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Introduction: To describe patients´ characteristics of confirmed COVID-19 with mild symptoms discharged home from the Emergency Department (ED) and followed using telemedicine, to estimate ED-readmission rates and hospitalization, and to explore associated factors with these clinical outcomes. Methods: We performed a retrospective cohort study in Hospital Italiano de Buenos Aires from June to August 2020, which included patients with mild COVID-19 symptoms, diagnosed with a positive result. Follow-up occurred from discharged until EDreadmission or 14 days. We estimate cumulative incidence using the Kaplan-Meier model and associated factors using logistic regression. Results: We included 1,239 patients, with a median of 41 years and 53.82% male. A total of 167 patients were readmitted to the ED within 14 days, with a global incidence rate of 13.08% (95%CI 11.32-15.08). Of these, 83 required hospitalization (median time from diagnosis 4.98 days), 5.98% was not related to any COVID19 complication, and five patients died. After adjustment by confounders (age ≥65, sex, diabetes, hypertension, former smoking, active smoking, fever, diarrhea, and oxygen saturation), we found significant associations: former smoking (adjusted OR 2.09, 95% CI 1.31- 3.34, p0 .002), fever (aOR 1.56, 95% CI 1.07-2.28, p0.002) and oxygen saturation (aOR 0.82, 95% CI 0.71-0.95, p0.009). Conclusion: The 13% rate of ED-readmission during 14 days of follow-up of mild symptomatic COVID-19 patients initially managed as outpatients with telehealth is highly significant in hospital management, quality performance, and patient safety. Introducción: Describir las características de los pacientes COVID-19 con síntomas leves dados de alta desde la Central de Emergencias de Adultos (CEA) y seguidos en forma ambulatoria mediante telemedicina. Estimar las tasas de re-consulta a CEA y hospitalización, y explorar los factores asociados a estos desenlaces. Métodos: Cohorte retrospectiva de Junio a Agosto 2020 en el Hospital Italiano de Buenos Aires, que incluyó personas COVID-19 con síntomas leves. Se siguieron durante 14 días hasta la ocurrencia de re-consulta en CEA y/o hospitalización. Se utilizaron modelos de Kaplan-Meier y regresión logística. Resultados: De un total de 1.239 pacientes, con una mediana de 41 años y 53,82% varones, 167 pacientes reconsultaron a CEA, con una tasa de incidencia global a los 14 días del 13,08% (IC del 95% 11,32 a 15,08). De estos, 83 requirieron hospitalización (media de 4,98 días), el 6% no se relaciona con COVID-19 y 5 pacientes fallecieron. Después del ajuste por factores confundidores (edad ≥65, sexo, diabetes, hipertensión, ex tabaquismo, tabaquismo activo, fiebre, diarrea y saturación de oxígeno), encontramos asociaciones significativas: tabaquismo anterior (ORa 2,09, IC95% 1,31-3,34, p0=0,002), fiebre (ORa 1,56, IC95% 1,07-2,28, p=0,002) y saturación de oxígeno (ORa 0,82, IC95% 0,71-0,95, p=0,009). Conclusión: La tasa del 13% de re-consulta a CEA durante 14 días de seguimiento resultó muy significativa para la gestión hospitalaria, la calidad del desempeño y la seguridad del paciente. Introdução: Descrever as características dos pacientes com COVID-19 com sintomas leves e alta do Centro de Emergência de Adultos (CEA) e acompanhados ambulatorialmente por telemedicina. Estime as taxas de nova consulta ao CEA e de hospitalização e explore os fatores associados a esses resultados. Métodos: Coorte retrospectiva de junho a agosto de 2020 no Hospital Italiano de Buenos Aires, que incluiu COVID-19 com sintomas leves. Eles foram acompanhados por 14 dias até a ocorrência de nova consulta no CEA e / ou internação. Modelos de Kaplan-Meier e regressão logística foram usados. Resultados: De um total de 1.239 pacientes, com mediana de 41 anos e 53,82% homens, 167 pacientes consultaram novamente o CEA, com uma taxa de incidência global em 14 dias de 13,08% (IC95% 11,32 a 15,08). Destes, 83 necessitaram de hospitalização (média de 4,98 dias), 6% não estavam relacionados com COVID-19 e 5 pacientes morreram. Após o ajuste para fatores de confusão (idade ≥65, sexo, diabetes, hipertensão, ex-tabagismo, tabagismo ativo, febre, diarreia e saturação de oxigênio), encontramos associações significativas: tabagismo prévio (ORa 2,09, IC 95% 1,31-3,34, p0 = 0,002), febre (ORa 1,56, IC 95% 1,07-2,28, p = 0,002) e saturação de oxigênio (ORa 0,82, IC 95% 0,71-0,95, p = 0,009). Conclusão: A taxa de 13% de re-consulta ao CEA durante 14 dias de seguimento foi muito significativa para a gestão hospitalar, qualidade do desempenho e segurança do paciente. Fil: Pedretti, Ana. Hospital Italiano. Departamento de Medicina.; Argentina Fil: Márquez Fosser, Santiago. McGill University; Canadá. Hospital Italiano; Argentina Fil: Pasquinelli, Rosario. Hospital Italiano. Departamento de Medicina.; Argentina Fil: Vallone, Marcelo. Hospital Italiano. Departamento de Medicina.; Argentina Fil: Plazzotta, Fernando. Hospital Italiano; Argentina Fil: Luna, Daniel Roberto. Hospital Italiano; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Medicina Traslacional e Ingeniería Biomédica - Hospital Italiano. Instituto de Medicina Traslacional e Ingeniería Biomédica.- Instituto Universitario Hospital Italiano de Buenos Aires. Instituto de Medicina Traslacional e Ingeniería Biomédica; Argentina Fil: Martínez, Bernardo. Hospital Italiano. Departamento de Medicina.; Argentina Fil: Rodriguez, Paz. Hospital Italiano; Argentina Fil: Grande Ratti, María Florencia. Hospital Italiano; Argentina

Crowding in Emergency Departments (ED), results from the imbalance between the simultaneous demand for health care and the ability of the system to respond. The NEDOCS scale (National Emergency Department Crowding Scale) measures the degree of crowding in an ED. Aim: To describe ED Crowding characteristics, using the NEDOCS scale, in an Argentinean hospital. Material and Methods: A retrospective cohort study was conducted with all adult patient consultations between July 2013 and July 2014 at the ED of Hospital Italiano de Buenos Aires. We included all hours in the analysis period (365 days x 24 h = 8,760). The NEDOCS value was calculated for each hour using an automatic algorithm and was quantified in a six points score. Levels 4 (overcrowded), 5 (severely overcrowded) and 6 (dangerously overcrowded) were defined as overcrowding. Contour plots analysis was applied to identify patterns. Results: During the study period, 124,758 visits to the ED were registered. Overcrowding was present in 57.7% (5,055) of the analyzed hours. A predominance of scores between four and five was observed between 10:00 and 24:00 hours. The months with predominance of overcrowding were June, July and August (southern winter). Conclusions: The calculation of the NEDOCS score and the analysis of its temporal distribution are highly relevant to identify opportunities for improvement and to develop mechanisms to prevent the highest categories of overcrowding