RESUMO Objetivo: Esse estudo tem como objetivo criar um modelo de Machine Learning por um oftalmologista sem experiência em programação utilizando auto Machine Learning predizendo influxo de pacientes em serviço de emergência e casos de trauma. Métodos: Um dataset de 366,610 visitas em Hospital Universitário da Universidade Federal de São Paulo de 01 de janeiro de 2014 até 31 de dezembro de 2019 foi incluído no treinamento do modelo, incluindo visitas/dia e código internacional de doenças. O treinamento e predição foram realizados com o Amazon Forecast por dois oftalmologistas sem experiência com programação. Resultados: O período de previsão estimou um volume de 206,37 pacientes/dia em p90, 180,75 em p50, 140,35 em p10 e média de 7,42 casos de trauma/dia em p90, 3,99 em p50 e 0,56 em p10. Janeiro de 2020 teve um total de 6.604 pacientes e média de 206,37 pacientes/dia, 13,5% menos do que a predição em p50. O período teve um total de 199 casos de trauma e média de 6,21 casos/dia, 55,77% mais casos do que a predição em p50. Conclusão: O desenvolvimento de modelos era restrito a cientistas de dados com experiencia em programação, porém a transferência de ensino com a tecnologia de auto Machine Learning permite o desenvolvimento de algoritmos por qualquer pessoa sem experiencia em programação. Esse estudo mostra um modelo com valores preditos próximos ao que ocorreram em janeiro de 2020. Fatores que podem ter influenciados no resultado foram feriados e tamanho do banco de dados. Esse é o primeiro estudo que aplicada auto Machine Learning em predição de visitas hospitalares com resultados próximos aos que ocorreram. Objetivo Métodos 366610 366 610 366,61 0 201 3 visitasdia dia doenças Resultados 20637 206 37 206,3 pacientesdia p90 p 18075 180 75 180,7 14035 140 35 140,3 p1 742 7 42 7,4 traumadia 399 99 3,9 p5 056 56 0,5 202 6604 6 604 6.60 135 13 5 13,5 19 621 21 6,2 casosdia casos/dia 5577 55 77 55,77 Conclusão 36661 36 61 366,6 20 2063 206, p9 1807 18 180, 1403 14 140, 74 4 7, 39 9 3, 05 0, 660 60 6.6 1 13, 62 2 6, 557 55,7 3666 366, 66 6. 55,

ABSTRACT Purpose: The emergency medical service is a fundamental part of healthcare, albeit crowded emergency rooms lead to delayed and low-quality assistance in actual urgent cases. Machine-learning algorithms can provide a smart and effective estimation of emergency patients’ volume, which was previously restricted to artificial intelligence (AI) experts in coding and computer science but is now feasible by anyone without any coding experience through auto machine learning. This study aimed to create a machine-learning model designed by an ophthalmologist without any coding experience using AutoML to predict the influx in the emergency department and trauma cases. Methods: A dataset of 356,611 visits at Hospital da Universidade Federal de São Paulo from January 01, 2014 to December 31, 2019 was included in the model training, which included visits/day and the international classification disease code. The training and prediction were made with the Amazon Forecast by 2 ophthalmologists with no prior coding experience. Results: The forecast period predicted a mean emergency patient volume of 216.27/day in p90, 180.75/day in p50, and 140.35/day in p10, and a mean of 7.42 trauma cases/ day in p90, 3.99/day in p50, and 0.56/day in p10. In January of 2020, there were a total of 6,604 patient visits and a mean of 206.37 patients/day, which is 13.5% less than the p50 prediction. This period involved a total of 199 trauma cases and a mean of 6.21 cases/day, which is 55.77% more traumas than that by the p50 prediction. Conclusions: The development of models was previously restricted to data scientists’ experts in coding and computer science, but transfer learning autoML has enabled AI development by any person with no code experience mandatory. This study model showed a close value to the actual 2020 January visits, and the only factors that may have influenced the results between the two approaches are holidays and dataset size. This is the first study to apply AutoML in hospital visits forecast, showing a close prediction of the actual hospital influx. Purpose healthcare lowquality low quality Machinelearning Machine patients (AI machinelearning Methods 356611 356 611 356,61 01 201 31 visitsday Results 21627day 216 27 p90 p 18075day 180 75 14035day 140 35 p10 742 7 42 7.4 399day 3 99 056day 0 56 6604 6 604 6,60 20637 206 37 206.3 patientsday patients/day 135 13 5 13.5 p5 19 621 21 6.2 casesday cases/day 5577 55 77 55.77 Conclusions scientists mandatory 202 size 35661 61 356,6 20 p9 18 14 p1 74 4 7. 9 660 60 6,6 2063 206. 1 13. 62 6. 557 55.7 3566 356, 66 6, 55.

ABSTRACT 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. Purpose blindness outcomes setting Methods telemedicinebased based COVID19 COVID 19 COVID-1 inperson person strategies CentralWest Central West Brazil camera variables age gender diagnosis comorbidities Results total 43 625 62 5 62. 110 11 0 11. years female 617 61 7 61.7% 153 15 3 15. 97 9 9. users 67.8%. 678 67.8% . 67 8 67.8%) group 2923 292 292. 2139 213 213. days 7329 73 29 73.29% 1588 158 158. 1924 192 4 192. 2938 38 29.38% p<0.001 p0001 p 001 (p<0.001 p<0.001. Conclusion realworld real world resourcelimited resource limited settings COVID1 1 COVID- 6 61.7 67.8 21 732 2 73.29 293 29.38 p<0.00 p000 00 (p<0.00 61. 67. 73.2 29.3 p<0.0 p00 (p<0.0 73. 29. p<0. p0 (p<0. p<0 (p<0 p< (p< (p

RESUMO Objetivos: A pandemia de COVID-19 foi iniciada em março de 2020 e mudou o sistema de saúde. Mudanças na alocação de recursos, sobrecarga de unidades de terapia intensiva, apreensão dos pacientes em procurar atendimento médico não relacionado ao COVID-19 e redução abrupta de todas as consultas e cirurgias não urgentes. Este estudo avalia o impacto em um pronto-socorro oftalmológico após 1 ano de pandemia, avaliando a correlação entre as fases de lockdown, a mortalidade do COVID-19 e as visitas ao pronto-socorro. Métodos: Estudo observacional retrospectivo que incluiu todos os pacientes admitidos no serviço de emergência oftalmológica do Hospital São Paulo, vinculado a UNIFESP/EPM, entre 1º de janeiro de 2019 e 28 de março de 2021. As visitas foram classificadas e comparadas em um grupo pré-pandemia e pandemia. Resultados: No período pré-pandemia, o hospital registrou um total de 71.485 atendimentos com média de 194,78 ± 49,74 atendimentos diários, e no grupo pandemia, um total de 41.791 com média de 114,18 ± 43,12 atendimentos diários, redução de 41,4%. Uma diminuição significativa de 16,4% (p<0,001) foi observada na prevalência de conjuntivite aguda e um aumento significativo de 6,4% (p<0,01) na prevalência de corpo estranho da córnea. Foi identificada uma correlação negativa entre a taxa de mortalidade do COVID-19 e as taxas de visita ao pronto-socorro. Conclusão: Esta análise de um ano mostrou uma redução de 41,4% nas visitas ao pronto-socorro, e uma diminuição significativa nas conjuntivites agudas. A mudança nos hábitos de higiene e o distanciamento social poderiam explicar essa redução, e o aumento da prevalência de traumas corneanos. Achados destacam a necessidade de medidas preventivas e educativas durante os períodos restritivos. Objetivos COVID19 COVID 19 COVID-1 202 saúde recursos intensiva urgentes prontosocorro pronto socorro lockdown prontosocorro. socorro. Métodos Paulo UNIFESPEPM UNIFESP EPM UNIFESP/EPM º 201 2 2021 prépandemia pré Resultados prépandemia, 71485 71 485 71.48 19478 194 78 194,7 4974 49 74 49,7 diários 41791 41 791 41.79 11418 114 18 114,1 4312 43 12 43,1 414 4 164 16 16,4 p<0,001 p0001 p 0 001 (p<0,001 64 6 6,4 p<0,01 p001 01 (p<0,01 córnea Conclusão 41,4 prontosocorro, socorro, agudas corneanos restritivos COVID1 COVID- 20 7148 7 48 71.4 1947 194, 497 49, 4179 79 41.7 1141 11 114, 431 43, 16, p<0,00 p000 00 (p<0,00 6, p<0,0 p00 (p<0,0 41, 714 71. 417 41. p<0, p0 (p<0, p<0 (p<0 p< (p< (p

ABSTRACT Purpose: The COVID-19 pandemic began in March 2020 and changed the healthcare system overall. The pandemic led to resource allocation changes, overloading of intensive care units, apprehensiveness of patients to seek medical care not related to COVID-19, and an abrupt reduction in all nonurgent consultations and surgeries. This study evaluated the impact on an ophthalmological emergency room for one year by assessing the correlation between societal lockdown phases and COVID-19 mortality. Methods: An observational, retrospective study was conducted that included all patients admitted to the Ophthalmology Emergency Department between January 1, 2019, and March 28, 2021. The visits were classified into prepandemic and pandemic groups that were then compared. Results: In the prepandemic period, the hospital registered a total of 71,485 visits with a mean of 194.78 ± 49.74 daily visits. In the pandemic group, there was a total of 41,791 visits with a mean of 114.18 ± 43.12 daily visits, which was a 41.4% decrease. A significant decrease (16.4 p<0.001) was observed in the prevalence of acute conjunctivitis, and a significant increase (6.4%; p<0.01) was observed in the prevalence of corneal foreign body disorders. A negative correlation was identified between the COVID-19 death rate and the ophthalmological inflow rates. Conclusion: This one-year analysis showed a reduction of 41.4% in emergency department visits and a significant decrease in infectious conditions. A change in hygiene habits and social distancing could explain this reduction, and the increased prevalence of trauma consultations highlighted the need for preventive and educative measures during these types of restrictive periods. Purpose COVID19 COVID 19 COVID-1 202 overall changes units COVID19, 19, surgeries mortality Methods observational 1 2019 28 2021 compared Results period 71485 71 485 71,48 19478 194 78 194.7 4974 49 74 49.7 group 41791 41 791 41,79 11418 114 18 114.1 4312 43 12 43.1 414 4 41.4 16.4 164 16 (16. p<0.001 p0001 p 0 001 conjunctivitis 6.4% 64 6 (6.4% p<0.01 p001 01 disorders rates Conclusion oneyear conditions periods COVID1 COVID- 20 201 2 7148 7 48 71,4 1947 194. 497 49. 4179 79 41,7 1141 11 114. 431 43. 41. 16. (16 p<0.00 p000 00 6.4 (6.4 p<0.0 p00 714 71, 417 41, (1 6. (6. p<0. p0 ( (6 p<0 p<

SUMMARY OBJECTIVE: The aim of this study was to evaluate the performance of ChatGPT-4.0 in answering the 2022 Brazilian National Examination for Medical Degree Revalidation (Revalida) and as a tool to provide feedback on the quality of the examination. METHODS: A total of two independent physicians entered all examination questions into ChatGPT-4.0. After comparing the outputs with the test solutions, they classified the large language model answers as adequate, inadequate, or indeterminate. In cases of disagreement, they adjudicated and achieved a consensus decision on the ChatGPT accuracy. The performance across medical themes and nullified questions was compared using chi-square statistical analysis. RESULTS: In the Revalida examination, ChatGPT-4.0 answered 71 (87.7%) questions correctly and 10 (12.3%) incorrectly. There was no statistically significant difference in the proportions of correct answers among different medical themes (p=0.4886). The artificial intelligence model had a lower accuracy of 71.4% in nullified questions, with no statistical difference (p=0.241) between non-nullified and nullified groups. CONCLUSION: ChatGPT-4.0 showed satisfactory performance for the 2022 Brazilian National Examination for Medical Degree Revalidation. The large language model exhibited worse performance on subjective questions and public healthcare themes. The results of this study suggested that the overall quality of the Revalida examination questions is satisfactory and corroborates the nullified questions. OBJECTIVE ChatGPT4.0 ChatGPT40 4.0 4 0 ChatGPT-4. 202 (Revalida METHODS ChatGPT4.0. 4.0. solutions adequate inadequate indeterminate disagreement chisquare chi square analysis RESULTS 7 87.7% 877 87 (87.7% 1 12.3% 123 12 3 (12.3% incorrectly p=0.4886. p04886 p p=0.4886 . 4886 (p=0.4886) 714 71.4 p=0.241 p0241 241 (p=0.241 nonnullified non groups CONCLUSION ChatGPT4 ChatGPT4. 40 4. ChatGPT-4 20 87.7 8 (87.7 12.3 (12.3 p0488 p=0.488 488 (p=0.4886 71. p=0.24 p024 24 (p=0.24 ChatGPT- 2 87. (87. 12. (12. p048 p=0.48 48 (p=0.488 p=0.2 p02 (p=0.2 (87 (12 p04 p=0.4 (p=0.48 p=0. p0 (p=0. (8 (1 (p=0.4 p=0 (p=0 ( p= (p= (p

RESUMO Objetivos: O objetivo do estudo é avaliar o perfil das visitas ao Pronto-Socorro de Oftalmologia (PS) do Hospital São Paulo, serviço público de atendimento terciário aberto 24 horas em São Paulo - Brasil, pertencente à Universidade Federal de São Paulo, nos últimos 11 anos. Métodos: Foi realizado um estudo transversal retrospectivo, com base em todos os pacientes (n=634.726) admitidos no pronto-socorro de oftalmologia do Hospital São Paulo entre janeiro de 2009 e dezembro de 2019. Resultados: De 2009 a 2019, houve um aumento no influxo de 39,2% com importante variação nos atendimentos ao longo dos anos, a mediana de idade foi de 38 ± 20,4 anos, o sexo masculino representou 53,3% e os pacientes únicos representaram 53,1%. Verificou-se que 79,5% das visitas ocorreram das 7h às 17h e 80,8% nos dias da semana. Os diagnósticos mais frequentes foram conjuntivite aguda seguida de blefarite, ceratite, hordéolo / calázio e corpo estranho corneano. Conclusão: Ao longo do período de análise do estudo, houve importante aumento nas apresentações, com predominância de atendimentos não urgentes e baixa proporção de pacientes com uma única visita. Nossos resultados evidenciam o perfil das consultas oftalmológicas, podendo gerar mudanças no sistema público de saúde visando a melhoria da qualidade do atendimento e acesso às emergências oftalmológicas na cidade de São Paulo. Objetivos ProntoSocorro Pronto Socorro PS (PS 2 Brasil 1 anos Métodos retrospectivo n=634.726 n634726 n 634 726 (n=634.726 prontosocorro pronto socorro 200 2019 Resultados 392 39 39,2 3 204 20 4 20, 533 53 53,3 531 53,1% Verificouse Verificou se 795 79 5 79,5 h 808 80 8 80,8 semana blefarite ceratite corneano Conclusão apresentações visita n=634.72 n63472 63 72 (n=634.72 201 39, 53, 53,1 7 79, 80, n=634.7 n6347 6 (n=634.7 n=634. n634 (n=634. n=634 n63 (n=634 n=63 n6 (n=63 n=6 (n=6 n= (n= (n

ABSTRACT Purpose: This study aimed to describe the visits profile to Hospital São Paulo’s ophthalmology emergency department, a 24-hour public open-access tertiary-care service in São Paulo, Brazil, that belongs to Federal University of São Paulo, over the last 11 years. Methods: A cross-sectional retrospective study was conducted, including all patients (n=634,726) admitted to the ophthalmology emergency department of Hospital São Paulo between January 2009 and December 2019. Results: From 2009 to 2019, the number of patients’ presentations increased to 39.2%, with considerable visits variation across the period. The median age was 38 ± 20.4 years. Males represented 53.3%, and single-visit patients represented 53.1%. A total of 79.5% of patients’ presentations occurred from 7 am to 5 pm, and 80.8% of patients’ presentations occurred during regular weekdays. The most frequent diagnoses were conjunctivitis, blepharitis, keratitis, hordeolum/chalazion, and corneal foreign body. Conclusions: Over the study period, presentations significantly increased in number, with nonurgent visits predominance, and a low number of single-visit patients. Our results demonstrate the ophthalmic visits profile and can lead to changes in the public health system to improve the quality of care and ophthalmology emergency access in São Paulo city. Purpose Paulos s 24hour hour 24 openaccess open tertiarycare tertiary Brazil 1 years Methods crosssectional cross sectional conducted n=634,726 n634726 n 634 726 (n=634,726 200 2019 Results 392 39 2 39.2% period 3 204 20 4 20. 533 53 53.3% singlevisit single visit 531 53.1% 795 79 79.5 pm 808 80 8 80.8 weekdays conjunctivitis blepharitis keratitis hordeolumchalazion hordeolum chalazion hordeolum/chalazion body Conclusions predominance city n=634,72 n63472 63 72 (n=634,72 201 39.2 53.3 53.1 79. 80. n=634,7 n6347 6 (n=634,7 39. 53. n=634, n634 (n=634, n=634 n63 (n=634 n=63 n6 (n=63 n=6 (n=6 n= (n= (n

RESUMO Objetivos: O objetivo do estudo é avaliar o perfil das visitas ao Pronto-Socorro de Oftalmologia (PS) do Hospital São Paulo, serviço público de atendimento terciário aberto 24 horas em São Paulo - Brasil, pertencente à Universidade Federal de São Paulo, nos últimos 11 anos. Métodos: Foi realizado um estudo transversal retrospectivo, com base em todos os pacientes (n=634.726) admitidos no pronto-socorro de oftalmologia do Hospital São Paulo entre janeiro de 2009 e dezembro de 2019. Resultados: De 2009 a 2019, houve um aumento no influxo de 39,2% com importante variação nos atendimentos ao longo dos anos, a mediana de idade foi de 38 ± 20,4 anos, o sexo masculino representou 53,3% e os pacientes únicos representaram 53,1%. Verificou-se que 79,5% das visitas ocorreram das 7h às 17h e 80,8% nos dias da semana. Os diagnósticos mais frequentes foram conjuntivite aguda seguida de blefarite, ceratite, hordéolo / calázio e corpo estranho corneano. Conclusão: Ao longo do período de análise do estudo, houve importante aumento nas apresentações, com predominância de atendimentos não urgentes e baixa proporção de pacientes com uma única visita. Nossos resultados evidenciam o perfil das consultas oftalmológicas, podendo gerar mudanças no sistema público de saúde visando a melhoria da qualidade do atendimento e acesso às emergências oftalmológicas na cidade de São Paulo.

ABSTRACT Purpose: This study aimed to describe the visits profile to Hospital São Paulo’s ophthalmology emergency department, a 24-hour public open-access tertiary-care service in São Paulo, Brazil, that belongs to Federal University of São Paulo, over the last 11 years. Methods: A cross-sectional retrospective study was conducted, including all patients (n=634,726) admitted to the ophthalmology emergency department of Hospital São Paulo between January 2009 and December 2019. Results: From 2009 to 2019, the number of patients’ presentations increased to 39.2%, with considerable visits variation across the period. The median age was 38 ± 20.4 years. Males represented 53.3%, and single-visit patients represented 53.1%. A total of 79.5% of patients’ presentations occurred from 7 am to 5 pm, and 80.8% of patients’ presentations occurred during regular weekdays. The most frequent diagnoses were conjunctivitis, blepharitis, keratitis, hordeolum/chalazion, and corneal foreign body. Conclusions: Over the study period, presentations significantly increased in number, with nonurgent visits predominance, and a low number of single-visit patients. Our results demonstrate the ophthalmic visits profile and can lead to changes in the public health system to improve the quality of care and ophthalmology emergency access in São Paulo city.

RESUMO Objetivos: A pandemia de COVID-19 foi iniciada em março de 2020 e mudou o sistema de saúde. Mudanças na alocação de recursos, sobrecarga de unidades de terapia intensiva, apreensão dos pacientes em procurar atendimento médico não relacionado ao COVID-19 e redução abrupta de todas as consultas e cirurgias não urgentes. Este estudo avalia o impacto em um pronto-socorro oftalmológico após 1 ano de pandemia, avaliando a correlação entre as fases de lockdown, a mortalidade do COVID-19 e as visitas ao pronto-socorro. Métodos: Estudo observacional retrospectivo que incluiu todos os pacientes admitidos no serviço de emergência oftalmológica do Hospital São Paulo, vinculado a UNIFESP/EPM, entre 1º de janeiro de 2019 e 28 de março de 2021. As visitas foram classificadas e comparadas em um grupo pré-pandemia e pandemia. Resultados: No período pré-pandemia, o hospital registrou um total de 71.485 atendimentos com média de 194,78 ± 49,74 atendimentos diários, e no grupo pandemia, um total de 41.791 com média de 114,18 ± 43,12 atendimentos diários, redução de 41,4%. Uma diminuição significativa de 16,4% (p<0,001) foi observada na prevalência de conjuntivite aguda e um aumento significativo de 6,4% (p<0,01) na prevalência de corpo estranho da córnea. Foi identificada uma correlação negativa entre a taxa de mortalidade do COVID-19 e as taxas de visita ao pronto-socorro. Conclusão: Esta análise de um ano mostrou uma redução de 41,4% nas visitas ao pronto-socorro, e uma diminuição significativa nas conjuntivites agudas. A mudança nos hábitos de higiene e o distanciamento social poderiam explicar essa redução, e o aumento da prevalência de traumas corneanos. Achados destacam a necessidade de medidas preventivas e educativas durante os períodos restritivos.

ABSTRACT Purpose: The COVID-19 pandemic began in March 2020 and changed the healthcare system overall. The pandemic led to resource allocation changes, overloading of intensive care units, apprehensiveness of patients to seek medical care not related to COVID-19, and an abrupt reduction in all nonurgent consultations and surgeries. This study evaluated the impact on an ophthalmological emergency room for one year by assessing the correlation between societal lockdown phases and COVID-19 mortality. Methods: An observational, retrospective study was conducted that included all patients admitted to the Ophthalmology Emergency Department between January 1, 2019, and March 28, 2021. The visits were classified into prepandemic and pandemic groups that were then compared. Results: In the prepandemic period, the hospital registered a total of 71,485 visits with a mean of 194.78 ± 49.74 daily visits. In the pandemic group, there was a total of 41,791 visits with a mean of 114.18 ± 43.12 daily visits, which was a 41.4% decrease. A significant decrease (16.4 p<0.001) was observed in the prevalence of acute conjunctivitis, and a significant increase (6.4%; p<0.01) was observed in the prevalence of corneal foreign body disorders. A negative correlation was identified between the COVID-19 death rate and the ophthalmological inflow rates. Conclusion: This one-year analysis showed a reduction of 41.4% in emergency department visits and a significant decrease in infectious conditions. A change in hygiene habits and social distancing could explain this reduction, and the increased prevalence of trauma consultations highlighted the need for preventive and educative measures during these types of restrictive periods.

RESUMO Objetivo: Esse estudo tem como objetivo criar um modelo de Machine Learning por um oftalmologista sem experiência em programação utilizando auto Machine Learning predizendo influxo de pacientes em serviço de emergência e casos de trauma. Métodos: Um dataset de 366,610 visitas em Hospital Universitário da Universidade Federal de São Paulo de 01 de janeiro de 2014 até 31 de dezembro de 2019 foi incluído no treinamento do modelo, incluindo visitas/dia e código internacional de doenças. O treinamento e predição foram realizados com o Amazon Forecast por dois oftalmologistas sem experiência com programação. Resultados: O período de previsão estimou um volume de 206,37 pacientes/dia em p90, 180,75 em p50, 140,35 em p10 e média de 7,42 casos de trauma/dia em p90, 3,99 em p50 e 0,56 em p10. Janeiro de 2020 teve um total de 6.604 pacientes e média de 206,37 pacientes/dia, 13,5% menos do que a predição em p50. O período teve um total de 199 casos de trauma e média de 6,21 casos/dia, 55,77% mais casos do que a predição em p50. Conclusão: O desenvolvimento de modelos era restrito a cientistas de dados com experiencia em programação, porém a transferência de ensino com a tecnologia de auto Machine Learning permite o desenvolvimento de algoritmos por qualquer pessoa sem experiencia em programação. Esse estudo mostra um modelo com valores preditos próximos ao que ocorreram em janeiro de 2020. Fatores que podem ter influenciados no resultado foram feriados e tamanho do banco de dados. Esse é o primeiro estudo que aplicada auto Machine Learning em predição de visitas hospitalares com resultados próximos aos que ocorreram.

ABSTRACT Purpose: The emergency medical service is a fundamental part of healthcare, albeit crowded emergency rooms lead to delayed and low-quality assistance in actual urgent cases. Machine-learning algorithms can provide a smart and effective estimation of emergency patients’ volume, which was previously restricted to artificial intelligence (AI) experts in coding and computer science but is now feasible by anyone without any coding experience through auto machine learning. This study aimed to create a machine-learning model designed by an ophthalmologist without any coding experience using AutoML to predict the influx in the emergency department and trauma cases. Methods: A dataset of 356,611 visits at Hospital da Universidade Federal de São Paulo from January 01, 2014 to December 31, 2019 was included in the model training, which included visits/day and the international classification disease code. The training and prediction were made with the Amazon Forecast by 2 ophthalmologists with no prior coding experience. Results: The forecast period predicted a mean emergency patient volume of 216.27/day in p90, 180.75/day in p50, and 140.35/day in p10, and a mean of 7.42 trauma cases/ day in p90, 3.99/day in p50, and 0.56/day in p10. In January of 2020, there were a total of 6,604 patient visits and a mean of 206.37 patients/day, which is 13.5% less than the p50 prediction. This period involved a total of 199 trauma cases and a mean of 6.21 cases/day, which is 55.77% more traumas than that by the p50 prediction. Conclusions: The development of models was previously restricted to data scientists’ experts in coding and computer science, but transfer learning autoML has enabled AI development by any person with no code experience mandatory. This study model showed a close value to the actual 2020 January visits, and the only factors that may have influenced the results between the two approaches are holidays and dataset size. This is the first study to apply AutoML in hospital visits forecast, showing a close prediction of the actual hospital influx.

Objetivos: Validar um sistema de teleoftalmologia móvel que tem como objetivo fornecer triagem de urgências oftalmológicas em áreas remotas e desfavorecidas do Brasil. O sistema permite que um ou mais oftalmologistas possam examinar remotamente a condição do paciente e apresentar uma decisão que descreve a gravidade do caso. Se necessário, o paciente será encaminhado ao hospital para consulta. Métodos: Através de um celular e sua câmera (modelo Nexus One com câmera de 5 megapixel), foram coletados dados de 100 pacientes aleatoriamente selecionados no pronto socorro oftalmológico da Universidade Federal de São Paulo (UNIFESP) e enviados remotamente para um sistema online, por meio do qual um oftalmologista analisou-os e enviou um diagnóstico sobre a gravidade dos casos. Os resultados enviados foram comparados com o padrão ouro que foi fornecido pelo médico no hospital. Resultados: O diagnóstico foi fornecido por dois oftalmologistas: um no hospital (padrão outro) e outro remotamente. Comparando os resultados dos diagnósticos, foi obtido 81,94% de especificidade, 92,85% de sensibilidade, acurácia de 85% e um valor preditivo negativo de 96,72%. Também foi testado o desempenho do sistema, resultando num tempo de processamento do atendimento remoto em média de 8,6 minutos por paciente. Conclusões: Esta solução de baixo custo é a primeira da literatura que utiliza apenas o telefone celular para detectar urgências oftalmológicas. Com base nos resultados, o sistema consegue oferecer um atendimento confiável, diferenciando os casos de urgências e não urgências através da plataforma de telemedicina. Como ferramenta de triagem, o mais importante é identificar os casos de urgência (ter alta sensibilidade). Assim, os resultados obtidos demonstram que a ferramenta é robusta e traz uma possibilidade real de conduzir um estudo maior para verificar sua eficiência em áreas mais distantes e desfavorecidas.

Purposes: To validate a teleophthalmology mobile system aimed at improving and providing eye urgency screenings in remote and poor area settings in Brazil. The system enables one or more ophthalmologists to remotely examine a patient's condition and submit a decision describing the gravity of the case. If necessary, the patient can be forwarded to a hospital for further consultation. Methods: A cellphone (Nexus One model, with a 5 megapixel camera) was used to collect data and pictures from 100 randomly selected patients at the Ophthalmology Emergency Room located at the General Hospital of the Federal University of São Paulo (UNIFESP). Data was then sent remotely to an online recording system to be reviewed by an ophthalmologist who provided feedback regarding the state of ocular urgency. Results were then compared to the gold standard diagnosis provided at the hospital. Results: The diagnosis of urgency was given by two ophthalmologists: one in the hospital (gold standard) and one remotely. When we compared both diagnoses we obtained results of 81.94% specificity, 92.85% sensitivity, and 85% accuracy, with a negative predictive value of 96.72%. This work also included a processing time analysis, resulting in an average time of 8.6 min per patient for remote consultations. Conclusions: This study is the first that has used only a cellphone for diagnosing the urgency of ocular cases. Based on our results, the system can provide a reliable distinction between urgent and non-urgent situations and can offer a viable alternative for the servicing of underprivileged areas. In screening techniques, the most important outcome is to identify urgent cases with a high level of sensitivity and predictive negative value. Thus, our results demonstrate that this tool is robust and we suggest that a major study aimed to verify its efficiency in resource-poor areas should be initiated.

Descrevemos o caso de uma paciente, de 53 anos, com quadro de oclusão de ramo venoso da retina após receber seis infusões de infliximabe (3 mg/kg/dose), para tratamento de artrite reumatóide. A investigação clínica e laboratorial sobre distúrbios de coagulação, cardiopatias e sinais de hipertensão arterial crônica foi negativa. A relação temporal do uso de infliximabe e o desenvolvimento do quadro de oclusão de ramo pode indicar um possível efeito adverso da medicação.

A case of a 53 year-old female patient who developed branch retinal vein occlusion after six 3 mg/kg Infliximab infusions for rheumatoid arthritis treatment is reported. Hematological disorders, cardiopathy and chronic systemic hypertension evaluation were negative. The relationship between the infliximab therapy and the development of retinal vein occlusion raises awareness of the possibility of a potential side effect of this medication.

OBJETIVO: Avaliar a resposta inflamatória associada com o uso de pericárdio suíno processado e esclera homóloga preservada em glicerina no recobrimento de tubo de drenagem de silicone utilizado em cirurgia de glaucoma em modelo experimental. MÉTODOS: Oito olhos de 8 coelhos albinos da raça Nova Zelândia receberam enxertos do mesmo tamanho de esclera homóloga, preservada em glicerina ou pericárdio suíno processado, suturados à esclera recobrindo um tubo de silicone. Os olhos foram avaliados quanto à hiperemia conjuntival de modo mascarado na primeira, terceira e sétima semanas de pós-operatório. Após a sétima semana os olhos foram enucleados e submetidos a estudo histopatológico. Os olhos também foram avaliados quanto à presença de afinamento do enxerto, exposição do tubo e quemose. RESULTADOS: Não ocorreram casos de afinamento do enxerto ou exposição do tubo, porém o pericárdio suíno esteve associado clinicamente a uma maior inflamação. Achados à microscopia óptica incluíram intensa reação inflamatória em torno do enxerto de pericárdio com formação de granuloma do tipo corpo estranho. Por outro lado, no grupo que recebeu esclera, ocorreu formação de granulomas apenas em torno dos fios de sutura. CONCLUSÃO: O pericárdio suíno esteve associado a maior inflamação tanto à histopatologia quanto clinicamente, quando usado no recobrimento de tubo de silicone, em comparação à esclera homóloga preservada em glicerina, durante o período de acompanhamento de sete semanas.

PURPOSE: To evaluate the inflammatory response associated with the use of processed porcine pericardium and glycerin-preserved homologous sclera as silicone glaucoma drainage device coverage in a rabbit experimental model. METHODS: Eight New Zealand white rabbits' eyes received an equal-sized glycerin-preserved homologous scleral patch or a double-layered processed porcine pericardium that was sutured to the bare sclera covering a silicone tube. Conjunctival hyperemia was graded using the double-blind method during the immediate postoperative period and during the first, third, and seventh postoperative weeks. After the seventh week, the enucleated eyes were histopathologically examined. They were also evaluated for signs of patch graft melting, tube erosion and chemosis. RESULTS: There was no occurrence of graft melting or tube exposure, although porcine pericardium was associated with greater inflammation through clinical observation. Light microscopy revealed marked inflammation surrounding the porcine pericardium with foreign body granuloma formation. On the other hand, the sclera group presented milder inflammation with foreign body granulomas only around the sutures. CONCLUSIONS: Porcine pericardium is associated with significant inflammation when used as tube coverage in a rabbit model, at both histopathologic and clinical levels, when compared to glycerin-preserved homologous sclera during the seven-week follow-up period.