolvimento Institucional do Sistema Único de Saúde". Métodos: Este estudo é um relato de experiência de um projeto realizado no Núcleo de Avaliação de Tecnologias em Saúde do Hospital Sírio-Libanês. Resultados: As atividades do projeto ocorreram em 2023 e incluíram dois cursos de formação online sobre estudos primários e revisões sistemáticas, 11 oficinas de um dia com conteúdo técnico-científico para membros dos Núcleos de Apoio Técnico ao Judiciário (NATJus), 40 consultas on-line técnico-científicas para magistrados em plataforma digital, 11 relatórios técnico-científicos abordando as tecnologias mais reivindicadas judicialmente no Brasil; duas ferramentas metodológicas, um fórum nacional (evento híbrido), 10 mentorias via chat para membros do NATJus; e a manutenção de um blog de acesso aberto, com publicação de notícias sobre temas relevantes de direito e saúde. Discussão e conclusão: Este projeto contribuiu para a melhoria do processo de tomada de decisão judicial, fornecendo uma série de atividades destinadas a ajudar na priorização de tecnologias de saúde que sejam claramente eficazes e seguras em detrimento daquelas que são ineficazes, prejudiciais ou têm efeitos incertos.

Objetivo: El objetivo principal de este estudio es informar sobre la implementación y los resultados del proyecto "Apoyo a las Decisiones Judiciales Relacionadas con la Salud en Brasil" realizado en el Centro de Tecnología en Salud del Hospital Sírio-Libanês a través del "Programa de Apoio ao Desenvolvimento Institucional do Sistema Único de Saúde", en Brasil. Métodos: Este estudio es un informe de experiencia de un proyecto realizado en el Centro de Tecnología en Salud del Hospital Sírio-Libanês. Resultados: Las actividades del proyecto ocurrieron en 2023 e incluyeron dos cursos de capacitación en línea sobre estudios primarios y revisiones sistemáticas, 11 talleres de un día de contenido técnico-científico para miembros de los Centros de Apoyo Técnico al Poder Judicial (NATJus), 40 consultas técnico-científicas en línea para magistrados en plataforma digital, 11 informes técnico-científicos que abordan las tecnologías más reclamadas legalmente en Brasil; dos herramientas metodológicas, un foro nacional (evento híbrido), 10 mentorías basadas en chat para miembros de NATJus; y el mantenimiento de un blog de acceso abierto, mediante la publicación de noticias sobre temas relevantes en derecho y salud. Discusión y conclusión: Este proyecto ha contribuido a mejorar el proceso de toma de decisiones judiciales proporcionando actividades para priorizar las tecnologías sanitarias claramente eficaces y seguras frente a aquellas que son ineficaces, nocivas o de efectos inciertos.

Setting Ranges in Potential Biomarkers for Type 2 Diabetes Mellitus Patients Early Detection By Sex-An Approach with Machine Learning Algorithms.

Type 2 diabetes mellitus (T2DM) is one of the most common metabolic diseases in the world and poses a significant public health challenge. Early detection and management of this metabolic disorder is crucial to prevent complications and improve outcomes. This paper aims to find core differences in male and female markers to detect T2DM by their clinic and anthropometric features, seeking out ranges in potential biomarkers identified to provide useful information as a pre-diagnostic tool whie excluding glucose-related biomarkers using machine learning (ML) models. We used a dataset containing clinical and anthropometric variables from patients diagnosed with T2DM and patients without TD2M as control. We applied feature selection with three different techniques to identify relevant biomarker models: an improved recursive feature elimination (RFE) evaluating each set from all the features to one feature with the Akaike information criterion (AIC) to find optimal outputs; Least Absolute Shrinkage and Selection Operator (LASSO) with glmnet; and Genetic Algorithms (GA) with GALGO and forward selection (FS) applied to GALGO output. We then used these for comparison with the AIC to measure the performance of each technique and collect the optimal set of global features. Then, an implementation and comparison of five different ML models was carried out to identify the most accurate and interpretable one, considering the following models: logistic regression (LR), artificial neural network (ANN), support vector machine (SVM), k-nearest neighbors (KNN), and nearest centroid (Nearcent). The models were then combined in an ensemble to provide a more robust approximation. The results showed that potential biomarkers such as systolic blood pressure (SBP) and triglycerides are together significantly associated with T2DM. This approach also identified triglycerides, cholesterol, and diastolic blood pressure as biomarkers with differences between male and female actors that have not been previously reported in the literature. The most accurate ML model was selection with RFE and random forest (RF) as the estimator improved with the AIC, which achieved an accuracy of 0.8820. In conclusion, this study demonstrates the potential of ML models in identifying potential biomarkers for early detection of T2DM, excluding glucose-related biomarkers as well as differences between male and female anthropometric and clinic profiles. These findings may help to improve early detection and management of the T2DM by accounting for differences between male and female subjects in terms of anthropometric and clinic profiles, potentially reducing healthcare costs and improving personalized patient attention. Further research is needed to validate these potential biomarkers ranges in other populations and clinical settings.

Green missing spots: Information entropy on greenhouse gas emission disclosure by Brazilian companies.

This study aims to address a critical gap in the literature by examining the incorporation of uncertainty in measuring carbon emissions using the greenhouse gas (GHG) Protocol methodology across all three scopes. By comprehensively considering the various dimensions of CO2 emissions within the context of organizational activities, our research contributes significantly to the existing body of knowledge. We address challenges such as data quality issues and a high prevalence of missing values by using information entropy, techniques for order preference by similarity to ideal solution (TOPSIS), and an artificial neural network (ANN) to analyze the contextual variables. Our findings, derived from the data sample of 56 companies across 18 sectors and 13 Brazilian states between 2017 and 2019, reveal that Scope 3 emissions exhibit the highest levels of information entropy. Additionally, we highlight the pivotal role of public policies in enhancing the availability of GHG emissions data, which, in turn, positively impacts policy-making practices. By demonstrating the potential for a virtuous cycle between improved information availability and enhanced policy outcomes, our research underscores the importance of addressing uncertainty in carbon emissions measurement for advancing effective climate change mitigation strategies.

Patient satisfaction and digital health in primary health care: a scoping review protocol.

Introduction: Using digital health in primary health care (PHC) contributes to reducing costs and travel time, achieving global development goals, improving access, quality and longitudinality of care, and managing health crises. Its evaluation must go beyond the technical-operational aspects to include patient satisfaction, a key element in assessing the quality of care. Objective: To identify and map patient satisfaction (expectations, desires, cultural values) about the adoption of digital health strategies and assess their impact on the quality of care in PHC. Methods: The review will follow the recommendations proposed by the Joanna's Briggs Institute (JBI) manual, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) and the methodology proposed by Arksey and O'Malley and Levac et al. and will be conducted in nine stages. The search will be conducted in health studies databases (MEDLINE via PubMed, EMBASE, CINAHL, Web of Science, and BVS), gray literature, and preprint repositories (Google Scholar and MedRxiv). Two reviewers will select the studies, and the third will analyze possible conflicts. The inclusion criteria comprise studies that have been made available in their entirety, whether they are primary studies or short communications, as well as the following materials extracted from the gray literature: preprints, manuals, government documents, books, guidelines, theses and dissertations. Exclusion criteria include literature reviews, abstracts, books, conference archives, letters to the editor, duplicates and opinion articles. Data will be analyzed by content analysis and inferential statistics. This protocol is registered on the Open Science Framework (OSF) under DOI 10.17605/OSF.IO/PUJDB. Results: The study aims to understand aspects related to the expectations, desires, and cultural values of patients from different countries, as well as the strengths and critical nodes of the use of digital health on the quality of care in PHC.

Qualidade dos dados antropométricos de crianças menores de cinco anos em sistemas de informação no estado de São Paulo, Brasil / The quality of the anthropometric data on children under five years of age in information systems in the State of São Paulo, Brazil

Resumo O objetivo foi analisar a qualidade dos dados antropométricos de crianças menores de cinco anos em dois sistemas de informação no estado de São Paulo. A amostra compreendeu 2.117.108 crianças do Sistema de Vigilância Alimentar e Nutricional (Sisvan) e 748.551 do Projeto Estadual do Leite (Vivaleite). Inicialmente, avaliamos a frequência de valores faltantes e fora do espectro do equipamento, e calculamos o índice de preferência de dígito para peso. Após calcular os índices de altura para idade (A-I), peso para idade (P-I) e índice de massa corporal para idade (IMC-I), identificamos os valores biologicamente implausíveis (VBI) e calculamos o desvio-padrão (DP). Para cada município, calculamos a média e o DP de A-I, P-I e IMC-I; e plotamos os valores de DP em função da média. A preferência de dígito no peso foi maior em crianças de 24 a 59 meses no Sisvan. A frequência de VBI para A-I (SISVAN 2,56%; Vivaleite 0,98%) foi maior do que para P-I (Sisvan 2,10%; Vivaleite 0,18%). Para o índice A-I as variações entre os municípios foram mais acentuadas no Vivaleite do que no Sisvan. A variável altura apresentou baixa confiabilidade nos dois sistemas. A variável peso apresentou qualidade satisfatória no Vivaleite e insatisfatória no Sisvan.

Abstract This paper involves the analysis of the quality of anthropometric data on children under five years of age in two information systems in the State of São Paulo. The sample included 2,117,108 children from the Food and Nutrition Surveillance System (SISVAN), and 748,551 from the State Milk Project (VIVALEITE). Initially, we evaluated the frequency of missing values and others outside the equipment spectrum and calculated the digit-to-weight preference index. After calculating height-for-age (HAZ), weight-for-age (WAZ), and body mass index-for-age (BAZ), we flagged the biologically implausible values (BIV) and calculated the standard deviation (SD). For each municipality, we calculated the mean and the SD of HAZ, WAZ, and BAZ; and plotted the SD values as a function of the mean. The digit-to-weight preference index was greater among children aged between 24 and 59 months in SISVAN. The frequency of BIV for HAZ (SISVAN 2.56%; VIVALEITE 0.98%) was higher than for WAZ (SISVAN 2.10%; VIVALEITE 0.18%). For HAZ, variations among municipalities were more pronounced in VIVALEITE than in SISVAN. The height variable presents low reliability in both systems. The weight variable reveals satisfactory quality in VIVALEITE and unsatisfactory quality in SISVAN.

Qualidade e acesso à água para consumo humano: um olhar sobre o estado do Amazonas, Brasil / Quality and access to water for human consumption: a look at the state of Amazonas, Brazil

Resumo Analisaram-se indicadores de vigilância da qualidade da água para consumo humano no Amazonas, de 2016 a 2020, utilizando 185.528 amostras provenientes de 11 microrregiões. Das amostras analisadas, 93,20% são da área urbana, 66,65% provinham do sistema público (SAA), 31,02% da Solução Alternativa Coletiva (SAC) e 2,33% da Solução de Alternativa Individual (SAI). Observou-se aumento do número de registros pelo SAA, com tendência de queda e oscilações de registros para a SAC e a SAI. Os indicadores de qualidade dos parâmetros químicos e físicos da área urbana foram superiores aos das áreas rurais e de comunidades tradicionais. A maior parte das amostras apresentou valores de pH abaixo do recomendado. Na quantificação dos parâmetros microbiológicos, identificou-se maior presença de coliformes totais e E.coli na área rural e em comunidades tradicionais. Em conclusão, verificaram-se inadequações nos parâmetros químicos, físicos e microbiológicos, assim como problemas relativos ao abastecimento, armazenamento e à vigilância da água distribuída para consumo humano. Tais achados indicam a necessidade de construir uma agenda, pela gestão pública, para o enfrentamento da insegurança hídrica e seus prováveis efeitos sobre a insegurança alimentar existente na região.

Abstract Surveillance indicators of the quality of water for human consumption in the Amazon were analysed from 2016 to 2020 using 185,528 samples from 11 microregions. Of the samples analysed, 93.20% were from urban areas, 66.65% were from the public water supply system (WSS), 31.02% were from the Collective Alternative Solution-CAS, and 2.33% from the Individual Alternative Solution-IAS. There was an increase in the number of records by the WSS, with a downwards trend and fluctuations in records for the CAS and the IAS. The quality indicators of chemical and physical parameters for urban areas were higher than those for rural areas and traditional communities. Most of the samples presented pH values below the recommended level. In the quantification of microbiological parameters, a higher presence of total coliforms and E. coli was identified in samples from rural areas and in traditional communities. In conclusion, there were inadequacies in the chemical, physical and microbiological parameters as well as problems related to the supply, storage and surveillance of water distributed for human consumption. These findings indicate the need to build an agenda for public management to address water insecurity and its likely effects on food insecurity in the region.

Geographic Disparities in Availability of General and Specialized Pediatricians in the United States and Prevalence of Childhood Neurodevelopmental Disorders.

General pediatricians and those specialized in developmental-behavioral and neurodevelopmental disabilities support children with neurodevelopmental disorders, such as autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD). We identified substantial geographic disparities in pediatrician availability (eg, urban > rural areas), as well as regions with low pediatrician access but high ASD/ADHD prevalence estimates (eg, the US Southeast).

A Survey on Error Exponents in Distributed Hypothesis Testing: Connections with Information Theory, Interpretations, and Applications.

A central challenge in hypothesis testing (HT) lies in determining the optimal balance between Type I (false positive) and Type II (non-detection or false negative) error probabilities. Analyzing these errors' exponential rate of convergence, known as error exponents, provides crucial insights into system performance. Error exponents offer a lens through which we can understand how operational restrictions, such as resource constraints and impairments in communications, affect the accuracy of distributed inference in networked systems. This survey presents a comprehensive review of key results in HT, from the foundational Stein's Lemma to recent advancements in distributed HT, all unified through the framework of error exponents. We explore asymptotic and non-asymptotic results, highlighting their implications for designing robust and efficient networked systems, such as event detection through lossy wireless sensor monitoring networks, collective perception-based object detection in vehicular environments, and clock synchronization in distributed environments, among others. We show that understanding the role of error exponents provides a valuable tool for optimizing decision-making and improving the reliability of networked systems.

Development and Evaluation of a Software Designed by a Nursing and Technology Team to Assess the Health Status of Adults over 65 Years of Age.

Objective: This work sought to develop the Actuasalud platform as a useful tool for nursing that permits assessing health, in term of frailty, in population over 65 years of age. Methods: For the design and development of Actuasalud, two working groups were formed: one from nursing with different profiles, to identify the scientific content and a computer science group responsible for the software programming and development. Both teams adapted the scientific content to the technology so that the tool would allow for population screening with detection of health problems and frailty states. Results: The software was developed in three large blocks that include all the dimensions of frailty: a: sociodemographic variables, b: comorbidities, and c: assessment tools of autonomy-related needs that evaluate the dimensions of frailty. At the end of the evaluation, a detailed report is displayed through bar diagram with the diagnosis of each of the dimensions assessed. The assessment in the participating elderly showed that 44.7% (n = 38) of the population was considered not frail, and 55.3%; (n = 47) as frail. Regarding associated pathologies, high blood pressure (67.1%; n = 57), osteoarthritis and/or arthritis (55.3%; n = 47), diabetes (48.2%; n = 41) and falls during the last year (35.3%; n = 30) were highlighted. Conclusion: Actuasalud is an application that allows nursing professionals to evaluate frailty and issue a quick diagnosis with ordered sequence, which helps to provide individualized care to elderly individuals according to the problems detected during the evaluation.

KLD: a program to elucidate the localization of the Fermi and Coulomb holes in molecular systems.

CONTEXT: The electron localization is a concept that allows scientists to better understand the physical and chemical properties of electronic systems. It is associated with the propensity of electron pairs with opposite spins to accumulate as well as with their response to external perturbations. This paper contains a detailed description of the design and implementation of the program KLD, which was primarily developed in our research group to elucidate electron localization in molecular systems by evaluating the information content of electron-pair density functions. KLD employs two information-based functions as a real space measure of the Fermi and Coulomb holes for same-spin electrons and shows a better resolution as compared to other methods (i.e., ELF). Information about the acceleration of the code is also included in the present work, being noticeable the reduction of wall-time calculation and the error calculation between versions. METHODS: KLD was designed to be easy to use, extend, and maintain; thus, many principles of modern software development, extensive testing, and package management were adopted. The latest version of the KLD program was created utilizing the Compute Unified Device Architecture (CUDA) version, which allows it to use the computational capacity of NVIDIA Graphics Processing Units (GPUs) for processing purposes. The electron-pair conditional density was calculated from the canonical molecular orbitals obtained at the HF/6-31G(2df,p) level, or alternatively the natural orbitals in the case of explicit correlated wavefunctions computed at the MP2/6-31G(2df,p)//HF/6-31G(2df,p) level.

Rényi entropy-complexity causality space: a novel neurocomputational tool for detecting scale-free features in EEG/iEEG data.

Scale-free brain activity, linked with learning, the integration of different time scales, and the formation of mental models, is correlated with a metastable cognitive basis. The spectral slope, a key aspect of scale-free dynamics, was proposed as a potential indicator to distinguish between different sleep stages. Studies suggest that brain networks maintain a consistent scale-free structure across wakefulness, anesthesia, and recovery. Although differences in anesthetic sensitivity between the sexes are recognized, these variations are not evident in clinical electroencephalographic recordings of the cortex. Recently, changes in the slope of the power law exponent of neural activity were found to correlate with changes in Rényi entropy, an extended concept of Shannon's information entropy. These findings establish quantifiers as a promising tool for the study of scale-free dynamics in the brain. Our study presents a novel visual representation called the Rényi entropy-complexity causality space, which encapsulates complexity, permutation entropy, and the Rényi parameter q. The main goal of this study is to define this space for classical dynamical systems within theoretical bounds. In addition, the study aims to investigate how well different time series mimicking scale-free activity can be discriminated. Finally, this tool is used to detect dynamic features in intracranial electroencephalography (iEEG) signals. To achieve these goals, the study implementse the Bandt and Pompe method for ordinal patterns. In this process, each signal is associated with a probability distribution, and the causal measures of Rényi entropy and complexity are computed based on the parameter q. This method is a valuable tool for analyzing simulated time series. It effectively distinguishes elements of correlated noise and provides a straightforward means of examining differences in behaviors, characteristics, and classifications. For the iEEG experimental data, the REM state showed a greater number of significant sex-based differences, while the supramarginal gyrus region showed the most variation across different modes and analyzes. Exploring scale-free brain activity with this framework could provide valuable insights into cognition and neurological disorders. The results may have implications for understanding differences in brain function between the sexes and their possible relevance to neurological disorders.

Experimental and modeling of potassium diclofenac uptake on activated carbon.

The presence of pharmaceuticals in wastewater resulting from human activities has driven researchers to explore effective treatment methods such as adsorption using activated carbon (AC). While AC shows promise as an adsorbent, further studies are essential to comprehend its entire interaction with pharmaceuticals. This article investigates the adsorption of potassium diclofenac (PD) onto AC using experimental and modeling approaches. Batch adsorption studies coupled with Fourier transform infrared spectroscopy (FTIR) were employed to clarify the adsorption mechanism of PD on AC. Various kinetic and isotherm adsorption models were applied to analyze the adsorbent-adsorbate interaction. The kinetics were best described by Avrami's fractional order (AFO) nonlinear model. Also, the intraparticle diffusion (IP) model reveals a three-stage adsorption process. The experimental equilibrium data fitted well with the three-parameter nonlinear Liu model, indicating a maximum adsorption capacity (Qmax) of 88.45 mg g-1 and suggesting monolayer or multilayer adsorption. Thermodynamic analysis showed favorable adsorption (ΔG° < 0), with an enthalpy change (ΔH° = -30.85 kJ mol-1) characteristic of physisorption involving hydrogen bonds and π-π interactions. The adsorption mechanism was attributed to forming a double layer (adsorbate-adsorbent and adsorbate-adsorbate).

Self-Controlled Feedback in Motor Learning: The Effects Depend on the Frequency of Request.

The benefits of allowing learners to control when to receive knowledge of results (KR) compared to a yoked group has been recently challenged and postulated to be mild at best. A potential explanation for such dissident findings is that individuals differentially utilize the autonomy provided by the self-controlled condition, which, in its turn, affects the outcomes. Therefore, the present study investigated the effects of self-controlled KR on motor learning focusing on the frequency of KR requests when performing an anticipatory timing task. Self-controlled groups were created based on participants' KR frequency of request (High, Medium, and Low referring to fifth, third, and first quintile) and, then, Yoked groups were created self-control condition pairing the KR request of the Self-controlled groups. We also measured self-efficacy and processing time as means to verify potential correlates. The results supported the expected interaction. While no difference between self-controlled and yoked groups were found for low frequencies of KR, a moderate amount of KR request was related to better results for the self-controlled group. Nonetheless, the opposite trend was observed for high frequencies of KR; the yoked group was superior to the self-controlled group. The results of this study allow us to conclude that the choices made, and not just the possibility of choosing, seem to define the benefits of KR self-control in motor learning.

Pregnant women's perceptions on Information Sources on Zika Virus: a qualitative study.

The Zika virus (ZIKV) epidemic had a sanitary, psychosocial, and economic impact on individuals of reproductive age. The primary concern revolved around infection during pregnancy due to possible vertical transmission and its association with adverse fetal and infant outcomes, known as Congenital Zika Syndrome (CZS). This qualitative study employs phenomenology and grounded theory. This study includes interviews with 98 women, some pregnant during the ZIKV epidemic in Brazil, Colombia, and Puerto Rico, who had children with CZS or without diagnosed neurological impairment. Additionally, the study included a group of women who were pregnant during the COVID-19 pandemic in these same countries. In both groups, interviewees had varying levels of knowledge about ZIKV. The study found that messages conveyed through the media tended to be alarmist, in contrast to the information provided by healthcare professionals, which was considered more trustworthy. Pregnant women during the ZIKV epidemic reported receiving their ZIKV and CSZ infection diagnoses late, either during or after childbirth. The study underscores the needs of pregnant women in high-risk scenarios, the importance of health education processes, and the necessity to reinforce communication and continuing education.

A epidemia do vírus Zika (ZIKV) teve impacto sanitário, psicossocial e econômico sobre pessoas em idade reprodutiva. A principal preocupação foi a infecção durante a gravidez devido a possível transmissão vertical e sua associação com resultados fetais e infantis adversos, conhecida como síndrome congênita associada à infecção pelo Vírus Zika (SCZ). Este estudo qualitativo utiliza a fenomenologia e a teoria fundamentada. O estudo inclui entrevistas com 98 mulheres, parte grávida durante a epidemia de ZIKV no Brasil, Colômbia e Porto Rico e que tiveram filhos com SCZ ou sem comprometimento neurológico diagnosticado. Além disso, o estudo inclui um grupo de mulheres grávidas durante a pandemia de COVID-19 nos mesmos países. Em ambos os grupos, as entrevistadas tinham diferentes níveis de conhecimento sobre ZIKV. O estudo constatou que as mensagens veiculadas por meio da mídia eram alarmistas; em contraste com as informações fornecidas por profissionais de saúde, consideradas mais confiáveis. Mulheres gestantes durante a epidemia do ZIKV relataram ter recebido seu diagnóstico de infecção por ZIKV e SCZ tardiamente ou após o parto. O estudo destaca as necessidades das mulheres grávidas em cenários de alto risco, a importância de processos de educação em saúde e a necessidade de reforçar a comunicação e a educação continuada.

Using Multimodal Data to Improve Precision of Inpatient Event Timelines.

Textual data often describe events in time but frequently contain little information about their specific timing, whereas complementary structured data streams may have precise timestamps but may omit important contextual information. We investigate the problem in healthcare, where we produce clinician annotations of discharge summaries, with access to either unimodal (text) or multimodal (text and tabular) data, (i) to determine event interval timings and (ii) to train multimodal language models to locate those events in time. We find our annotation procedures, dashboard tools, and annotations result in high-quality timestamps. Specifically, the multimodal approach produces more precise timestamping, with uncertainties of the lower bound, upper bounds, and duration reduced by 42% (95% CI 34-51%), 36% (95% CI 28-44%), and 13% (95% CI 10-17%), respectively. In the classification version of our task, we find that, trained on our annotations, our multimodal BERT model outperforms unimodal BERT model and Llama-2 encoder-decoder models with improvements in F1 scores for upper (10% and 61%, respectively) and lower bounds (8% and 56%, respectively). The code for the annotation tool and the BERT model is available (link).

Computed tomography and magnetic resonance imaging in Brazil: an epidemiological study on the distribution of equipment and frequency of examinations, with comparisons between the public and private sectors.

Objective: To compare information on highly complex radiological procedures-computed tomography (CT) and magnetic resonance imaging (MRI)-between the public and private health care systems, across the five regions of Brazil, in terms of the numbers of radiological devices and examinations performed, between 2015 and 2021. Materials and Methods: This was a descriptive time series analysis of secondary data in the public domain, available from the Information Technology Department of the Brazilian Unified Health Care System, an entity of the Brazilian National Ministry of Health (NMH) that is responsible for collecting and storing health-related information in Brazil. The analysis included the numbers of CT and MRI scanners; the volumes and types of examinations; the type of institution (public or private); the regions of the country; and the years (2015 to 2021). Results: Progressive increases in the numbers of CT and MRI devices, as well as in the volumes of examinations, were observed over the years in all regions of the country. The private sector showed higher rates of equipment acquisition and of growth in the number of examinations. However, the public health care system did not reach the equipment targets set by the NMH, whereas the private health care system surpassed those targets. A greater number of examinations were performed in the private sector than in the public sector. Conclusion: During the period evaluated, the public health care system did not meet the equipment or examination targets recommended by the NMH, in any of the regions of the country, unlike the private health care system, which exceeded both in all of the regions.

Objetivo: Comparar informações sobre procedimentos radiológicos de alta complexidade ­ tomografia computadorizada (TC) e ressonância magnética (RM) ­, considerando o número de aparelhos e o quantitativo de exames nas esferas pública e privada nas cinco regiões brasileiras entre 2015 e 2021. Materiais e Métodos: Trata-se de um estudo descritivo de série temporal que utilizou dados secundários do Departamento de Informática do Sistema Único de Saúde, órgão do Ministério da Saúde (MS) responsável pela coleta e armazenamento das informações relacionadas à saúde no Brasil. Analisamos os números de aparelhos e de exames de TC e RM, considerando os tipos de aparelhos e exames, instituição (pública ou privada), região brasileira e ano (2015 a 2021). Resultados: Houve aumento de aparelhos e exames de TC e RM em todas as regiões ao longo dos anos. A esfera privada apresentou maior aquisição desses aparelhos e crescimento no número de exames. O sistema público não atingiu o número de aparelhos preconizado pelo MS, enquanto o sistema privado superou a recomendação. Observou-se maior número de exames na esfera privada quando comparada à pública. Conclusão: O sistema público não atendeu aos números de aparelhos e exames realizados preconizados pelo MS, diferentemente da esfera privada, em todas as regiões no período estudado.

Clinical, epidemiological characteristics and mortality of pregnant and postpartum women associated with COVID-19 in Brazil: cohort study.

Objective: To analyze the death of Brazilian pregnant and postpartum women due to COVID-19 or unspecific cause. Methods: This is retrospective, descriptive-exploratory, population-based study carried out with the Sistema de Informação de Vigilância Epidemiológica da Gripe (SIVEP-Gripe) database, with pregnant and postpartum women of reproductive age who died from confirmed COVID-19 between 2020 and 2021. The chosen variables were: age, gestational period, type and number of comorbidities, skin color, using the statistical software R Foundation for Statistical Computing Platform, version 4.0.3 and Statistical Package for Social Science, version 29.0 for analysis. Results: A total of 19,333 cases of pregnant and postpartum women aged between 10 and 55 years diagnosed with SARS were identified, whether due to confirmed COVID-19 or unspecific causes. Of these, 1,279 died, these cases were classified into two groups according to the cause of death: deaths from COVID-19 (n= 1,026) and deaths from SARS of unspecific cause (n= 253). Conclusion: The risk of death increased among black and brown women, in the postpartum period and with the presence of comorbidities, mainly diabetes, cardiovascular diseases and obesity. The data presented here draw attention to the number of deaths from SARS, especially among sociodemographic profiles, precarious access to health, such as the black population. In addition, limitations in adequate access to health care are reinforced by even lower rates of ICU admissions among women who died from SARS of an unspecified cause.

Hidden leprosy in a low-endemic area in southern Brazil: changes in endemicity following an active search.

BACKGROUND: Leprosy, a neglected tropical disease, is reported in over 120 countries, with upwards of 200,000 new cases annually. This Cross-Sectional Cohort Study aimed to delineate the epidemiological profile of leprosy in a low-endemic area in southern Brazil, both before and after implementing an active search strategy. METHODS: The study examined two surveillance periods in Caçador, Santa Catarina, Brazil. The active search strategy was carried out through the application of the LSQ by the community health workers as a screening and detection tool for new cases of leprosy and this was compared with passive case detection. The first spanned from 2014 to 2020, and the second from January 2021 to August 2023. FINDINGS: 48 leprosy cases were reported throughout the study, 83.3 % of which were diagnosed as multibacillary. The first period had an average detection rate of 0.38 cases per 10,000 inhabitants, increasing to 1.19 cases per 10,000 inhabitants in the second period. Notably, there was a substantial shift in the degree of physical disability (GD), with more Grade 0 and Grade 1 disabilities observed post-active search. MAIN CONCLUSIONS: The study underscores the efficacy of active search strategies in early diagnosis, highlighting a 300 % increase in the annual average of diagnosed cases. This large number of detected cases demonstrates the high sensitivity of the LSQ. This approach significantly aids in uncovering hidden cases of leprosy, enhancing disease management and control in low-endemic areas indicating that the Ministry of Health should intensify leprosy control activities in these regions.