Is it possible to estimate the number of patients with COVID-19 admitted to intensive care units and general wards using clinical and telemedicine data?

BACKGROUND: Gabaldi et al. utilized telemedicine data, web search trends, hospitalized patient characteristics, and resource usage data to estimate bed occupancy during the COVID-19 pandemic. The results showcase the potential of data-driven strategies to enhance resource allocation decisions for an effective pandemic response. OBJECTIVE: To develop and validate predictive models to estimate the number of COVID-19 patients hospitalized in the intensive care units and general wards of a private not-for-profit hospital in São Paulo, Brazil. METHODS: Two main models were developed. The first model calculated hospital occupation as the difference between predicted COVID-19 patient admissions, transfers between departments, and discharges, estimating admissions based on their weekly moving averages, segmented by general wards and intensive care units. Patient discharge predictions were based on a length of stay predictive model, assessing the clinical characteristics of patients hospitalized with COVID-19, including age group and usage of mechanical ventilation devices. The second model estimated hospital occupation based on the correlation with the number of telemedicine visits by patients diagnosed with COVID-19, utilizing correlational analysis to define the lag that maximized the correlation between the studied series. Both models were monitored for 365 days, from May 20th, 2021, to May 20th, 2022. RESULTS: The first model predicted the number of hospitalized patients by department within an interval of up to 14 days. The second model estimated the total number of hospitalized patients for the following 8 days, considering calls attended by Hospital Israelita Albert Einstein's telemedicine department. Considering the average daily predicted values for the intensive care unit and general ward across a forecast horizon of 8 days, as limited by the second model, the first and second models obtained R² values of 0.900 and 0.996, respectively and mean absolute errors of 8.885 and 2.524 beds, respectively. The performances of both models were monitored using the mean error, mean absolute error, and root mean squared error as a function of the forecast horizon in days. CONCLUSION: The model based on telemedicine use was the most accurate in the current analysis and was used to estimate COVID-19 hospital occupancy 8 days in advance, validating predictions of this nature in similar clinical contexts. The results encourage the expansion of this method to other pathologies, aiming to guarantee the standards of hospital care and conscious consumption of resources. BACKGROUND: Developed models to forecast bed occupancy for up to 14 days and monitored errors for 365 days. BACKGROUND: Telemedicine calls from COVID-19 patients correlated with the number of patients hospitalized in the next 8 days.

Is it possible to estimate the number of patients with COVID-19 admitted to intensive care units and general wards using clinical and telemedicine data?

ABSTRACT Objective: To develop and validate predictive models to estimate the number of COVID-19 patients hospitalized in the intensive care units and general wards of a private not-for-profit hospital in São Paulo, Brazil. Methods: Two main models were developed. The first model calculated hospital occupation as the difference between predicted COVID-19 patient admissions, transfers between departments, and discharges, estimating admissions based on their weekly moving averages, segmented by general wards and intensive care units. Patient discharge predictions were based on a length of stay predictive model, assessing the clinical characteristics of patients hospitalized with COVID-19, including age group and usage of mechanical ventilation devices. The second model estimated hospital occupation based on the correlation with the number of telemedicine visits by patients diagnosed with COVID-19, utilizing correlational analysis to define the lag that maximized the correlation between the studied series. Both models were monitored for 365 days, from May 20th, 2021, to May 20th, 2022. Results: The first model predicted the number of hospitalized patients by department within an interval of up to 14 days. The second model estimated the total number of hospitalized patients for the following 8 days, considering calls attended by Hospital Israelita Albert Einstein's telemedicine department. Considering the average daily predicted values for the intensive care unit and general ward across a forecast horizon of 8 days, as limited by the second model, the first and second models obtained R² values of 0.900 and 0.996, respectively and mean absolute errors of 8.885 and 2.524 beds, respectively. The performances of both models were monitored using the mean error, mean absolute error, and root mean squared error as a function of the forecast horizon in days. Conclusion: The model based on telemedicine use was the most accurate in the current analysis and was used to estimate COVID-19 hospital occupancy 8 days in advance, validating predictions of this nature in similar clinical contexts. The results encourage the expansion of this method to other pathologies, aiming to guarantee the standards of hospital care and conscious consumption of resources.

Longer-term effectiveness of a heterologous coronavirus disease 2019 (COVID-19) vaccine booster in healthcare workers in Brazil.

Objective: To compare the long-term vaccine effectiveness between those receiving viral vector [Oxford-AstraZeneca (ChAdOx1)] or inactivated viral (CoronaVac) primary series (2 doses) and those who received an mRNA booster (Pfizer/BioNTech) (the third dose) among healthcare workers (HCWs). Methods: We conducted a retrospective cohort study among HCWs (aged ≥18 years) in Brazil from January 2021 to July 2022. To assess the variation in the effectiveness of booster dose over time, we estimated the effectiveness rate by taking the log risk ratio as a function of time. Results: Of 14,532 HCWs, coronavirus disease 2019 (COVID-19) was confirmed in 56.3% of HCWs receiving 2 doses of CoronaVac vaccine versus 23.2% of HCWs receiving 2 doses of CoronaVac vaccine with mRNA booster (P < .001), and 37.1% of HCWs receiving 2 doses of ChAdOx1 vaccine versus 22.7% among HCWs receiving 2 doses of ChAdOx1 vaccine with mRNA booster (P < .001). The highest vaccine effectiveness with mRNA booster was observed 30 days after vaccination: 91% for the CoronaVac vaccine group and 97% for the ChAdOx1 vaccine group. Vacine effectiveness declined to 55% and 67%, respectively, at 180 days. Of 430 samples screened for mutations, 49.5% were SARS-CoV-2 delta variants and 34.2% were SARS-CoV-2 omicron variants. Conclusions: Heterologous COVID-19 vaccines were effective for up to 180 days in preventing COVID-19 in the SARS-CoV-2 delta and omicron variant eras, which suggests the need for a second booster.

Clinical characteristics and outcomes of patients with COVID-19 admitted to the intensive care unit during the first and second waves of the pandemic in Brazil: a single-center retrospective cohort study.

OBJECTIVE: To describe and compare the clinical characteristics and outcomes of patients admitted to intensive care units during the first and second waves of the COVID-19 pandemic. METHODS: In this retrospective single-center cohort study, data were retrieved from the Epimed Monitor System; all adult patients admitted to the intensive care unit between March 4, 2020, and October 1, 2021, were included in the study. We compared the clinical characteristics and outcomes of patients admitted to the intensive care unit of a quaternary private hospital in São Paulo, Brazil, during the first (May 1, 2020, to August 31, 2020) and second (March 1, 2021, to June 30, 2021) waves of the COVID-19 pandemic. RESULTS: In total, 1,427 patients with COVID-19 were admitted to the intensive care unit during the first (421 patients) and second (1,006 patients) waves. Compared with the first wave group [median (IQR)], the second wave group was younger [57 (46-70) versus 67 (52-80) years; p<0.001], had a lower SAPS 3 Score [45 (42-52) versus 49 (43-57); p<0.001], lower SOFA Score on intensive care unit admission [3 (1-6) versus 4 (2-6); p=0.018], lower Charlson Comorbidity Index [0 (0-1) versus 1 (0-2); p<0.001], and were less frequently frail (10.4% versus 18.1%; p<0.001). The second wave group used more noninvasive ventilation (81.3% versus 53.4%; p<0.001) and high-flow nasal cannula (63.2% versus 23.0%; p<0.001) during their intensive care unit stay. The intensive care unit (11.3% versus 10.5%; p=0.696) and in-hospital mortality (12.3% versus 12.1%; p=0.998) rates did not differ between both waves. CONCLUSION: In the first and second waves, patients with severe COVID-19 exhibited similar mortality rates and need for invasive organ support, despite the second wave group being younger and less severely ill at the time of intensive care unit admission.

Risk factors for long coronavirus disease 2019 (long COVID) among healthcare personnel, Brazil, 2020-2022.

OBJECTIVE: To determine risk factors for the development of long coronavirus disease 2019 (COVID-19) in healthcare personnel (HCP). METHODS: We conducted a case-control study among HCP who had confirmed symptomatic COVID-19 working in a Brazilian healthcare system between March 1, 2020, and July 15, 2022. Cases were defined as those having long COVID according to the Centers for Disease Control and Prevention definition. Controls were defined as HCP who had documented COVID-19 but did not develop long COVID. Multiple logistic regression was used to assess the association between exposure variables and long COVID during 180 days of follow-up. RESULTS: Of 7,051 HCP diagnosed with COVID-19, 1,933 (27.4%) who developed long COVID were compared to 5,118 (72.6%) who did not. The majority of those with long COVID (51.8%) had 3 or more symptoms. Factors associated with the development of long COVID were female sex (OR, 1.21; 95% CI, 1.05-1.39), age (OR, 1.01; 95% CI, 1.00-1.02), and 2 or more SARS-CoV-2 infections (OR, 1.27; 95% CI, 1.07-1.50). Those infected with the SARS-CoV-2 δ (delta) variant (OR, 0.30; 95% CI, 0.17-0.50) or the SARS-CoV-2 o (omicron) variant (OR, 0.49; 95% CI, 0.30-0.78), and those receiving 4 COVID-19 vaccine doses prior to infection (OR, 0.05; 95% CI, 0.01-0.19) were significantly less likely to develop long COVID. CONCLUSIONS: Long COVID can be prevalent among HCP. Acquiring >1 SARS-CoV-2 infection was a major risk factor for long COVID, while maintenance of immunity via vaccination was highly protective.

Effectiveness of two coronavirus disease 2019 (COVID-19) vaccines (viral vector and inactivated viral vaccine) against severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infection in a cohort of healthcare workers.

OBJECTIVE: We investigated real-world vaccine effectiveness for Oxford-AstraZeneca (ChAdOx1) and CoronaVac against laboratory-confirmed severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infection among healthcare workers (HCWs). METHODS: We conducted a retrospective cohort study among HCWs (aged ≥18 years) working in a private healthcare system in Brazil between January 1, 2021 and August 3, 2021, to assess vaccine effectiveness. We calculated vaccine effectiveness as 1 - rate ratio (RR), with RR determined by adjusting Poisson models with the occurrence of SARS-CoV-2 infection as the outcome and the vaccination status as the main variable. We used the logarithmic link function and simple models adjusting for sex, age, and job types. RESULTS: In total, 13,813 HCWs met the inclusion criteria for this analysis. Among them, 6,385 (46.2%) received the CoronaVac vaccine, 5,916 (42.8%) received the ChAdOx1 vaccine, and 1,512 (11.0%) were not vaccinated. Overall, COVID-19 occurred in 6% of unvaccinated HCWs, 3% of HCWs who received 2 doses of CoronaVac vaccine, and 0.7% of HCWs who received 2 doses of ChAdOx1 vaccine (P < .001). In the adjusted analyses, the estimated vaccine effectiveness rates were 51.3% for CoronaVac, and 88.1% for ChAdOx1 vaccine. Both vaccines reduced the number of hospitalizations, the length of hospital stay, and the need for mechanical ventilation. In addition, 19 SARS-CoV-2 samples from 19 HCWs were screened for mutations of interest. Of 19 samples, 18 were the γ (gamma) variant. CONCLUSIONS: Although both COVID-19 vaccines (viral vector and inactivated virus) can significantly prevent COVID-19 among HCWs, CoronaVac was much less effective. The COVID-19 vaccines were also effective against the dominant γ variant.

Effectiveness of Heterologous Coronavirus Disease 2019 (COVID-19) Vaccine Booster Dosing in Brazilian Healthcare Workers, 2021.

BACKGROUND: Little is currently known about vaccine effectiveness (VE) for either 2 doses of Oxford-AstraZeneca (ChAdOx1) viral vector vaccine or CoronaVac (Instituto Butantan) inactivated viral vaccine followed by a third dose of mRNA vaccine (Pfizer/BioNTech) among healthcare workers (HCWs). METHODS: We conducted a retrospective cohort study among HCWs (aged ≥18 years) working in a private healthcare system in Brazil from January to December 2021. VE was defined as 1 - incidence rate ratio (IRR), with IRR determined using Poisson models with the occurrence of laboratory-confirmed coronavirus disease 2019 (COVID-19) infection as the outcome, adjusting for age, sex, and job type. We compared those receiving viral vector or inactivated viral primary series (2 doses) with those who received an mRNA booster. RESULTS: A total of 11 427 HCWs met the inclusion criteria. COVID-19 was confirmed in 31.5% of HCWs receiving 2 doses of CoronaVac vaccine versus 0.9% of HCWs receiving 2 doses of CoronaVac vaccine with mRNA booster (P < .001) and 9.8% of HCWs receiving 2 doses of ChAdOx1 vaccine versus 1% among HCWs receiving 2 doses of ChAdOx1 vaccine with mRNA booster (P < .001). In the adjusted analyses, the estimated VE was 92.0% for 2 CoronaVac vaccines plus mRNA booster and 60.2% for 2 ChAdOx1 vaccines plus mRNA booster, when compared with those with no mRNA booster. Of 246 samples screened for mutations, 191 (77.6%) were Delta variants. CONCLUSIONS: While 2 doses of ChAdOx1 or CoronaVac vaccines prevent COVID-19, the addition of a Pfizer/BioNTech booster provided significantly more protection.

Prevalence, predictors, and patient-reported outcomes of long COVID in hospitalized and non-hospitalized patients from the city of São Paulo, Brazil.

Background: Robust data comparing long COVID in hospitalized and non-hospitalized patients in middle-income countries are limited. Methods: A retrospective cohort study was conducted in Brazil, including hospitalized and non-hospitalized patients. Long COVID was diagnosed at 90-day follow-up using WHO criteria. Demographic and clinical information, including the depression screening scale (PHQ-2) at day 30, was compared between the groups. If the PHQ-2 score is 3 or greater, major depressive disorder is likely. Logistic regression analysis identified predictors and protective factors for long COVID. Results: A total of 291 hospitalized and 1,118 non-hospitalized patients with COVID-19 were included. The prevalence of long COVID was 47.1% and 49.5%, respectively. Multivariable logistic regression showed female sex (odds ratio [OR] = 4.50, 95% confidence interval (CI) 2.51-8.37), hypertension (OR = 2.90, 95% CI 1.52-5.69), PHQ-2 > 3 (OR = 6.50, 95% CI 1.68-33.4) and corticosteroid use during hospital stay (OR = 2.43, 95% CI 1.20-5.04) as predictors of long COVID in hospitalized patients, while female sex (OR = 2.52, 95% CI 1.95-3.27) and PHQ-2 > 3 (OR = 3.88, 95% CI 2.52-6.16) were predictors in non-hospitalized patients. Conclusion: Long COVID was prevalent in both groups. Positive depression screening at day 30 post-infection can predict long COVID. Early screening of depression helps health staff to identify patients at a higher risk of long COVID, allowing an early diagnosis of the condition.

Clinical characteristics and outcomes of patients with COVID-19 admitted to the intensive care unit during the first and second waves of the pandemic in Brazil: a single-center retrospective cohort study

ABSTRACT Objective To describe and compare the clinical characteristics and outcomes of patients admitted to intensive care units during the first and second waves of the COVID-19 pandemic. Methods In this retrospective single-center cohort study, data were retrieved from the Epimed Monitor System; all adult patients admitted to the intensive care unit between March 4, 2020, and October 1, 2021, were included in the study. We compared the clinical characteristics and outcomes of patients admitted to the intensive care unit of a quaternary private hospital in São Paulo, Brazil, during the first (May 1, 2020, to August 31, 2020) and second (March 1, 2021, to June 30, 2021) waves of the COVID-19 pandemic. Results In total, 1,427 patients with COVID-19 were admitted to the intensive care unit during the first (421 patients) and second (1,006 patients) waves. Compared with the first wave group [median (IQR)], the second wave group was younger [57 (46-70) versus 67 (52-80) years; p<0.001], had a lower SAPS 3 Score [45 (42-52) versus 49 (43-57); p<0.001], lower SOFA Score on intensive care unit admission [3 (1-6) versus 4 (2-6); p=0.018], lower Charlson Comorbidity Index [0 (0-1) versus 1 (0-2); p<0.001], and were less frequently frail (10.4% versus 18.1%; p<0.001). The second wave group used more noninvasive ventilation (81.3% versus 53.4%; p<0.001) and high-flow nasal cannula (63.2% versus 23.0%; p<0.001) during their intensive care unit stay. The intensive care unit (11.3% versus 10.5%; p=0.696) and in-hospital mortality (12.3% versus 12.1%; p=0.998) rates did not differ between both waves. Conclusion In the first and second waves, patients with severe COVID-19 exhibited similar mortality rates and need for invasive organ support, despite the second wave group being younger and less severely ill at the time of intensive care unit admission.

Clinical characteristics and outcomes of COVID-19 patients admitted to the intensive care unit during the first year of the pandemic in Brazil: a single center retrospective cohort study.

OBJECTIVE: To describe clinical characteristics, resource use, outcomes, and to identify predictors of in-hospital mortality of patients with COVID-19 admitted to the intensive care unit. METHODS: Retrospective single-center cohort study conducted at a private hospital in São Paulo (SP), Brazil. All consecutive adult (≥18 years) patients admitted to the intensive care unit, between March 4, 2020 and February 28, 2021 were included in this study. Patients were categorized between survivors and non-survivors according to hospital discharge. RESULTS: During the study period, 1,296 patients [median (interquartile range) age: 66 (53-77) years] with COVID-19 were admitted to the intensive care unit. Out of those, 170 (13.6%) died at hospital (non-survivors) and 1,078 (86.4%) were discharged (survivors). Compared to survivors, non-survivors were older [80 (70-88) versus 63 (50-74) years; p<0.001], had a higher Simplified Acute Physiology Score 3 [59 (54-66) versus 47 (42-53) points; p<0.001], and presented comorbidities more frequently. During the intensive care unit stay, 56.6% of patients received noninvasive ventilation, 32.9% received mechanical ventilation, 31.3% used high flow nasal cannula, 11.7% received renal replacement therapy, and 1.5% used extracorporeal membrane oxygenation. Independent predictors of in-hospital mortality included age, Sequential Organ Failure Assessment score, Charlson Comorbidity Index, need for mechanical ventilation, high flow nasal cannula, renal replacement therapy, and extracorporeal membrane oxygenation support. CONCLUSION: Patients with severe COVID-19 admitted to the intensive care unit exhibited a considerable morbidity and mortality, demanding substantial organ support, and prolonged intensive care unit and hospital stay.

Impact of the COVID-19 pandemic on emergency department visits: experience of a Brazilian reference center.

OBJECTIVE: To analyze the impact of COVID-19 on emergency department metrics at a large tertiary reference hospital in Brazil. METHODS: A retrospective analysis of consecutive emergency department visits, from January 1, 2020, to November 21, 2020, was performed and compared to the corresponding time frame in 2018 and 2019. The volume of visits and patients' demographic and clinic characteristics were compared. All medical conditions were included, except confirmed cases of COVID-19. RESULTS: A total of 138,138 emergency department visits occurred during the study period, with a statistically significant (p<0.01) reduction by 52% compared to both 2018 and 2019. This decrease was more pronounced for pediatric visits - a drop by 71% in comparison to previous years. Regarding clinical presentation, there was a decrease of severe cases by 34.7% and 37.6%, whereas mild cases decreased by 55.2% and 56.2% when comparing 2020 to 2018 and 2019, respectively. A 30% fall in the total volume of hospital admission from emergency department patients was observed during the study period, but accompanied by a proportional increase in monthly admission rates since April 2020. CONCLUSION: The COVID-19 pandemic led to a 52% fall in attendance at our emergency department for other conditions, along with a proportional increase in hospital admission rates of COVID-19 patients. Healthcare providers should raise patient awareness not to delay seeking medical treatment of severe conditions that require care at the emergency department.

Clinical characteristics and outcomes of COVID-19 patients admitted to the intensive care unit during the first year of the pandemic in Brazil: a single center retrospective cohort study / Características clínicas e desfechos de pacientes com COVID-19 admitidos em unidade de terapia intensiva durante o primeiro ano de pandemia no Brasil: um estudo de coorte retrospectivo em centro único

ABSTRACT Objective: To describe clinical characteristics, resource use, outcomes, and to identify predictors of in-hospital mortality of patients with COVID-19 admitted to the intensive care unit. Methods: Retrospective single-center cohort study conducted at a private hospital in São Paulo (SP), Brazil. All consecutive adult (≥18 years) patients admitted to the intensive care unit, between March 4, 2020 and February 28, 2021 were included in this study. Patients were categorized between survivors and non-survivors according to hospital discharge. Results: During the study period, 1,296 patients [median (interquartile range) age: 66 (53-77) years] with COVID-19 were admitted to the intensive care unit. Out of those, 170 (13.6%) died at hospital (non-survivors) and 1,078 (86.4%) were discharged (survivors). Compared to survivors, non-survivors were older [80 (70-88) versus 63 (50-74) years; p<0.001], had a higher Simplified Acute Physiology Score 3 [59 (54-66) versus 47 (42-53) points; p<0.001], and presented comorbidities more frequently. During the intensive care unit stay, 56.6% of patients received noninvasive ventilation, 32.9% received mechanical ventilation, 31.3% used high flow nasal cannula, 11.7% received renal replacement therapy, and 1.5% used extracorporeal membrane oxygenation. Independent predictors of in-hospital mortality included age, Sequential Organ Failure Assessment score, Charlson Comorbidity Index, need for mechanical ventilation, high flow nasal cannula, renal replacement therapy, and extracorporeal membrane oxygenation support. Conclusion: Patients with severe COVID-19 admitted to the intensive care unit exhibited a considerable morbidity and mortality, demanding substantial organ support, and prolonged intensive care unit and hospital stay.

RESUMO Objetivo: Descrever características clínicas, uso de recursos e desfechos e identificar preditores de mortalidade intra-hospitalar de pacientes com COVID-19 admitidos na unidade de terapia intensiva. Métodos: Estudo de coorte retrospectivo, em centro único, realizado em um hospital privado localizado em São Paulo (SP). Pacientes adultos (≥18 anos) admitidos consecutivamente na unidade de terapia intensiva, entre 4 de março de 2020 a 28 de fevereiro de 2021, foram incluídos neste estudo. Os pacientes foram classificados como sobreviventes e não sobreviventes, de acordo com a alta hospitalar. Resultados: Durante o período do estudo, 1.296 pacientes [mediana (intervalo interquartil) de idade: 66 (53-77) anos] com COVID-19 foram admitidos na unidade de terapia intensiva. Destes, 170 (13,6%) pacientes morreram no hospital (não sobreviventes), e 1.078 (86,4%) receberam alta hospitalar (sobreviventes). Comparados aos sobreviventes, os não sobreviventes eram mais idosos [80 (70-88) versus 63 (50-74) anos; p<0,001], apresentavam pontuação mais alta no sistema prognóstico Simplified Acute Physiology Score 3 [59 (54-66) versus 47 (42-53); pontos p<0,001] e tinham mais comorbidades. Durante a internação na unidade de terapia intensiva, 56,6% dos pacientes usaram ventilação não invasiva, 32,9% usaram ventilação mecânica invasiva, 31,3% usaram cateter nasal de alto fluxo, 11,7% foram submetidos à terapia renal substitutiva, e 1,5% usou oxigenação por membrana extracorpórea. Os preditores independentes de mortalidade intra-hospitalar foram idade, Sequential Organ Failure Assessment, Índice de Comorbidade de Charlson, necessidade de ventilação mecânica, uso de cateter nasal de alto fluxo, uso de terapia renal substitutiva e suporte por oxigenação por membrana extracorpórea. Conclusão: Pacientes com quadros graves da COVID-19 admitidos na unidade de terapia intensiva apresentaram considerável mortalidade e morbidade, com alta demanda de terapia de suporte e internação prolongada em unidade de terapia intensiva e hospitalar.

Impact of COVID-19 pandemic on care of oncological patients: experience of a cancer center in a Latin American pandemic epicenter / Impacto da COVID-19 sobre o atendimento de pacientes oncológicos: experiência de um centro oncológico localizado em um epicentro Latino-Americano da pandemia

ABSTRACT Objective Since the rising of coronavirus disease 2019 (COVID-19) pandemic, there is uncertainty regarding the impact of transmission to cancer patients. Evidence on increased severity for patients undergoing antineoplastic treatment is posed against deferring oncologic treatment. We aimed to evaluate the impact of COVID-19 pandemic on patient volumes in a cancer center in an epicenter of the pandemic. Methods Outpatient and inpatient volumes were extracted from electronic health record database. Two intervals were compared: pre-COVID-19 (March to May 2019) and COVID-19 pandemic (March to May 2020) periods. Results The total number of medical appointments declined by 45% in the COVID-19 period, including a 56.2% decrease in new visits. There was a 27.5% reduction in the number of patients undergoing intravenous systemic treatment and a 57.4% decline in initiation of new treatments. Conversely, there was an increase by 309% in new patients undergoing oral chemotherapy regimens and a 5.9% rise in new patients submitted to radiation therapy in the COVID-19 period. There was a 51.2% decline in length of stay and a 60% reduction in the volume of surgical cases during COVID-19. In the stem cell transplant unit, we observed a reduction by 36.5% in length of stay and a 62.5% drop in stem cell transplants. Conclusion A significant decrease in the number of patients undergoing cancer treatment was observed after COVID-19 pandemic. Although this may be partially overcome by alternative therapeutic options, avoiding timely health care due to fear of getting COVID-19 infection might impact on clinical outcomes. Our findings may help support immediate actions to mitigate this hypothesis.

RESUMO Objetivo Desde o surgimento da pandemia da doença pelo coronavírus 2019 (COVID-19), há incerteza quanto ao impacto da transmissão para pacientes com câncer. As evidências sobre o aumento da gravidade para pacientes submetidos a tratamento antineoplásico são contra o adiamento do tratamento oncológico. Nosso objetivo foi avaliar o impacto da pandemia de COVID-19 em volumes de pacientes em um centro oncológico, em um epicentro da pandemia. Métodos Os volumes de pacientes ambulatoriais e de internação foram extraídos do banco de dados de prontuários eletrônicos. Dois intervalos foram comparados: períodos pré-COVID-19 (março a maio de 2019) e pandemia COVID-19 (março a maio de 2020). Resultados O número total de consultas médicas diminuiu 45% no período pandemia COVID-19, inclusive com redução de 56,2% nas novas consultas. Houve redução de 27,5% no número de pacientes em tratamento sistêmico intravenoso e de 57,4% no início de novos tratamentos. Por outro lado, ocorreram aumento de 309% em novos pacientes submetidos a regimes de quimioterapia oral e elevação de 5,9% em novos pacientes submetidos à radioterapia no período pandemia COVID-19. Observaram-se queda de 51,2% nos dias de internação e redução de 60% no volume de casos cirúrgicos durante a COVID-19. Na unidade de transplante de células-tronco, a redução foi de 36,5% nos dias de internação e de 62,5% nos transplantes de células-tronco. Conclusão Foi observado declínio significativo no número de pacientes em tratamento de câncer após a pandemia de COVID-19. Embora isso possa ser parcialmente superado por opções terapêuticas alternativas, evitar cuidados de saúde oportunos devido ao medo de contrair COVID-19 pode impactar nos resultados clínicos. Nossos resultados podem ajudar a apoiar ações imediatas para mitigar essa hipótese.

Impact of the COVID-19 pandemic on emergency department visits: experience of a Brazilian reference center / Impacto da pandemia da COVID-19 no volume de atendimentos no pronto atendimento: experiência de um centro de referência no Brasil

ABSTRACT Objective To analyze the impact of COVID-19 on emergency department metrics at a large tertiary reference hospital in Brazil. Methods A retrospective analysis of consecutive emergency department visits, from January 1, 2020, to November 21, 2020, was performed and compared to the corresponding time frame in 2018 and 2019. The volume of visits and patients' demographic and clinic characteristics were compared. All medical conditions were included, except confirmed cases of COVID-19. Results A total of 138,138 emergency department visits occurred during the study period, with a statistically significant (p<0.01) reduction by 52% compared to both 2018 and 2019. This decrease was more pronounced for pediatric visits - a drop by 71% in comparison to previous years. Regarding clinical presentation, there was a decrease of severe cases by 34.7% and 37.6%, whereas mild cases decreased by 55.2% and 56.2% when comparing 2020 to 2018 and 2019, respectively. A 30% fall in the total volume of hospital admission from emergency department patients was observed during the study period, but accompanied by a proportional increase in monthly admission rates since April 2020. Conclusion The COVID-19 pandemic led to a 52% fall in attendance at our emergency department for other conditions, along with a proportional increase in hospital admission rates of COVID-19 patients. Healthcare providers should raise patient awareness not to delay seeking medical treatment of severe conditions that require care at the emergency department.

RESUMO Objetivo Analisar o impacto da pandemia da COVID-19 nas métricas do pronto atendimento de um hospital terciário de referência no Brasil. Métodos Uma análise retrospectiva das visitas consecutivas ao pronto atendimento, de 1o de janeiro de 2020 a 21 de novembro de 2020, foi realizada e comparada ao mesmo intervalo nos anos de 2018 e 2019. O volume de atendimentos e as características clínicas e demográficas dos pacientes foram comparados. Todos os diagnósticos foram incluídos, exceto os casos confirmados de COVID-19. Resultados Um total de 138.138 visitas ao pronto atendimento ocorreu durante o período do estudo, com redução estatisticamente significativa (p<0,01) de 52% do volume comparado tanto a 2018 como a 2019. Essa queda foi mais pronunciada nos atendimentos de pediatria, com redução de 71% se comparada aos números de anos anteriores. Em relação ao quadro clínico, houve redução dos casos graves em 34,7% e 37,6%, enquanto os casos leves caíram 55,2% e 56,2%, quando comparado 2020 a 2018 e a 2019, respectivamente. Uma queda de 30% foi vista no volume de admissões hospitalares originadas dessas visitas, porém houve aumento percentual da taxa de admissão mensal em relação ao volume desde abril de 2020. Conclusão O impacto da pandemia da COVID-19 gerou redução de 52% no volume de atendimento do pronto atendimento por outras condições clínicas, bem como aumento proporcional na taxa de admissão hospitalar de pacientes com COVID-19. Os profissionais de saúde devem orientar seus pacientes a não atrasar a procura por atendimento médico de condições graves que precisem de cuidados no pronto atendimento.

Impact of COVID-19 pandemic on care of oncological patients: experience of a cancer center in a Latin American pandemic epicenter.

OBJECTIVE: Since the rising of coronavirus disease 2019 (COVID-19) pandemic, there is uncertainty regarding the impact of transmission to cancer patients. Evidence on increased severity for patients undergoing antineoplastic treatment is posed against deferring oncologic treatment. We aimed to evaluate the impact of COVID-19 pandemic on patient volumes in a cancer center in an epicenter of the pandemic. METHODS: Outpatient and inpatient volumes were extracted from electronic health record database. Two intervals were compared: pre-COVID-19 (March to May 2019) and COVID-19 pandemic (March to May 2020) periods. RESULTS: The total number of medical appointments declined by 45% in the COVID-19 period, including a 56.2% decrease in new visits. There was a 27.5% reduction in the number of patients undergoing intravenous systemic treatment and a 57.4% decline in initiation of new treatments. Conversely, there was an increase by 309% in new patients undergoing oral chemotherapy regimens and a 5.9% rise in new patients submitted to radiation therapy in the COVID-19 period. There was a 51.2% decline in length of stay and a 60% reduction in the volume of surgical cases during COVID-19. In the stem cell transplant unit, we observed a reduction by 36.5% in length of stay and a 62.5% drop in stem cell transplants. CONCLUSION: A significant decrease in the number of patients undergoing cancer treatment was observed after COVID-19 pandemic. Although this may be partially overcome by alternative therapeutic options, avoiding timely health care due to fear of getting COVID-19 infection might impact on clinical outcomes. Our findings may help support immediate actions to mitigate this hypothesis.

Epidemiologic and clinical features of patients with COVID-19 in Brazil.

Objective This study describes epidemiological and clinical features of patients with confirmed infection by SARS-CoV-2 diagnosed and treated at Hospital Israelita Albert Einstein , which admitted the first patients with this condition in Brazil. Methods In this retrospective, single-center study, we included all laboratory confirmed COVID-19 cases at Hospital Israelita Albert Einstein , São Paulo, Brazil, from February until March 2020. Demographic, clinical, laboratory and radiological data were analyzed. Results A total of 510 patients with a confirmed diagnosis of COVID-19 were included in this study. Most patients were male (56.9%) with a mean age of 40 years. A history of a close contact with a positive/suspected case was reported by 61.1% of patients and 34.4% had a history of recent international travel. The most common symptoms upon presentation were fever (67.5%), nasal congestion (42.4%), cough (41.6%) and myalgia/arthralgia (36.3%). Chest computed tomography was performed in 78 (15.3%) patients, and 93.6% of those showed abnormal results. Hospitalization was required for 72 (14%) patients and 20 (27.8%) were admitted to the Intensive Care Unit. Regarding clinical treatment, the most often used medicines were intravenous antibiotics (84.7%), chloroquine (45.8%) and oseltamivir (31.9%). Invasive mechanical ventilation was required by 65% of Intensive Care Unit patients. The mean length of stay was 9 days for all patients (22 and 7 days for patients requiring or not intensive care, respectively). Only one patient (1.38%) died during follow-up. Conclusion These results may be relevant for Brazil and other countries with similar characteristics, which are starting to deal with this pandemic.

Epidemiologic and clinical features of patients with COVID-19 in Brazil / Características epidemiológicas e clínicas dos pacientes com COVID-19 no Brasil

ABSTRACT Objective This study describes epidemiological and clinical features of patients with confirmed infection by SARS-CoV-2 diagnosed and treated at Hospital Israelita Albert Einstein , which admitted the first patients with this condition in Brazil. Methods In this retrospective, single-center study, we included all laboratory confirmed COVID-19 cases at Hospital Israelita Albert Einstein , São Paulo, Brazil, from February until March 2020. Demographic, clinical, laboratory and radiological data were analyzed. Results A total of 510 patients with a confirmed diagnosis of COVID-19 were included in this study. Most patients were male (56.9%) with a mean age of 40 years. A history of a close contact with a positive/suspected case was reported by 61.1% of patients and 34.4% had a history of recent international travel. The most common symptoms upon presentation were fever (67.5%), nasal congestion (42.4%), cough (41.6%) and myalgia/arthralgia (36.3%). Chest computed tomography was performed in 78 (15.3%) patients, and 93.6% of those showed abnormal results. Hospitalization was required for 72 (14%) patients and 20 (27.8%) were admitted to the Intensive Care Unit. Regarding clinical treatment, the most often used medicines were intravenous antibiotics (84.7%), chloroquine (45.8%) and oseltamivir (31.9%). Invasive mechanical ventilation was required by 65% of Intensive Care Unit patients. The mean length of stay was 9 days for all patients (22 and 7 days for patients requiring or not intensive care, respectively). Only one patient (1.38%) died during follow-up. Conclusion These results may be relevant for Brazil and other countries with similar characteristics, which are starting to deal with this pandemic.

RESUMO Objetivo Descrever as características epidemiológicas e clínicas de pacientes com infecção confirmada pelo SARS-CoV-2, diagnosticados e tratados no Hospital Israelita Albert Einstein, que admitiu os primeiros pacientes com essa condição no Brasil. Métodos Neste estudo retrospectivo, de centro único, incluímos todos os casos com confirmação laboratorial de COVID-19 no Hospital Israelita Albert Einstein, em São Paulo (SP) de fevereiro a março de 2020. Foram analisados dados demográficos, clínicos, laboratoriais e radiológicos. Resultados Foram incluídos 510 pacientes com diagnóstico confirmado de COVID-19. A maioria dos pacientes era do sexo masculino (56,9%), com média de idade de 40 anos. Foi relatada história de contato próximo com um caso positivo/suspeito por 61,1% dos pacientes, e 34,4% tinham história de viagens internacionais recentes. Os sintomas mais comuns foram febre (67,5%), congestão nasal (42,4%), tosse (41,6%) e mialgia/artralgia (36,3%). A tomografia computadorizada de tórax foi realizada em 78 (15,3%) pacientes, e 93,6% deles apresentaram resultados anormais. A hospitalização foi necessária para 72 (14%) pacientes, e 20 (27,8%) foram admitidos na Unidade de Terapia Intensiva. Quanto ao tratamento clínico, os medicamentos mais utilizados foram antibióticos intravenosos (84,7%), cloroquina (45,8%) e oseltamivir (31,9%). A ventilação mecânica invasiva foi necessária em 65% dos pacientes na Unidade de Terapia Intensiva. O tempo médio de internação foi 9 dias para todos os pacientes (22 e 7 dias para pacientes que necessitaram ou não de cuidados intensivos, respectivamente). Apenas um (1,38%) paciente morreu durante o acompanhamento. Conclusão Estes resultados podem ser relevantes para o Brasil e outros países com características semelhantes, que começaram a lidar com essa pandemia.