ABSTRACT Objective To calculate the positive likelihood ratio to determine whether telemedicine is able to optimize referral to the emergency department. Methods Unicenter study with 182 consecutive patients admitted to Hospital Israelita Albert Einstein due to respiratory symptoms. All patients were submitted to oxygen saturation measurement using the standard method Welch Allyn finger device vital sign monitor and a 2-minute evaluation (Binah.ai mobile application). The reproducibility of oxygen saturation measurements made with both methods was investigated using interclass correlation coefficients and analysis of dispersion. Bland-Altman plots were constructed and kappa concordance coefficients used to examine data normality. Accuracy was also estimated. Results Oxygen saturation measurement differences between methods were ≤2% in more than 85% of cases. The mean difference (bias) between methods was near zero (0.835; Bland-Altman analysis). Oxygen saturation measurements made using the Binah.ai mobile application had an average ability to detect patients with altered oxygen saturation levels compared to the conventional method (ROC analysis). The positive likelihood ratio of the mobile application was 6.23. Conclusion Mobile applications for oxygen saturation measurement are accessible user-friendly tools with moderate impact on clinical telemedicine evaluation of patients with respiratory symptoms, and may optimize referral to the emergency department.

ABSTRACT Chest pain is a frequent, potentially life-threatening condition in the emergency department and requires immediate investigation and treatment. This case report highlights a rare differential diagnosis of pleuritic chest pain: epipericardial fat necrosis. A 29-year-old man presented with normal clinical evaluation, electrocardiography, point-of-care ultrasound, and unremarkable laboratory tests. The initial hypothesis was acute pleuritis. Chest radiography revealed peri-cardiac nonspecific findings, and computed tomography revealed epicardial fat necrosis. Despite the rarity of this condition, accurate diagnosis allows for better practices. An algorithm for a diagnostic approach is proposed.

ABSTRACT Objective To analyze telemedicine diagnostic accuracy in patients with respiratory infections during COVID-19 pandemic compared to face-to-face evaluation in the emergency department. Methods Randomized, unicentric study between September 2020 and November 2020 in patients with any respiratory symptom (exclusion criteria: age >65 years, chronic heart or lung diseases, immunosuppressed). Patients were randomized 1:1 for brief telemedicine followed by face-to-face consultation or direct face-to-face evaluation. The primary endpoint was the International Classification of Diseases code. The secondary analysis comprised length of stay, diagnostic test ordering, medical prescription, and proposed destination. Results Ninety-eight patients were enrolled. The mean age was 36.3±9.7 years old, 57.1% were women, and 81.6% had diagnostic test ordered. Mean grouped by International Classification of Diseases code for upper respiratory tract infection, pharyngotonsillitis, and sinusitis showed no difference between study groups or secondary endpoints. The Telemedicine Group was representative of the population usually evaluated in this center. In the Telemedicine Group (n=48), 18.7% patients would be referred for evaluation at the emergency department. The distribution of diagnoses by telemedicine was 67.4% for upper respiratory tract infection, 2.3% for pharyngotonsillitis, and 0% for sinusitis, being statistically similar to the subsequent face-to-face assessment, respectively: 72.1%, 11.6% and 7% (Kappa 0.386 [95%CI: 0.112-0.66]; p=0.536). Telemedicine ordered COVID-19 molecular (RT-PCR) tests in 76.5% versus 79.4% in face-to-face evaluation (Kappa 0.715 [95%CI: 0.413-1]; p>0.999). Conclusion Diagnostic telemedicine consultation of low-risk patients with acute respiratory symptoms is not inferior to face-to-face evaluation at emergency department. Telemedicine is to be reinforced in the health care system as a strategy for the initial assessment of acute patients. ClinicalTrials.gov Identifier: NCT04806477

RESUMO Objetivo: Caracterizar as variáveis associadas ao encaminhamento à emergência após consulta de Telemedicina durante a pandemia de COVID-19. Métodos: Estudo transversal e retrospectivo, realizado entre março e maio de 2020, com amostra de 500 pacientes adultos. O critério de inclusão foi apresentação de sintomas respiratórios, independente do tipo. Resultados: A média de idade dos pacientes foi de 34,7±10,5 anos, e 59% eram do sexo feminino. A maioria dos pacientes (62,6%) se classificou subjetivamente como tendo um mal-estar, e alguns (41,4%) autodiagnosticaram COVID-19. Tosse (74,4%), rinorreia (65,6%), dor de garganta (38,6%) e espirros (20,6%) foram os sintomas mais comuns relacionados à infecção. Dispneia e dor torácica foram relatados por 29,4% e 16% dos pacientes, respectivamente. Foi calculado o escore de Roth de um número considerável de pacientes (67,6%), obtendo resultado normal em 83,5%, moderadamente alterado em 10,7% e grave em 5,6%. A percentagem de casos suspeitos de COVID-19 foi de 67,6%, e 75% desses foram gerenciados remotamente, com apenas um quarto sendo encaminhado para avaliação imediata na emergência. Conclusão: A avaliação da Telemedicina está associada à reclassificação da impressão subjetiva do paciente, melhor inspeção da COVI-19 e identificação de pacientes de risco. O encaminhamento é otimizado, para evitar avaliação presencial inadequada, e permite que os pacientes de baixo risco sejam orientados de forma apropriada. A Telemedicina deve ser implementada no sistema de saúde como estratégia com boa relação custo-efetividade para a avaliação inicial de pacientes agudos.

ABSTRACT Objective: To characterize variables associated with referral to the emergency department following Telemedicine consultation during the COVID-19 pandemic. Methods: Cross-sectional retrospective study conducted between March and May 2020, with a sample of 500 adult patients. The inclusion criterion was the manifestation of respiratory symptoms, regardless of type. Results: The mean age of patients was 34.7±10.5 years, and 59% were women. Most patients (62.6%) perceived their own health status as malaise and some (41.4%) self-diagnosed COVID-19. Cough (74.4%), rhinorrhea (65.6%), sore throat (38.6%) and sneezing (20.6%) were the most common infection-related symptoms. Overall, 29.4% and 16% of patients reported dyspnea and chest pain, respectively. The Roth score was calculated for a sizeable number of patients (67.6%) and was normal, moderately altered or severely altered in 83.5%, 10.7% and 5.6% of patients, respectively. The percentage of suspected COVID-19 cases was 67.6%. Of these, 75% were managed remotely and only one quarter referred for emergency assessment. Conclusion: Telemedicine assessment is associated with reclassification of patient's subjective impression, better inspection of coronavirus disease 2019 and identification of risk patients. Referral is therefore optimized to avoid inappropriate in-person assessment, and low-risk patients can be properly guided. Telemedicine should be implemented in the health care system as a cost-effective strategy for initial assessment of acute patients.