Tempo de espera para internação com síndrome respiratória aguda grave por COVID-19 na rede de urgência e emergência e óbito hospitalar: coorte retrospectiva
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2023-04-24
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Universidade Estadual Paulista (Unesp)
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Introdução: no Brasil, durante a segunda onda da pandemia COVID-19, houve escassez de leitos hospitalares para transferir doentes, sobrecarregando serviços da Rede de Urgência e Emergência (RUE), principalmente com aqueles com Síndrome Respiratória Aguda Grave (SRAG). Conjectura-se esse tempo de espera ter influenciado no desfecho óbito hospitalar, contudo não há consenso na literatura, sobre o risco acumulado por dia de espera nos serviços de urgência e emergência, assim como o tempo que maximizou o risco de óbito hospitalar desse paciente. Objetivo: investigar associação entre o desfecho óbito hospitalar e o tempo de espera na RUE, mediante a solicitação de leito via Centro de Regulação de Ofertas de Serviços de Saúde (CROSS), para pacientes com SRAG por COVID-19. Métodos: trata-se de coorte retrospectiva com 996 usuários do Sistema Único de Saúde (SUS) ≥ 18 anos, residentes no município de Bauru, São Paulo, Brasil, que aguardaram internação via RUE-CROSS, com SRAG por COVID-19, de 01/11/2020 a 30/04/2021. Coletou-se os dados do Sistema de Vigilância Epidemiológica da Gripe (SIVEP-Gripe) e CROSS. Considerou-se como variável de exposição o período de tempo em dias de espera por liberação de leito hospitalar via RUE-CROSS e como desfecho o óbito hospitalar. A análise estatística final deu-se por ajuste de modelo de regressão linear múltipla parcimoniosa, a partir de regressão múltipla com resposta Poisson, decorrente de associações bivariadas. Resultados: o tempo médio de espera por internação via RUE-CROSS de pacientes com SRAG por COVID-19 foi de 1,88 ± 1,82 dias, com risco de óbito, em média, de 1% a cada dia de espera (24 horas) (RR = 1,01; IC95% = (1,001 - 1,03); p = 0,047). Estimou-se por meio da Curva ROC em 1,5 dias (36 horas) o tempo de espera que maximiza a predição do óbito por COVID-19, com área sob a curva significativa (área=0,59, IC95% = (0,55; 0,63)). Ademais, outras associações estatísticas conferiram riscos, como: internação em UTI (50%); pacientes com procedimento de intubação (20%) e velamento difuso pulmonar (15%). Conclusões: o tempo médio de espera elevado na RUE, mesmo ampliado o número de leitos em instituições hospitalares locais e regionais já existentes, mostrou-se estratégia contingencial insuficiente para reduzir o risco de óbito hospitalar pela doença em período de pico da transmissão da COVID-19, uma vez ter ultrapassado a média de tempo de corte para a maximização de risco, de 1,5 dias para 1,88 ± 1,82 dias. Sugere-se a necessidade de se dispor de hospitais de campanha nos planos contingenciais da doença e de outras pandemias de doenças infecciosas respiratórias.
Introduction: in Brazil, during the second wave of the COVID-19 pandemic, there was a shortage of hospital beds to transfer patients, overloading services in the Urgency and Emergency Network (UEN), especially with those with Severe Acute Respiratory Syndrome (SARS). This waiting time is conjectured to have influenced the hospital death outcome, however there isn’t consensus in the literature on the accumulated risk per day of waiting in urgent and emergency services, as well as the time that maximized the risk of hospital death for this patient. Objective: to investigate the association between the outcome of hospital death and the waiting time in the UEN, upon requesting a bed via the Center for the Regulation of Health Service Offers (CROSS), for patients with SARS due to COVID-19. Methods: this is a retrospective cohort with 996 users of the Unified Health System (SUS) ≥ 18 years old, living in the city of Bauru, São Paulo, Brazil, who waited for hospitalization via UEN-CROSS, with SARS due to COVID-19, from 11/01/2020 to 04/30/2021. Data were collected from the Influenza Epidemiological Surveillance System (SIVEP-Flu) and CROSS. The length of time in days waiting for hospital bed release via UEN-CROSS was considered as an exposure variable, and hospital death was considered as the outcome. The final statistical analysis was carried out by adjusting a parsimonious multiple linear regression model, based on multiple regression with Poisson response, resulting from bivariate associations. Results: the mean waiting time for hospitalization via UEN-CROSS of patients with SARS due to COVID-19 was 1.88 ± 1.82 days, with an average risk of death of 1% for each day of waiting (24 hours) (RR = 1.01; CI95% = (1.001 - 1.03); p = 0.047). Using the ROC curve, the waiting time that maximizes the prediction of death from COVID-19 was estimated at 1.5 days (36 hours), with a significant area under the curve (area=0.59, 95%CI = (0 .55; 0.63)). Furthermore, other statistical associations conferred risks, such as: ICU admission (50%); patients with intubation procedure (20%) and diffuse pulmonary veiling (15%). Conclusions: the high average waiting time in the UEN, even with the increased number of beds in existing local and regional hospital institutions, proved to be an insufficient contingency strategy to reduce the risk of hospital death from the disease during the peak period of COVID-19 transmission. 19, once the average cut-off time for risk maximization was exceeded, from 1.5 days to 1.88 ± 1.82 days. It is suggested the need to have field hospitals in the contingency plans for the disease and other pandemics of infectious respiratory diseases.
Introduction: in Brazil, during the second wave of the COVID-19 pandemic, there was a shortage of hospital beds to transfer patients, overloading services in the Urgency and Emergency Network (UEN), especially with those with Severe Acute Respiratory Syndrome (SARS). This waiting time is conjectured to have influenced the hospital death outcome, however there isn’t consensus in the literature on the accumulated risk per day of waiting in urgent and emergency services, as well as the time that maximized the risk of hospital death for this patient. Objective: to investigate the association between the outcome of hospital death and the waiting time in the UEN, upon requesting a bed via the Center for the Regulation of Health Service Offers (CROSS), for patients with SARS due to COVID-19. Methods: this is a retrospective cohort with 996 users of the Unified Health System (SUS) ≥ 18 years old, living in the city of Bauru, São Paulo, Brazil, who waited for hospitalization via UEN-CROSS, with SARS due to COVID-19, from 11/01/2020 to 04/30/2021. Data were collected from the Influenza Epidemiological Surveillance System (SIVEP-Flu) and CROSS. The length of time in days waiting for hospital bed release via UEN-CROSS was considered as an exposure variable, and hospital death was considered as the outcome. The final statistical analysis was carried out by adjusting a parsimonious multiple linear regression model, based on multiple regression with Poisson response, resulting from bivariate associations. Results: the mean waiting time for hospitalization via UEN-CROSS of patients with SARS due to COVID-19 was 1.88 ± 1.82 days, with an average risk of death of 1% for each day of waiting (24 hours) (RR = 1.01; CI95% = (1.001 - 1.03); p = 0.047). Using the ROC curve, the waiting time that maximizes the prediction of death from COVID-19 was estimated at 1.5 days (36 hours), with a significant area under the curve (area=0.59, 95%CI = (0 .55; 0.63)). Furthermore, other statistical associations conferred risks, such as: ICU admission (50%); patients with intubation procedure (20%) and diffuse pulmonary veiling (15%). Conclusions: the high average waiting time in the UEN, even with the increased number of beds in existing local and regional hospital institutions, proved to be an insufficient contingency strategy to reduce the risk of hospital death from the disease during the peak period of COVID-19 transmission. 19, once the average cut-off time for risk maximization was exceeded, from 1.5 days to 1.88 ± 1.82 days. It is suggested the need to have field hospitals in the contingency plans for the disease and other pandemics of infectious respiratory diseases.
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Síndrome Respiratória Aguda Grave, Serviços médicos de emergência, Ocupação de leitos, Mortalidade hospitalar, Estudos de coortes, COVID-19 (Doença)