Transition from an in-person to a telemedicine diabetic retinopathy screening program.

PURPOSE: Timely screening and treatment are essential for preventing diabetic retinopathy blindness. Improving screening workflows can reduce waiting times for specialist evaluation and thus enhance patient outcomes. This study assessed different screening approaches in a Brazilian public healthcare setting. METHODS: This retrospective study evaluated a telemedicine-based diabetic retinopathy screening implemented during the COVID-19 pandemic and compared it with in-person strategies. The evaluation was conducted from the perspective of a specialized referral center in an urban area of Central-West Brazil. In the telemedicine approach, a trained technician would capture retinal images by using a handheld camera. These images were sent to specialists for remote evaluation. Patient variables, including age, gender, duration of diabetes diagnosis, diabetes treatment, comorbidities, and waiting time, were analyzed and compared. RESULTS: In total, 437 patients with diabetes mellitus were included in the study (mean age: 62.5 ± 11.0 years, female: 61.7%, mean diabetes duration: 15.3 ± 9.7 years, insulin users: 67.8%). In the in-person assessment group, the average waiting time between primary care referral and specialist evaluation was 292.3 ± 213.9 days, and the referral rate was 73.29%. In the telemedicine group, the average waiting time was 158.8 ± 192.4 days, and the referral rate was 29.38%. The telemedicine approach significantly reduced the waiting time (p<0.001) and significantly lowered the referral rate (p<0.001). CONCLUSION: The telemedicine approach significantly reduced the waiting time for specialist evaluation in a real-world setting. Employing portable retinal cameras may address the burden of diabetic retinopathy, especially in resource-limited settings.

Could Teledentistry Be a Solution in the Diagnosis of Oral Lesions?

In recent years, teledentistry has gained visibility, especially because of the COVID-19 pandemic. Concerning oral medicine, there is great expectation, particularly about its potential to promote early diagnosis of oral lesions. In southern Brazil, two initiatives have shown a positive influence on each other and have led to greater awareness of oral cancer and more access to qualified advice on diagnosing and managing oral lesions. Although the contributions of this approach are promising, there are barriers to be overcome.

Diagnostic evaluation of institutions as a basis for designing the Brazilian maturity model of telehealth services.

BACKGROUND: The number and specificities of telehealth service units that expanded their services and diversified with the COVID-19 pandemic in Brazil need to be discovered. The objective of this manuscript is to present a methodology for the diagnostic evaluation of 19 telehealth units from different regions of the country for federal governmental decision-making. METHODS: A cross-sectional quantitative and qualitative study was carried out in the form of a census based on administrative records with an online survey and in-depth interviews with local telehealth managers. RESULTS: Despite the discontinuity of regular funding, the results point to a diversity of initiatives and advances. Citizenship, sustainability, security, and budget management are recurring themes in the maturity analysis of telehealth services after the advent of the pandemic. CONCLUSION: It is necessary for Brazil to build a resilient model of the maturity of telehealth services that contemplates the different regional scenarios.

Agreement between Handheld and Standard Echocardiography for Diagnosis of Latent Rheumatic Heart Disease in Brazilian Schoolchildren from High-Prevalence Settings (Agreement between Screening and Standard Echo for RHD).

Introduction: Handheld echocardiography (echo) is the tool of choice for rheumatic heart disease (RHD) screening. We aimed to assess the agreement between screening and standard echo for latent RHD diagnosis in schoolchildren from an endemic setting. Methods: Over 14 months, 3 nonphysicians used handheld machines and the 2012 WHF Criteria to determine RHD prevalence in consented schoolchildren from Brazilian low-income public schools. Studies were interpreted by telemedicine by 3 experts (Brazil, US). RHD-positive children (borderline/definite) and those with congenital heart disease (CHD) were referred for standard echo, acquired and interpreted by a cardiologist. Agreement between screening and standard echo, by WHF subgroups, was assessed. Results: 1390 students were screened in 6 schools, with 110 (7.9%, 95% CI 6.5-9.5) being screen positive (14 ± 2 years, 72% women). Among 16 cases initially diagnosed as definite RHD, 11 (69%) were confirmed, 4 (25%) reclassified to borderline, and 1 to normal. Among 79 cases flagged as borderline RHD, 19 (24%) were confirmed, 50 (63%) reclassified to normal, 8 (10%) reclassified as definite RHD, and 2 had mild CHD. Considering the 4 diagnostic categories, kappa was 0.18. In patients with borderline RHD reclassified to non-RHD, the most frequent WHF criterion was B (isolated mitral regurgitation, 64%), followed by A (2 mitral valve morphological features, 31%). In 1 patient with definite RHD reclassified to normal, the WHF criterion was D (borderline RHD in aortic and mitral valves). After standard echo, RHD prevalence was 3.2% (95% CI 2.3-4.2). Conclusions: Although practical, RHD screening with handheld devices tends to overestimate prevalence.

Expanded disability status scale by phone BR: Brazilian Portuguese validation.

BACKGROUND: The Expanded Disability Status Scale (EDSS) is widely used and accepted by regulatory agencies for the assessment of neurological disability secondary to Multiple Sclerosis. The "Expanded Disability Status Scale (EDSS) by phone" was developed to be a patient-reported telephone-based alternative for the assessment of EDSS functional system scores when a physical examination is not possible. The scale has been validated in multiple languages; however, its reliability has not been assessed in Brazilian Portuguese. METHODS: After cross-cultural translation and adaptation, 57 people with MS with a recent in-person visit (±6 months) were invited to answer the EDSS by phone scale on two occasions, 15 days apart. The agreement between scales (in-person and telephone-based) and between telephone-based assessments was evaluated using intraclass correlation coefficients (ICC) for absolute agreement and weighted Kappa coefficients. RESULTS: An excellent reliability was obtained for the agreement between the in-person and telephone assessments (ICC: 0.95, 95 %CI 0.92-0.97, Kappa: 0.83, 95 %CI 0.78-0.89) and between telephone-based assessments (ICC: 0.99, 95 %CI 0.98-0.99, Kappa: 0.93, 95 %CI 0.88-0.97). After stratification by disability level, the agreement between scales was less pronounced for subjects with an EDSS ≤ 4.0. CONCLUSION: this study offers evidence that supports the validity of the EDSS by phone questionnaire translated into Brazilian Portuguese, particularly for patients with higher EDSS scores.

Teleconsulta de enfermagem: desenvolvimento de plataforma para atendimento de casos de Covid-19 / Nursing teleconsultation: development of a platform for Covid-19 case management / Telecosulta en enfermería: desarrollo de una plataforma para el manejo de casos de Covid-19

Objetivo: Desenvolver uma plataforma virtual de Teleconsulta para atendimento a casos suspeitos de Síndromes Gripais e infecção por COVID-19. Metodologia: Trata-se de um estudo de natureza aplicada, com desenvolvimento de produção tecnológica e inovadora, prospectivo, ecológico, descritivo, de série temporal. A população do estudo foi formada por qualquer pessoa sintomática para Síndromes Gripais por COVID-19, suspeitos ou confirmados, de qualquer local do Brasil. Este estudo foi realizado em duas etapas, a saber: Etapa I: Desenvolvimento da Aplicação para Plataforma de Teleconsulta. Etapa II: atendimento por meio de Teleconsulta de Casos suspeitos de COVID-19 e Sindromes Gripais. A metodologia utilizada para o desenvolvimento da aplicação proposta foi a modelagem por prototipação evolucionária. Resultados: Foram realizados 209 atendimentos na Plataforma de Teleconsulta, sendo 151 (70%) do sexo feminino e 65 (30%) do sexo masculino, com prevalência de idade variando de 20 a 29 anos (41%). Quanto ao risco de infecção por COVID-19, 42 (20%) tinham alto risco, 75 (36%) médio risco e 92 (44%) baixo risco. Os sintomas mais prevalentes foram: secreção nasal ou espirros (53%), dores no corpo (49%), dor de cabeça (47%), dor de garganta (46%), tosse seca (35%), Febre (31%), falta de ar (25%) e diarreia (23%). Inicialmente o teleatendimento foi composto por teletriagem com classificação de risco com base na sintomatologia dos pacientes que foram codificados com pontuações conforme a gravidade do sintoma para formas graves de COVID-19. A classificação de risco categorizou os pacientes em risco baixo (1 a 9 pontos), risco médio (10 a 19 pontos) e risco alto (20 a 36 pontos). Em seguida, a teleconsulta foi agendada conforme disponibilidade do paciente por meio do método SBAR para comunicação efetiva e ao término do atendimento um plano de cuidados com Sistematização da Assistência de Enfermagem ­ SAE era encaminhado ao paciente por meio de WhatsApp ou e-mail. Conclusão: A plataforma de teleconsulta possibilitou a triagem dos pacientes, reduziu as visitas desnecessárias às unidades de emergência, permitiu a avaliação e monitoramento dos casos, bem como o acompanhamento de pacientes ambulatoriais que não necessitam de avaliação presencial.

Objective: To develop a virtual Teleconsultation platform for care of suspected cases of influenza syndromes and infection by COVID-19. Methodology: This is a study of applied nature, with development of technological and innovative production, prospective, ecological, descriptive, time series. The study population was made up of any person symptomatic for COVID-19 influenza syndromes, suspected or confirmed, from any location in Brazil. This study was conducted in two stages, namely: Stage I: Development of the Application for Teleconsultation Platform. Stage II: care through Teleconsultation of suspected cases of COVID-19 and influenza syndromes. The methodology used to develop the proposed application was evolutionary prototyping modeling. Results: There were 209 consultations in the Teleconsultation Platform, 151 (70%) were female and 65 (30%) were male, with prevalence of age ranging from 20 to 29 years (41%). As for the risk of infection by COVID-19, 42 (20%) had high risk, 75 (36%) medium risk and 92 (44%) low risk. The most prevalent symptoms were: nasal discharge or sneezing (53%), body aches (49%), headache (47%), sore throat (46%), dry cough (35%), fever (31%), shortness of breath (25%), and diarrhea (23%). Initially, the telecare was composed of teletry with risk classification based on the symptomatology of the patients who were coded with scores according to symptom severity for severe forms of COVID-19. The risk classification categorized patients into low risk (1 to 9 points), medium risk (10 to 19 points), and high risk (20 to 36 points). Then, the teleconsultation was scheduled according to the patient's availability through the SBAR method for effective communication and at the end of the service a care plan with Nursing Assistance Systematization - SAE was forwarded to the patient through WhatsApp or e-mail. Conclusion: Teleconsultation platform enabled patient triage, reduced unnecessary visits to emergency units, allowed the evaluation and monitoring of cases, as well as the follow- up of outpatients who do not need face-to-face evaluation.

Objetivo: Desarrollar una plataforma de Teleconsulta virtual para atender casos sospechosos de síndromes gripales e infección por COVID-19. Metodología: Se trata de un estudio aplicado, con desarrollo de producción tecnológica e innovadora, prospectivo, ecológico, descriptivo, con serie de tiempo. La población de estudio estuvo formada por cualquier persona sintomática de síndromes gripales por COVID-19, sospechada o confirmada, de cualquier localidad de Brasil. Este estudio se realizó en dos etapas, a saber: Etapa I: Desarrollo de Aplicaciones para la Plataforma de Teleconsulta. Etapa II: atención mediante teleconsulta de casos sospechosos de COVID-19 y síndromes gripales. La metodología utilizada para el desarrollo de la aplicación propuesta fue el modelado por prototipo evolutivo. Resultados: Se realizaron 209 consultas en la Plataforma de Teleconsulta, 151 (70%) del sexo femenino y 65 (30%) del masculino, con prevalencia de edades entre 20 a 29 años (41%). En cuanto al riesgo de infección por COVID-19, 42 (20%) fueron de alto riesgo, 75 (36%) de riesgo medio y 92 (44%) de bajo riesgo. Los síntomas más prevalentes fueron: secreción nasal o estornudos (53%), dolor de cuerpo (49%), dolor de cabeza (47%), dolor de garganta (46%), tos seca (35%), fiebre (31%), falta de aliento (25%) y diarrea (23%). Inicialmente, la teleasistencia consistía en teleselección con clasificación de riesgo en función de la sintomatología de los pacientes a los que se codificaba con puntuaciones según la gravedad del síntoma para formas graves de COVID-19. La clasificación de riesgo clasificó a los pacientes en riesgo bajo (1 a 9 puntos), riesgo medio (10 a 19 puntos) y riesgo alto (20 a 36 puntos). Luego, se programó la teleconsulta de acuerdo a la disponibilidad del paciente a través del método SBAR para una comunicación efectiva y al final de la atención se remitió al paciente un plan de cuidados con Sistematización de Atención de Enfermería - SAE vía WhatsApp o correo electrónico. Conclusión: La plataforma de teleconsulta posibilitó el triaje de pacientes, redujo las visitas innecesarias a las unidades de emergencia, permitió la evaluación y seguimiento de casos, así como el seguimiento de pacientes ambulatorios que no requieren evaluación presencial.

Effectiveness of m-health-based core strengthening exercise and health education for public safety workers with chronic non-specific low back pain: study protocol for a superiority randomized controlled trial (SAFEBACK).

BACKGROUND: Low back pain (LBP) is the leading cause of years lived with disability worldwide. Public safety workers are highly exposed to physically demanding activities and inappropriate postures, increasing the risk of experiencing LBP. Smartphone app-based self-managed interventions may be an alternative for chronic non-specific LBP (CNSLBP) treatment. This study aims to evaluate the effectiveness of a smartphone app-based self-managed exercise program plus health education, compared to a health education program alone, on neuromuscular and perceptual outcomes in police officers and firefighters with CNSLBP. METHODS: This is a parallel, two-armed, blinded evaluator randomized clinical trial. Police officers and firefighters (from public safety institutions in the Rio Grande do Sul state, Brazil) will be randomly assigned to a m-health self-managed exercise program (twice a week) plus health education or health education alone. Self-management exercise program components are mobility and core resistance exercises, available on the app. Follow-ups will be conducted post-treatment (8 weeks) and 16 weeks after randomization. The co-primary outcomes will be pain intensity and disability post-treatment (8 weeks). Secondary outcomes will be biopsychosocial factors related to CNSLBP. DISCUSSION: We hypothesize that the effects of a smartphone app-based self-managed exercise program on co-primary and secondary outcomes will be superior, compared to the health education only in public safety workers with CNSLBP. TRIAL REGISTRATION: The study was prospectively registered at ClinicalTrials.gov (NCT05481996. Registered on August 01, 2022).

One step at a time. Shaping consensus on research priorities and terminology in telehealth in musculoskeletal pain: an international modified e-Delphi study.

BACKGROUND: Telehealth has emerged as an alternative model for treatment delivery and has become an important component of health service delivery. However, there is inconsistency in the use of terminologies and a lack of research priorities in telehealth in musculoskeletal pain. The purpose of this international, multidisciplinary expert panel assembled in a modified three-round e-Delphi survey is to achieve a consensus on research priorities and for the standard terminology for musculoskeletal pain telehealth practice. METHODS: In this international modified e-Delphi survey, we invited an expert panel consisting of researchers, clinicians, consumer representatives, industry partners, healthcare managers, and policymakers to participate in a three-round e-Delphi. Expert panels were identified through the Expertscape website, PubMed database, social media, and a snowball approach. In Round 1, potential research priorities and terminologies were presented to panel members. Panel members rated the agreement of each research priority on a 5-point Likert scale and an 11-point numerical scale, and each terminology on a 5-point Likert scale for the "telehealth in musculoskeletal pain " field over rounds. At least 80% of the panel members were required to agree to be deemed a consensus. We analyzed the data descriptively and assessed the stability of the results using the Wilcoxon matched-pairs signed rank test. RESULTS: We performed an international e-Delphi survey from February to August 2022. Of 694 invited people, 160 panel members participated in the first round, 133 in the second round (83% retention), and 134 in the third round (84% retention). Most of the panel members were researchers 76 (47%), clinicians 57 (36%), and consumer representatives 9 (6%) of both genders especially from Brazil 31 (19%), India 22 (14%), and Australia 19 (12%) in the first round. The panel identified fourteen telehealth research priorities spanned topics including the development of strategies using information and communication technology, telehealth implementation services, the effectiveness and cost-effectiveness of telehealth interventions, equity of telehealth interventions, qualitative research and eHealth literacy in musculoskeletal pain conditions from an initial list of 20 research priorities. The consensus was reached for "digital health" and "telehealth" as standard terminologies from an initial list of 37 terminologies. CONCLUSION: An international, multidisciplinary expert consensus recommends that future research should consider the 14 research priorities for telehealth musculoskeletal pain reached. Additionally, the terms digital health and telehealth as the most appropriate terminologies to be used in musculoskeletal telehealth research. REGISTER: Open Science Framework ( https://osf.io/tqmz2/ ).

[Duration of remote work and a positive diagnosis of COVID-19: an analysis of PNAD COVID19 data]. / Duração do trabalho remoto e diagnóstico positivo de COVID-19: análises dos dados da PNAD COVID19.

The scope of this work was to assess the association between the duration of remote work and a positive diagnosis of COVID-19 among individuals employed in Brazil. Data from the PNAD COVID19 (2020) survey were consulted. The variables in the work situation described included: absence from work due to physical distancing, work segment (work sector and formality: formal or informal private, military, statutory civil servant, CLT public sector, informal public sector, employer, self-employed/unpaid worker) and duration of remote work (no remote work for 1-2 months, 3-4 months, 5-7 months, respectively). The association between duration of remote work (exposure) and positive diagnosis for COVID-19 (outcome) was estimated by Cox regression, with adjustment for sociodemographic variables and work segment. The positive diagnosis of COVID-19 increased from 2.1% to 4.8% between July and November, and the frequency of remote work decreased from 11.6% to 9.5% between May and November. The risk of a positive diagnosis of COVID-19 was lower for people working remotely for 3-4 months, (HR=0.79; CI95%=0.67;0.92) and 5-7 months (HR=0.57; CI95%=0.48;0.67) compared to those who did not work remotely. There was a slight decrease in the percentage of remote work employees, and a longer duration reduced the risk of a positive diagnosis for COVID-19.

Nosso objetivo foi analisar a associação entre a duração do trabalho remoto e o diagnóstico positivo da COVID-19 entre pessoas ocupadas no Brasil. Foram utilizados dados da PNAD COVID19 (2020). As variáveis sobre a situação do trabalho descritas foram: afastamento do trabalho em função do distanciamento físico, segmento de trabalho (setor de trabalho e formalidade: privado formal/informal, militar, servidor público estatutário, setor público CLT/informal, empregador, conta-própria/trabalhador não remunerado) e duração do trabalho remoto (sem trabalho remoto, 1-2 meses, 3-4 meses, 5-7 meses). Associação entre duração do trabalho remoto (exposição) e diagnóstico positivo para COVID-19 (desfecho) foi estimada por regressão de Cox, com ajuste para variáveis sociodemográficas e segmento de trabalho. O diagnóstico positivo da COVID-19 aumentou de 2,1% para 4,8% entre julho e novembro, e a frequência de trabalho remoto reduziu de 11,6% para 9,5% entre maio e novembro. O risco de diagnóstico positivo da COVID-19 foi menor para pessoas que trabalharam remotamente por 3-4 meses (RR=0,79; IC95%=0,67;0,92) e 5 meses (RR=0,57; IC95%=0,48;0,67) comparadas àquelas que não trabalharam remotamente. Houve discreta redução do percentual de trabalhadores em trabalho remoto e sua maior extensão reduziu o risco de diagnóstico positivo para COVID-19.

End-to-end risk prediction of atrial fibrillation from the 12-Lead ECG by deep neural networks.

BACKGROUND: Atrial fibrillation (AF) is one of the most common cardiac arrhythmias that affects millions of people each year worldwide and it is closely linked to increased risk of cardiovas- cular diseases such as stroke and heart failure. Machine learning methods have shown promising results in evaluating the risk of developing atrial fibrillation from the electrocardiogram. We aim to develop and evaluate one such algorithm on a large CODE dataset collected in Brazil. METHODS: We used the CODE cohort to develop and test a model for AF risk prediction for individual patients from the raw ECG recordings without the use of additional digital biomarkers. The cohort is a collection of ECG recordings and annotations by the Telehealth Network of Minas Gerais, in Brazil. A convolutional neural network based on a residual network architecture was implemented to produce class probabilities for the classification of AF. The probabilities were used to develop a Cox proportional hazards model and a Kaplan-Meier model to carry out survival analysis. Hence, our model is able to perform risk prediction for the development of AF in patients without the condition. RESULTS: The deep neural network model identified patients without indication of AF in the presented ECG but who will develop AF in the future with an AUC score of 0.845. From our survival model, we obtain that patients in the high-risk group (i.e. with the probability of a future AF case being >0.7) are 50% more likely to develop AF within 40 weeks, while patients belonging to the minimal-risk group (i.e. with the probability of a future AF case being less than or equal to 0.1) have >85% chance of remaining AF free up until after seven years. CONCLUSION: We developed and validated a model for AF risk prediction. If applied in clinical practice, the model possesses the potential of providing valuable and useful information in decision- making and patient management processes.

Duração do trabalho remoto e diagnóstico positivo de COVID-19: análises dos dados da PNAD COVID19 / Duration of remote work and a positive diagnosis of COVID-19: an analysis of PNAD COVID19 data

Resumo Nosso objetivo foi analisar a associação entre a duração do trabalho remoto e o diagnóstico positivo da COVID-19 entre pessoas ocupadas no Brasil. Foram utilizados dados da PNAD COVID19 (2020). As variáveis sobre a situação do trabalho descritas foram: afastamento do trabalho em função do distanciamento físico, segmento de trabalho (setor de trabalho e formalidade: privado formal/informal, militar, servidor público estatutário, setor público CLT/informal, empregador, conta-própria/trabalhador não remunerado) e duração do trabalho remoto (sem trabalho remoto, 1-2 meses, 3-4 meses, 5-7 meses). Associação entre duração do trabalho remoto (exposição) e diagnóstico positivo para COVID-19 (desfecho) foi estimada por regressão de Cox, com ajuste para variáveis sociodemográficas e segmento de trabalho. O diagnóstico positivo da COVID-19 aumentou de 2,1% para 4,8% entre julho e novembro, e a frequência de trabalho remoto reduziu de 11,6% para 9,5% entre maio e novembro. O risco de diagnóstico positivo da COVID-19 foi menor para pessoas que trabalharam remotamente por 3-4 meses (RR=0,79; IC95%=0,67;0,92) e 5 meses (RR=0,57; IC95%=0,48;0,67) comparadas àquelas que não trabalharam remotamente. Houve discreta redução do percentual de trabalhadores em trabalho remoto e sua maior extensão reduziu o risco de diagnóstico positivo para COVID-19.

Abstract The scope of this work was to assess the association between the duration of remote work and a positive diagnosis of COVID-19 among individuals employed in Brazil. Data from the PNAD COVID19 (2020) survey were consulted. The variables in the work situation described included: absence from work due to physical distancing, work segment (work sector and formality: formal or informal private, military, statutory civil servant, CLT public sector, informal public sector, employer, self-employed/unpaid worker) and duration of remote work (no remote work for 1-2 months, 3-4 months, 5-7 months, respectively). The association between duration of remote work (exposure) and positive diagnosis for COVID-19 (outcome) was estimated by Cox regression, with adjustment for sociodemographic variables and work segment. The positive diagnosis of COVID-19 increased from 2.1% to 4.8% between July and November, and the frequency of remote work decreased from 11.6% to 9.5% between May and November. The risk of a positive diagnosis of COVID-19 was lower for people working remotely for 3-4 months, (HR=0.79; CI95%=0.67;0.92) and 5-7 months (HR=0.57; CI95%=0.48;0.67) compared to those who did not work remotely. There was a slight decrease in the percentage of remote work employees, and a longer duration reduced the risk of a positive diagnosis for COVID-19.

Leprosy and tuberculosis control scenario of the national program for the improvement of access and quality of primary care in Brazil.

BACKGROUND: In Brazil, despite advances in public health policies aimed at eliminating and controlling infectious and parasitic diseases, the incidence of neglected diseases is still high. The epidemiological scenario in Brazil of diseases such as tuberculosis and leprosy evidences a public policy agenda that has not been resolute in terms of control, nor in terms of elimination. OBJECTIVE: To analyze the actions of diagnosis and treatment of leprosy and tuberculosis in the context of primary health care. METHODS: In this ecological study, data from the third cycle of the Program for the Improvement of Access and Quality of Primary Care were extracted from electronic address of the Primary Health Care Secretariat of Brazil in the area of Actions, Programs and Strategies. A total of 37,350 primary health care teams were that answered the questionnaire were eligible, with variables extracted from leprosy and tuberculosis control actions. The municipalities were grouped according to the characteristic of the Brazilian municipality. The partition chi-square and the Residuals Test were used to assess whether there was a difference in the proportion of tuberculosis and leprosy actions between types of municipalities. Statistics were carried out using Minitab 20 and Bioestat 5.3. RESULTS: Regarding the leprosy treatment location, there is a higher proportion of people referred to be treated at the reference in adjacent rural (p = 0.0097) and urban (p < 0.0001) municipalities; monitoring of people with leprosy referred to the service network (p. = 0.0057) in remote rural areas. Lower proportion of teams requesting bacilloscopy in remote rural areas (p = 0.0019). Rural areas have a higher proportion of teams that diagnose new cases (p = 0.0004). Regarding the actions of diagnosis and treatment of tuberculosis. There is a higher proportion of teams that carry out consultations at the unit itself in rural areas when compared to adjacent intermediaries (p = 0.0099) and urban (p < 0.0001); who requested sputum smear microscopy in adjacent intermediaries (p = 0.0021); X-ray in adjacent intermediaries (p < 0.0001) and urban (p < 0.0001); collection of the first sputum sample in urban (p < 0.0001) and adjacent rural areas (p < 0.0001); directly observed treatment (p < 0.0001) in adjacent rural municipalities. CONCLUSION: There are inequalities in the diagnosis and treatment of leprosy and tuberculosis among the types of municipalities.

Enhancing anomaly detection in distributed power systems using autoencoder-based federated learning.

The growing use of Internet-of-Things devices in electric power systems has resulted in increased complexity and flexibility, making monitoring power usage critical for effective system maintenance and detecting abnormal behavior. However, traditional anomalous power consumption detection methods struggle to handle the vast amounts of data generated by these devices. While deep learning and machine learning are effective in anomaly detection, they require significant amounts of training data collected on centralized servers. This centralized approach results in high response time delays and data leakage problems. To address these challenges, we propose an Autoencoder-based Federated Learning method that combines the AutoEncoder and Federated Learning networks to develop a high-accuracy algorithm for identifying anomalies of power consumption data in distributed power systems. The proposed method allows for decentralized training of anomaly detection models among IoT devices, reducing response time and eventually solving data leakage issues. Our experimental results demonstrate the effectiveness of the FLAE method in detecting anomalies without needing data transferring.

A distributed SDN-based intrusion detection system for IoT using optimized forests.

Along with the expansion of Internet of Things (IoT), the importance of security and intrusion detection in this network also increases, and the need for new and architecture-specific intrusion detection systems (IDS) is felt. In this article, a distributed intrusion detection system based on a software defined networking (SDN) is presented. In this method, the network structure is divided into a set of sub-networks using the SDN architecture, and intrusion detection is performed in each sub-network using a controller node. In order to detect intrusion in each sub-network, a decision tree optimized by black hole optimization (BHO) algorithm is used. Thus, the decision tree deployed in each sub-network is pruned by BHO, and the split points in its decision nodes are also determined in such a way that the accuracy of each tree in detecting sub-network attacks is maximized. The performance of the proposed method is evaluated in a simulated environment and its performance in detecting attacks using the NSLKDD and NSW-NB15 databases is examined. The results show that the proposed method can identify attacks in the NSLKDD and NSW-NB15 databases with an accuracy of 99.2% and 97.2%, respectively, which indicates an increase compared to previous methods.

Indoor Human Detection from a Building's Exterior Using 433 MHz Wireless Transceivers.

This study introduces a novel system for detecting humans inside a building by utilizing RF signals from the building's exterior. Existing RF communication devices encounter signal attenuation issues when passing through walls, limiting their effectiveness. In contrast, our system employs a low-power, long-distance communication signal operating at 433 MHz to enhance signal permeability, enabling the accurate detection of individuals within the building. The system analyzes received signal strength indicator (RSSI) data using variance and mean analysis algorithms to determine the presence or absence of people. The evaluation results indicate promising average accuracies of 88% for the variance analysis algorithm and 97.7% for the mean analysis algorithm. The proposed system holds potential for real-world deployment, particularly in challenging scenarios such as fire incidents, where pre-installation is challenging. Continued research and development efforts aim to enhance the system's performance and address any limitations, making it more effective and robust in various practical applications.

Assessment of the Implementation of a Chatbot-Based Screening for Burnout and COVID-19 Symptoms Among Residents During the Pandemic.

Background: Early identification of COVID-19 symptoms and burnout among residents is essential for proper management. Digital assistants might help in the large-scale screening of residents. Objective: To assess the implementation of a chatbot for tele-screening emotional exhaustion and COVID-19 among residents at a hospital in Brazil. Methods: From August to October 2020, a chatbot sent participants' phones a daily question about COVID-19 symptoms and a weekly question about emotional exhaustion. After 8 weeks, the residents answered the Maslach Burnout Inventory-Human Services Survey (MBI-HSS). The primary outcome was the reliability of the chatbot in identifying suspect cases of COVID-19 and burnout. Results: Among the 489 eligible residents, 174 (35.6%) agreed to participate. The chatbot identified 61 positive responses for COVID-19 symptoms, and clinical suspicion was confirmed in 9 residents. User error in the first weeks was the leading cause (57.7%, 30 of 52) of nonconfirmed suspicion. The chatbot failed to identify 3 participants with COVID-19 due to nonresponse. Twelve of 118 (10.2%) participants who answered the MBI-HSS were characterized as having burnout by the MBI-HHS. Two of them were identified as at risk by the chatbot and 8 never answered the emotional exhaustion screening question. Conversely, among the 19 participants identified as at risk for emotional exhaustion by the chatbot, 2 (10.5%) were classified with burnout, and 5 (26.3%) as overextended based on MBI-HHS scores. Conclusions: The chatbot was able to identify residents suspected of having COVID-19 and those at risk for burnout. Nonresponse was the leading cause of failure in identifying those at risk.

Access to rehabilitation professionals by individuals with stroke one month after hospital discharge from a stroke unit in Brazil is insufficient regardless of the pandemic.

OBJECTIVE: To compare access to rehabilitation professionals by individuals with stroke one month after hospital discharge from a stroke unit in Brazil, before and during the COVID-19 pandemic. MATERIALS AND METHODS: This longitudinal and prospective study included individuals aged 20 years or older without previous disabilities admitted into a stroke unit due to a first stroke. Individuals were divided into two groups: before (G1) and during (G2) the COVID-19 pandemic. Groups were matched for age, sex, education level, socioeconomic status, and stroke severity. One month after hospital discharge, individuals were contacted via telephone to collect data regarding their access to rehabilitation services based on the number of referred rehabilitation professionals. Then, between-group comparisons were conducted (α = 5%). RESULTS: The access to rehabilitation professionals was similar between groups. Rehabilitation professionals accessed included medical doctors, occupational therapists, physical therapists, and speech therapists. The first consultation after hospital discharge was mainly provided by public services. Despite the pandemic, telehealth was not frequent in any period evaluated. In both groups, the number of accessed professionals (G1 = 110 and G2 = 90) was significantly lower than the number of referrals (G1 = 212 and G2 = 194; p < 0.001). CONCLUSIONS: Access to rehabilitation professionals was similar between groups. However, the number of accessed rehabilitation professionals was lower than that of referred ones during both periods. This finding indicates a compromised comprehensiveness of care for individuals with stroke, regardless of the pandemic.

Temporomandibular disorders and orofacial neuropathic pain in children and adolescents: a systematic review.

Pediatric orofacial pain (OFP) is a blanket term referring to the pain of soft and hard tissue in the face, neck and headaches affecting subjects younger than 18. OFP encompasses pain due to various causes, i.e., (i) Temporomandibular Disorders (TMD), (ii) Headache, and (iii) Neuropathies. This review aims to provide an overview of these three causes of OFP. The inclusion criteria are: (1) articles in English; (2) human studies; (3) clinical trials; (4) systematic review. Data from the included studies using a customized data extraction on a Microsoft Excel sheet. PubMed, Web of Science and Lilacs were systematically searched. The time window considered for the electronic search was from 01 January 1950 to 21 October 2022. A total of 3399 articles published were found from electronic searches. Finally, six full-text articles satisfied the inclusion criteria. The included studies have been published over the past 27 years (1993 to 2020). The studies analyzed were conducted in various parts of the world: USA, Argentina, Canada, South America (Brazil), and India. A total of 308 subjects were analyzed. TMD, headache, and neuropathies are among the leading causes of orofacial pain. Lifestyle changes and psychological approaches could be curative. However, some patients need pharmacotherapy. Regarding the inadequate treatment of pain after hospital discharge due to the difficulty of following the scheduled intervals prescribed, remote monitoring through telemedicine tools could be a solution in the future. Several conditions present with pain in children and adolescents; in most of them, pain is the most prominent symptom. This review found that one of the most critical causes of OFP is temporomandibular dysfunction. Treatment is founded on a multidisciplinary approach.

Effectiveness of a multicomponent intervention to face the COVID-19 pandemic in Rio de Janeiro's favelas: difference-in-differences analysis.

INTRODUCTION: Few community-based interventions addressing the transmission control and clinical management of COVID-19 cases have been reported, especially in poor urban communities from low-income and middle-income countries. Here, we analyse the impact of a multicomponent intervention that combines community engagement, mobile surveillance, massive testing and telehealth on COVID-19 cases detection and mortality rates in a large vulnerable community (Complexo da Maré) in Rio de Janeiro, Brazil. METHODS: We performed a difference-in-differences (DID) analysis to estimate the impact of the multicomponent intervention in Maré, before (March-August 2020) and after the intervention (September 2020 to April 2021), compared with equivalent local vulnerable communities. We applied a negative binomial regression model to estimate the intervention effect in weekly cases and mortality rates in Maré. RESULTS: Before the intervention, Maré presented lower rates of reported COVID-19 cases compared with the control group (1373 vs 1579 cases/100 000 population), comparable mortality rates (309 vs 287 deaths/100 000 population) and higher case fatality rates (13.7% vs 12.2%). After the intervention, Maré displayed a 154% (95% CI 138.6% to 170.4%) relative increase in reported case rates. Relative changes in reported death rates were -60% (95% CI -69.0% to -47.9%) in Maré and -28% (95% CI -42.0% to -9.8%) in the control group. The case fatality rate was reduced by 77% (95% CI -93.1% to -21.1%) in Maré and 52% (95% CI -81.8% to -29.4%) in the control group. The DID showed a reduction of 46% (95% CI 17% to 65%) of weekly reported deaths and an increased 23% (95% CI 5% to 44%) of reported cases in Maré after intervention onset. CONCLUSION: An integrated intervention combining communication, surveillance and telehealth, with a strong community engagement component, could reduce COVID-19 mortality and increase case detection in a large vulnerable community in Rio de Janeiro. These findings show that investment in community-based interventions may reduce mortality and improve pandemic control in poor communities from low-income and middle-income countries.

Implementation of an online pain science education for chronic musculoskeletal pain in Brazilian public health system: protocol for a hybrid type III randomised controlled trial with economic evaluation.

BACKGROUND: Although clinical practice guidelines recommend pain education as the first-line option for the management of chronic musculoskeletal pain, there is a lack of pain education programmes in healthcare. Thus, digital health programmes can be an effective tool for implementing pain education strategies for public health. This trial will aim to analyse the implementation and effectiveness outcomes of three online pain science education strategies in the Brazilian public health system (SUS) for individuals with chronic musculoskeletal pain. METHODS: We will conduct a hybrid type III effectiveness-implementation randomised controlled trial with economic evaluation. We will include adult individuals with chronic musculoskeletal pain, recruited from primary healthcare in the city of Guarapuava, Brazil. Individuals will be randomised to three implementation groups receiving a pain science education intervention (EducaDor) but delivered in different modalities: group 1) synchronous online; group 2) asynchronous videos; and group 3) interactive e-book only. Implementation outcomes will include acceptability, appropriateness, feasibility, adoption, fidelity, penetration, sustainability, and costs. We will also assess effectiveness outcomes, such as pain, function, quality of life, sleep, self-efficacy, and adverse effects. Cost-effectiveness and cost-utility analyses will be conducted from the SUS and societal perspectives. The evaluations will be done at baseline, post-intervention (10 weeks), and 6 months. DISCUSSION: This study will develop and implement a collaborative intervention model involving primary healthcare professionals, secondary-level healthcare providers, and patients to enhance self-management of chronic pain. In addition to promoting better pain management, this study will also contribute to the field of implementation science in public health by generating important insights and recommendations for future interventions. TRIAL REGISTRATION: ClinicalTrials.gov (NCT05302180; 03/29/2022).