Chemical characterisation, thermal analysis, and antibacterial activity of honeys from Caatinga stingless bees of Melipona spp.

In the present study, chemical characterisation, thermal analysis and antibacterial activity of honeys from Melipona spp. with occurrence in Caatinga biome of Brazil. The honeys presented pH from 4.07 to 4.14, density of 1.41 g/cm3 and °Brix value of 79.90. The thermogravimetry (TG) analysis presented six-seven events and differential thermal analysis (DTA) presented three-four endothermic peaks. HPLC fingerprint revealed a predominant presence of gallic acid and vanillin. Antioxidant activity evaluated using in vitro 2,2-diphenyl-1-picrylhydrazyl radical (DPPH) radical scavenging with IC50 values in the range of 14.5404 to 15.2454 mg/mL. The honeys also showed antimicrobial activities against Staphylococcus aureus and Pseudomonas aeruginosa using a modified agar diffusion and microdilution method. The results of the present study demonstrate that the honey from stingless bees by Caatinga biome indicate polyphenol compounds, antioxidant activity and in vitro antimicrobial potential. The analytical methos permitted of fingerprint of samples.

Digital dual test syphilis/HIV detection based on Fourier Descriptors of Cyclic Voltammetry curves.

BACKGROUND: Effective and timely detection is vital for mitigating the severe impacts of Sexually Transmitted Infections (STI), including syphilis and HIV. Cyclic Voltammetry (CV) sensors have shown promise as diagnostic tools for these STI, offering a pathway towards cost-effective solutions in primary health care settings. OBJECTIVE: This study aims to pioneer the use of Fourier Descriptors (FDs) in analyzing CV curves as 2D closed contours, targeting the simultaneous detection of syphilis and HIV. METHODS: Raw CV signals are filtered, resampled, and transformed into 2D closed contours for FD extraction. Essential shape characteristics are captured through selected coefficients. A complementary geometrical analysis further extracts features like curve areas and principal axes lengths from CV curves. A Mahalanobis Distance Classifier is employed for differentiation between patient and control groups. RESULTS: The evaluation of the proposed method revealed promising results with classification performance metrics such as Accuracy and F1-Score consistently achieving values rounded to 0.95 for syphilis and 0.90 for HIV. These results underscore the potential efficacy of the proposed approach in differentiating between patient and control samples for STI detection. CONCLUSION: By integrating principles from biosensors, signal processing, image processing, machine learning, and medical diagnostics, this study presents a comprehensive approach to enhance the detection of both syphilis and HIV. This setts the stage for advanced and accessible STI diagnostic solutions.

Pharmacological, toxicological and phytochemical analysis of Spondias dulcis parkinson.

Spondias dulcis Parkinson have been used in traditional medicine in Asia, Oceania, and South America, for different diseases conditions and as a functional food. The scientific literature described as different potential pharmacology such as antioxidant, anti-inflammatory, antimicrobial, thrombolytic and enzymatic inhibitor. This study aimed to: (1) establish the pharmacological activity in intestinal motility in vivo and antioxidant activity in vitro; (2) perform the acute toxicology test in mouse; (3) characterize the phytochemical profile based on counter-current chromatography (CCC) and NMR analysis. The results revealed a laxative effect of S. dulcis extract and a high antioxidant activity (IC50 = 5.10 for DPPH assay and 14.14 for hydrogen peroxide scavenging test). No side effects were observed in the oral acute toxicity test for a dose up to 2000 mg/kg. The chemical profile was identified by CCC and NMR, and the comparison of the data obtained with previous literature revealed the presence of the flavonoid rutin (Quercetin-3-O-rutinoside) in the extract.

Artificial intelligence applied to analyzes during the pandemic: COVID-19 beds occupancy in the state of Rio Grande do Norte, Brazil.

The COVID-19 pandemic is already considered one of the biggest global health crises. In Rio Grande do Norte, a Brazilian state, the RegulaRN platform was the health information system used to regulate beds for patients with COVID-19. This article explored machine learning and deep learning techniques with RegulaRN data in order to identify the best models and parameters to predict the outcome of a hospitalized patient. A total of 25,366 bed regulations for COVID-19 patients were analyzed. The data analyzed comes from the RegulaRN Platform database from April 2020 to August 2022. From these data, the nine most pertinent characteristics were selected from the twenty available, and blank or inconclusive data were excluded. This was followed by the following steps: data pre-processing, database balancing, training, and test. The results showed better performance in terms of accuracy (84.01%), precision (79.57%), and F1-score (81.00%) for the Multilayer Perceptron model with Stochastic Gradient Descent optimizer. The best results for recall (84.67%), specificity (84.67%), and ROC-AUC (91.6%) were achieved by Root Mean Squared Propagation. This study compared different computational methods of machine and deep learning whose objective was to classify bed regulation data for patients with COVID-19 from the RegulaRN Platform. The results have made it possible to identify the best model to help health professionals during the process of regulating beds for patients with COVID-19. The scientific findings of this article demonstrate that the computational methods used applied through a digital health solution, can assist in the decision-making of medical regulators and government institutions in situations of public health crisis.

Evaluation of massive education in prison health: a perspective of health care for the person deprived of freedom in Brazil.

Education, with an emphasis on prison health, has acted as a policy inducing changes in work processes, which the Brazilian National Health System (SUS) has used, and which is present in permanent health education, which promotes health care for people deprived of liberty. This article aims to present an analysis of the impacts of the strategy of massive education on prison health in Brazil from the perspective of health professionals and other actors operating in the Brazilian prison system. The data used in the study come from a questionnaire consisting of 37 questions applied nationwide between March and June 2022. Responses were collected from students who completed the course "Health Care for People Deprived of Freedom" of the learning pathway "Prison System", available in the Virtual Learning Environment of the Brazilian Health System (AVASUS). This course was offered nationally, whose adhesion (enrollment) occurred spontaneously, i.e., the course was not a mandatory. The data collected allowed us to analyze the impacts of massive education on prison health. The study also shows that the search for the course is made by several areas of knowledge, with a higher incidence in the health area, but also in other areas, such as humanities, which also work directly with the guarantee of the rights of people deprived of liberty, which are professionals in the areas of social work, psychology, and education. The analysis based on the data suggests that the massive education mediated by technology through the courses of the learning pathway, besides disseminating knowledge-following the action plan of the 2030 Agenda of the United Nations Educational, Scientific and Cultural Organization (UNESCO)-, are an effective tool to promote resilience in response to prison health and care demands of people deprived of liberty.

Computational methods applied to syphilis: where are we, and where are we going?

Syphilis is an infectious disease that can be diagnosed and treated cheaply. Despite being a curable condition, the syphilis rate is increasing worldwide. In this sense, computational methods can analyze data and assist managers in formulating new public policies for preventing and controlling sexually transmitted infections (STIs). Computational techniques can integrate knowledge from experiences and, through an inference mechanism, apply conditions to a database that seeks to explain data behavior. This systematic review analyzed studies that use computational methods to establish or improve syphilis-related aspects. Our review shows the usefulness of computational tools to promote the overall understanding of syphilis, a global problem, to guide public policy and practice, to target better public health interventions such as surveillance and prevention, health service delivery, and the optimal use of diagnostic tools. The review was conducted according to PRISMA 2020 Statement and used several quality criteria to include studies. The publications chosen to compose this review were gathered from Science Direct, Web of Science, Springer, Scopus, ACM Digital Library, and PubMed databases. Then, studies published between 2015 and 2022 were selected. The review identified 1,991 studies. After applying inclusion, exclusion, and study quality assessment criteria, 26 primary studies were included in the final analysis. The results show different computational approaches, including countless Machine Learning algorithmic models, and three sub-areas of application in the context of syphilis: surveillance (61.54%), diagnosis (34.62%), and health policy evaluation (3.85%). These computational approaches are promising and capable of being tools to support syphilis control and surveillance actions.

Digital health solution for monitoring and surveillance of Amyotrophic Lateral Sclerosis in Brazil.

Amyotrophic Lateral Sclerosis (ALS) is a complex and rare neurodegenerative disease given its heterogeneity. Despite being known for many years, few countries have accurate information about the characteristics of people diagnosed with ALS, such as data regarding diagnosis and clinical features of the disease. In Brazil, the lack of information about ALS limits data for the research progress and public policy development that benefits people affected by this health condition. In this context, this article aims to show a digital health solution development and application for research, intervention, and strengthening of the response to ALS in the Brazilian Health System. The proposed solution is composed of two platforms: the Brazilian National ALS Registry, responsible for the data collection in a structured way from ALS patients all over Brazil; and the Brazilian National ALS Observatory, responsible for processing the data collected in the National Registry and for providing a monitoring room with indicators on people diagnosed with ALS in Brazil. The development of this solution was supported by the Brazilian Ministry of Health (MoH) and was carried out by a multidisciplinary team with expertise in ALS. This solution represents a tool with great potential for strengthening public policies and stands out for being the only public database on the disease, besides containing innovations that allow data collection by health professionals and/or patients. By using both platforms, it is believed that it will be possible to understand the demographic and epidemiological data of ALS in Brazil, since the data will be able to be analyzed by care teams and also by public health managers, both in the individual and collective monitoring of people living with ALS in Brazil.

Digital Alternative Communication for Individuals with Amyotrophic Lateral Sclerosis: What We Have.

Amyotrophic Lateral Sclerosis is a disease that compromises the motor system and the functional abilities of the person in an irreversible way, causing the progressive loss of the ability to communicate. Tools based on Augmentative and Alternative Communication are essential for promoting autonomy and improving communication, life quality, and survival. This Systematic Literature Review aimed to provide evidence on eye-image-based Human-Computer Interaction approaches for the Augmentative and Alternative Communication of people with Amyotrophic Lateral Sclerosis. The Systematic Literature Review was conducted and guided following a protocol consisting of search questions, inclusion and exclusion criteria, and quality assessment, to select primary studies published between 2010 and 2021 in six repositories: Science Direct, Web of Science, Springer, IEEE Xplore, ACM Digital Library, and PubMed. After the screening, 25 primary studies were evaluated. These studies showcased four low-cost, non-invasive Human-Computer Interaction strategies employed for Augmentative and Alternative Communication in people with Amyotrophic Lateral Sclerosis. The strategies included Eye-Gaze, which featured in 36% of the studies; Eye-Blink and Eye-Tracking, each accounting for 28% of the approaches; and the Hybrid strategy, employed in 8% of the studies. For these approaches, several computational techniques were identified. For a better understanding, a workflow containing the development phases and the respective methods used by each strategy was generated. The results indicate the possibility and feasibility of developing Human-Computer Interaction resources based on eye images for Augmentative and Alternative Communication in a control group. The absence of experimental testing in people with Amyotrophic Lateral Sclerosis reiterates the challenges related to the scalability, efficiency, and usability of these technologies for people with the disease. Although challenges still exist, the findings represent important advances in the fields of health sciences and technology, promoting a promising future with possibilities for better life quality.

Robotic Myotomy and Partial Fundoplication for Achalasia.

Laparoscopic Heller myotomy is currently considered the standard definitive treatment of achalasia. With the advancements in technology, robotic Heller myotomy has emerged as an alternative approach to traditional laparoscopy due to three-dimensional (3D) visualization, fine motor control, and improved ergonomics provided by the robot. Although there is a lack of randomized controlled trials, robotic-assisted Heller myotomy seems to be associated with lower rates of intraoperative perforations compared to the laparoscopic approach. A robotic approach may also improve surgical outcomes by providing a more complete myotomy. Here, we describe the detailed steps of robotic myotomy and partial fundoplication for achalasia.

Osteoporosis screening using machine learning and electromagnetic waves.

Osteoporosis is a disease characterized by impairment of bone microarchitecture that causes high socioeconomic impacts in the world because of fractures and hospitalizations. Although dual-energy X-ray absorptiometry (DXA) is the gold standard for diagnosing the disease, access to DXA in developing countries is still limited due to its high cost, being present only in specialized hospitals. In this paper, we analyze the performance of Osseus, a low-cost portable device based on electromagnetic waves that measures the attenuation of the signal that crosses the medial phalanx of a patient's middle finger and was developed for osteoporosis screening. The analysis is carried out by predicting changes in bone mineral density using Osseus measurements and additional common risk factors used as input features to a set of supervised classification models, while the results from DXA are taken as target (real) values during the training of the machine learning algorithms. The dataset consisted of 505 patients who underwent osteoporosis screening with both devices (DXA and Osseus), of whom 21.8% were healthy and 78.2% had low bone mineral density or osteoporosis. A cross-validation with k-fold = 5 was considered in model training, while 20% of the whole dataset was used for testing. The obtained performance of the best model (Random Forest) presented a sensitivity of 0.853, a specificity of 0.879, and an F1 of 0.859. Since the Random Forest (RF) algorithm allows some interpretability of its results (through the impurity check), we were able to identify the most important variables in the classification of osteoporosis. The results showed that the most important variables were age, body mass index, and the signal attenuation provided by Osseus. The RF model, when used together with Osseus measurements, is effective in screening patients and facilitates the early diagnosis of osteoporosis. The main advantages of such early screening are the reduction of costs associated with exams, surgeries, treatments, and hospitalizations, as well as improved quality of life for patients.

Veno-venous extracorporeal membrane oxygenation in patients with SARS-CoV-2 pneumonia in Brazil: a case series.

OBJECTIVE: The world has been suffering from the COVID-19 pandemic. Some COVID-19 patients develop severe viral pneumonia, requiring mechanical ventilation and measures to treat refractory hypoxemia, such as a protective ventilation strategy, prone positioning, and the use of veno-venous extracorporeal membrane oxygenation (VV-ECMO). We describe a case series of 30 COVID-19 patients who needed VV-ECMO at the Hospital Alemão Oswaldo Cruz, located in the city of São Paulo, Brazil. METHODS: We included all patients who required VV-ECMO due to COVID-19 pneumonia between March of 2020 and June of 2021. RESULTS: Prior to VV-ECMO, patients presented with the following median scores: SOFA score, 11; APPS score, 7; Respiratory ECMO Survival Prediction score, 2; and Murray score, 3.3. The 60-day-in-hospital mortality was 33.3% (n = 10). CONCLUSIONS: Although our patients had a highly severe profile, our results were similar to those of other cohort studies in the literature. This demonstrates that VV-ECMO can be a good tool even in a pandemic situation when it is managed in an experienced center.

Trends and Application of Chemometric Pattern Recognition Techniques in Medicinal Plants Analysis.

Medicinal plants have been used and studied for ages, from very old registers to modern ethnopharmacology, which encompasses analytical chemistry, foods, and pharmacy. Based on international norms and governmental organizations of health, phytomedicine-for example, herbal drugs-needs to guarantee the quality control of products and identify contaminants, biomarkers, and chemical profiles, among other issues. In this sense, is necessary to develop advanced analytical methods that show interesting possibilities and obtain a great amount of data. In order to treat the data, a set of mathematical and statistical procedures named chemometrics is necessary. In terms of herbal drugs, chemometric tools may be used to identify the following in plants: parts, development stages, processing, geographic origin, authentication, and chemical markers. This review describes applications of chemometric pattern recognition tools to analyze herbal drugs in different conditions associated with analytical methods in the last six years (2015-2020).

Veno-venous extracorporeal membrane oxygenation in patients with SARS-CoV-2 pneumonia in Brazil: a case series / Oxigenação por membrana extracorpórea venovenosa em pacientes com pneumonia por SARS-CoV-2 no Brasil: série de casos

ABSTRACT Objective: The world has been suffering from the COVID-19 pandemic. Some COVID-19 patients develop severe viral pneumonia, requiring mechanical ventilation and measures to treat refractory hypoxemia, such as a protective ventilation strategy, prone positioning, and the use of veno-venous extracorporeal membrane oxygenation (VV-ECMO). We describe a case series of 30 COVID-19 patients who needed VV-ECMO at the Hospital Alemão Oswaldo Cruz, located in the city of São Paulo, Brazil. Methods: We included all patients who required VV-ECMO due to COVID-19 pneumonia between March of 2020 and June of 2021. Results: Prior to VV-ECMO, patients presented with the following median scores: SOFA score, 11; APPS score, 7; Respiratory ECMO Survival Prediction score, 2; and Murray score, 3.3. The 60-day-in-hospital mortality was 33.3% (n = 10). Conclusions: Although our patients had a highly severe profile, our results were similar to those of other cohort studies in the literature. This demonstrates that VV-ECMO can be a good tool even in a pandemic situation when it is managed in an experienced center.

RESUMO Objetivo: O mundo vem sofrendo com a pandemia de COVID-19. Alguns pacientes com COVID-19 desenvolvem pneumonia viral grave, necessitando ventilação mecânica e medidas para tratar a hipoxemia refratária, como estratégias de ventilação protetora, posição prona e uso de oxigenação por membrana extracorpórea venovenosa (ECMO-VV). Descrevemos uma série de casos de 30 pacientes com COVID-19 que necessitaram de ECMO-VV no Hospital Alemão Oswaldo Cruz, localizado na cidade de São Paulo, Brasil. Métodos: Foram incluídos todos os pacientes que necessitaram de ECMO-VV devido à pneumonia por COVID-19 entre março de 2020 e junho de 2021. Resultados: Antes da ECMO-VV, os pacientes apresentavam as seguintes medianas: escore SOFA de 11; escore APPS de 7; escore Respiratory ECMO Survival Prediction de 2; e escore de Murray de 3,3. A mortalidade hospitalar em 60 dias foi de 33,3% (n = 10). Conclusões: Apesar de nossos pacientes apresentarem um perfil de alta gravidade, nossos resultados foram semelhantes aos de outros estudos de coorte na literatura. Isso demonstra que a ECMO-VV pode ser uma boa ferramenta mesmo em uma situação de pandemia quando administrada em um centro experiente.

Development of a Cyclic Voltammetry-Based Method for the Detection of Antigens and Antibodies as a Novel Strategy for Syphilis Diagnosis.

The improvement of laboratory diagnosis is a critical step for the reduction of syphilis cases around the world. In this paper, we present the development of an impedance-based method for detecting T. pallidum antigens and antibodies as an auxiliary tool for syphilis laboratory diagnosis. We evaluate the voltammetric signal obtained after incubation in carbon or gold nanoparticle-modified carbon electrodes in the presence or absence of Poly-L-Lysine. Our results indicate that the signal obtained from the electrodes was sufficient to distinguish between infected and non-infected samples immediately (T0') or 15 min (T15') after incubation, indicating its potential use as a point-of-care method as a screening strategy.

Effectiveness of COVID-19 Vaccination on Reduction of Hospitalizations and Deaths in Elderly Patients in Rio Grande do Norte, Brazil.

Since the COVID-19 pandemic emerged, vaccination has been the core strategy to mitigate the spread of SARS-CoV-2 in humans. This paper analyzes the impact of COVID-19 vaccination on hospitalizations and deaths in the state of Rio Grande do Norte, Brazil. We analyzed data from 23,516 hospitalized COVID-19 patients diagnosed between April 2020 and August 2021. We excluded the data from patients hospitalized through direct occupancy, unknown outcomes, and unconfirmed COVID-19 cases, resulting in data from 12,635 patients cross-referenced with the immunization status during hospitalization. Our results indicated that administering at least one dose of the immunizers was sufficient to significantly reduce the occurrence of moderate and severe COVID-19 cases among patients under 59 years. Considering the partially or fully immunized patients, the mean age is similar between the analyzed groups, despite the occurrence of comorbidities and higher than that observed among not immunized patients. Thus, immunized patients present lower Unified Score for Prioritization (USP) levels when diagnosed with COVID-19. Our data suggest that COVID-19 vaccination significantly reduced the hospitalization and death of elderly patients (60+ years) after administration of at least one dose. Comorbidities do not change the mean age of moderate/severe COVID-19 cases and the days required for the hospitalization of these patients.

Electronic health records in Brazil: Prospects and technological challenges.

Electronic Health Records (EHR) are critical tools for advancing digital health worldwide. In Brazil, EHR development must follow specific standards, laws, and guidelines that contribute to implementing beneficial resources for population health monitoring. This paper presents an audit of the main approaches used for EHR development in Brazil, thus highlighting prospects, challenges, and existing gaps in the field. We applied a systematic review protocol to search for articles published from 2011 to 2021 in seven databases (Science Direct, Web of Science, PubMed, Springer, IEEE Xplore, ACM Digital Library, and SciELO). Subsequently, we analyzed 14 articles that met the inclusion and quality criteria and answered our research questions. According to this analysis, 78.58% (11) of the articles state that interoperability between systems is essential for improving patient care. Moreover, many resources are being designed and deployed to achieve this communication between EHRs and other healthcare systems in the Brazilian landscape. Besides interoperability, the articles report other considerable elements: (i) the need for increased security with the deployment of permission resources for viewing patient data, (ii) the absence of accurate data for testing EHRs, and (iii) the relevance of defining a methodology for EHR development. Our review provides an overview of EHR development in Brazil and discusses current gaps, innovative approaches, and technological solutions that could potentially address the related challenges. Lastly, our study also addresses primary elements that could contribute to relevant components of EHR development in the context of Brazil's public health system. Systematic review registration: PROSPERO, identifier CRD42021233219, https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021233219.

The relevancy of massive health education in the Brazilian prison system: The course "health care for people deprived of freedom" and its impacts.

Introduction: Brazil has one of the largest prison populations globally, with over 682,000 imprisoned people. Prison health is a public health emergency as it presents increasingly aggravating disease rates, mainly sexually transmitted infections (STI). And this problem already affects both developed and developing nations. Therefore, when thinking about intervention strategies to improve this scenario in Brazil, the course "Health Care for People Deprived of Freedom" (ASPPL), aimed at prison health, was developed. This course was implemented in the Virtual Learning Environment of the Brazilian Health System (AVASUS). Given this context, this study analyzed the aspects associated with massive training through technological mediation and its impacts on prison health. Methods: This cross-sectional study analyzed data from 8,118 ASPPL course participants. The data analyzed were collected from six sources, namely: (i) AVASUS, (ii) National Registry of Health Care Facilities (CNES), (iii) Brazilian Occupational Classification (CBO), (iv) National Prison Department (DEPEN); (v) Brazilian Institute of Geography and Statistics (IBGE); and the (iv) Brazilian Ministry of Health (MoH), through the Outpatient Information System of the Brazilian National Health System (SIA/SUS). A data processing pipeline was conducted using Python 3.8.9. Results: The ASPPL course had 8,118 participants distributed across the five Brazilian regions. The analysis of course evaluation by participants who completed it shows that 5,190 (63.93%) reported a significant level of satisfaction (arithmetic mean = 4.9, median = 5, and standard deviation = 0.35). The analysis revealed that 3,272 participants (40.31%) are health workers operating in distinct levels of care. The prison system epidemiological data shows an increase in syphilis diagnosis in correctional facilities. Conclusions: The course enabled the development of a massive training model for various health professionals at all care levels and regions of Brazil. This is particularly important in a country with a continental size and a large health workforce like Brazil. As a result, social and prison health impacts were observed.

Translational research in health technologies: A scoping review.

Introduction: The current debate on the process of technological innovation points out as a challenge for universities consolidation of competencies that allow the generation and transfer of knowledge to society. The Translational Research (TR) approach has as one of its main objectives the acceleration of the innovation process, based on the transposition from basic science to applied science and innovation, which comprises the different stages of research, development and innovation. The literature points out that the dynamics of translation, which results in new technologies, are complex, transdisciplinary, inter-institutional, systemic, and non-linear. The main objective of this review is to contribute to the adoption of institutional strategies and the formulation of public policies aimed at solving today's social and economic challenges, ensuring access to technologies and sustainability for the health system. The specific objectives were: (i) to systematize studies that characterized translational research in medical devices; (ii) map the challenges for the implementation of translational health research; (iii) contribute to the design of institutional strategies; and (iv) support the formulation of public policies. Methods: This study used the scoping review technique, according to PRISMA-ScR and the Joanna Briggs Institute guidelines. Concerning the extraction of relevant articles, the journals indexed in Bireme, Pubmed, Scopus, Web of Science, and Google Scholar were consulted for selecting relevant articles. The search was carried out on November 28, 2021, updated on April 29, 2022, and there were no restrictions as to the year of publication, language or type of analysis. Studies that did not answer the research question were excluded, as they dealt exclusively with the pharmaceutical segment, the translation of knowledge into clinical practice, or addressed the process of translational research applied to specific diseases or technologies. Results: Thirty-three articles were included indicating that the approach of translation of research is multidisciplinary and transdisciplinary and encompasses knowledge and aspects that go beyond basic and applied research and incorporates final steps concerning regulatory aspects, clinical research, market analysis, technology transfer, production and incorporation of technologies into the health system.

Virtual Learning Environment of the Brazilian Health System (AVASUS): Efficiency of Results, Impacts, and Contributions.

The Virtual Learning Environment of the Brazilian Health System (AVASUS) is a free and open distance education platform of the Ministry of Health (MS). AVASUS is a scalable virtual learning environment that has surpassed 800,000 users, 2 million enrollments, and 310 courses in its catalog. The objective of this paper was to assess the impacts of the educational offerings on health services and AVASUS course participants' professional practice. This study analyzed data from AVASUS, the Brazilian National Registry of Health Care Facilities (CNES), the Brazilian Occupational Classification (CBO), and a questionnaire applied to 720-course participants from five regions of Brazil. After acquiring and extracting data, computational methods were used for the evaluation process. Only the responses of 462 participants were considered for data analysis, as they had a formal link to CNES. The results showed that respondents recommended 76.2% of AVASUS courses to peers. Accordingly, the quality of educational offerings motivated 81.3% of such recommendations. In addition, 75.6% of course participants who answered the questionnaire also indicated that AVASUS course contents contribute to enhancing existing health services in the health facilities where they work. Finally, 24.6% of all responses mentioned that courses available in AVASUS were essential in offering new health services in such facilities.