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. COVID19 COVID 19 COVID-1 pandemic singlecenter single center study System 2020 2021 Paulo Brazil May 31 30 total 1427 427 1,42 421 (42 1,006 1006 006 (1,00 median IQR, IQR , (IQR)] 57 [5 4670 46 70 (46-70 6 5280 52 80 (52-80 years p<0.001, p0001 p p<0.001 0 001 p<0.001] 45 [4 4252 42 (42-52 4357 43 (43-57) [ 16 (1-6 26 2 (2-6) p=0.018, p0018 p=0.018 018 p=0.018] 01 (0-1 02 (0-2) 10.4% 104 10 (10.4 18.1% 181 18 p<0.001. . 81.3% 813 81 (81.3 53.4% 534 53 highflow high flow 63.2% 632 63 (63.2 23.0% 230 23 stay 11.3% 113 11 (11.3 10.5% 105 5 p=0.696 p0696 696 inhospital 12.3% 123 12 (12.3 12.1% 121 p=0.998 p0998 998 support COVID1 COVID- 202 142 1,4 (4 1,00 100 00 (1,0 (IQR) 467 7 (46-7 528 8 (52-8 p000 p<0.00 425 (42-5 435 (43-57 (1- (2-6 p001 p=0.01 (0- (0-2 10.4 (10. 18.1 81.3 (81. 53.4 63.2 (63. 23.0 11.3 (11. 10.5 p=0.69 p069 69 12.3 (12. 12.1 p=0.99 p099 99 20 14 ( 1,0 (1, (IQR (46- (52- p00 p<0.0 (42- (43-5 (1 (2- p=0.0 (0 10. (10 18. 81. (81 53. 63. (63 23. 11. (11 p=0.6 p06 12. (12 p=0.9 p09 9 (46 (52 p0 p<0. (43- (2 p=0. (8 (6 (5 p<0 (43 p=0 p< p=

ABSTRACT Objective The objective of the present study is to evaluate the association of red blood cell distribution width with acute kidney injury in sepsis. Methods This is a retrospective study of 849 critically ill patients with sepsis in intensive care unit. Demographic data, renal function, inflammation, complete blood count, and acid-base parameters were compared between acute kidney injury and non-acute kidney injury groups. Therefore, a multivariate analysis was performed to observe independent predictive factors. Results Comparatively, higher levels of C-reactive protein, lactate, red blood cell distribution width, and Simplified Acute Physiology Score 3 were found in the acute kidney injury group. The study showed a higher frequency of women, hemoglobin (Hgb) concentration, platelets, bicarbonate and PaO2/FiO2 ratio in the non-acute kidney injury group. In addition, there was an independent association of comorbidity-chronic kidney disease [OR 3.549, 95%CI: 1.627-7.743; p<0.001], urea [OR 1.047, 95%CI: 1.036-1.058; p<0.001] and RDW [OR 1.158, 95%CI: 1.045-1.283; p=0.005] with acute kidney injury in sepsis patients. Conclusion As an elective risk factor, red blood cell distribution width was independently associated with sepsis-related acute kidney injury. Thus, red blood cell distribution width acts like a predictive factor for sepsis-induced acute kidney injury in intensive care unit admission.

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.

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.

Objetivo Comparar os resultados obtidos com a ressuscitação de idosos (≥65 anos) e não idosos (<65 anos) com sepse grave ou choque séptico e determinar os preditores de óbito em pacientes idosos.Métodos Estudo de coorte retrospectivo com 848 pacientes com sepse grave ou choque séptico admitidos na unidade de terapia intensiva entre janeiro de 2006 e março de 2012.Resultados Pacientes idosos representaram 62,6% (531/848) e não idosos 37,4% (317/848) dos pacientes. Pacientes idosos apresentaram maior escore APACHE II [22 (18-28) versus 19 (15-24); p<0,001] em comparação com pacientes não idosos, embora o número de disfunções orgânicas não tenha sido diferente entre os grupos. Não se observaram diferenças significativas na mortalidade hospitalar e em 28 dias entre pacientes idosos e não idosos, embora o tempo de internação hospitalar tenha sido superior nos pacientes idosos, em comparação com não idosos [18 (10-41) versus 14 (8-29) dias, respectivamente; p=0,0001]. Foram preditores de óbito entre pacientes idosos a idade, o local do diagnóstico, o escore APACHE II e a necessidade de ventilação mecânica e vasopressores.Conclusão A ressuscitação de pacientes idosos com sepse grave ou choque séptico não associou-se ao aumento de mortalidade hospitalar. Estudos prospectivos são necessários para avaliação do impacto a longo prazo no estado funcional e qualidade de vida dos pacientes idosos ressuscitados.

Objective To compare outcomes between elderly (≥65 years old) and non-elderly (<65 years old) resuscitated severe sepsis and septic shock patients and determine predictors of death among elderly patients.Methods Retrospective cohort study including 848 severe sepsis and septic shock patients admitted to the intensive care unit between January 2006 and March 2012.Results Elderly patients accounted for 62.6% (531/848) and non-elderly patients for 37.4% (317/848). Elderly patients had a higher APACHE II score [22 (18-28)versus 19 (15-24); p<0.001], compared to non-elderly patients, although the number of organ dysfunctions did not differ between the groups. No significant differences were found in 28-day and in-hospital mortality rates between elderly and non-elderly patients. The length of hospital stay was higher in elderly compared to non-elderly patients admitted with severe sepsis and septic shock [18 (10-41)versus 14 (8-29) days, respectively; p=0.0001]. Predictors of death among elderly patients included age, site of diagnosis, APACHE II score, need for mechanical ventilation and vasopressors.Conclusion In this study population early resuscitation of elderly patients was not associated with increased in-hospital mortality. Prospective studies addressing the long-term impact on functional status and quality of life are necessary.

CONTEXTO E OBJETIVO: Modelos prognósticos refletem as características da população dos países de onde eles são originários. Modelos preditivos devem ser customizados para se adequar à população geral onde eles serão utilizados. O objetivo aqui foi de realizar a validação externa de dois modelos preditivos e comparar o seu desempenho em uma população mista de pacientes graves no Brasil.TIPO DE ESTUDO E LOCAL: Estudo retrospectivo em uma unidade de terapia intensiva geral brasileira.MÉTODOS: Este é um estudo retrospectivo de todos os pacientes internados em uma unidade de terapia intensiva (UTI) mista com 41 leitos entre agosto de 2011 e setembro de 2012. A calibração (avaliada com o teste de Hosmer-Lemeshow goodness-of-fit) e a discriminação (avaliada como a área sob a curva) do APACHE II e do SAPS III foram comparados. A razão de mortalidade padronizada (SMR) foi calculada pela divisão do número de óbitos observados pelo número de óbitos esperados.RESULTADOS: Um total de 3.333 pacientes internados na UTI foi registrado. O teste de Hosmer-Lemeshow goodness-of-fit demonstrou boa calibração para todos os modelos em relação a mortalidade hospitalar. Para a mortalidade intra-hospitalar, há um ajuste pior do APACHE II em pacientes clínicos. A discriminação foi melhor para o SAPS III para mortalidade na UTI e no hospital (P = 0,042). A SMR para toda a população foi de 0,27 (intervalo de confiança [IC]: 0,23-0,33) para APACHE II e de 0,28 (IC: 0,22-0,36) para SAPS III.CONCLUSÕES: Neste grupo de pacientes graves, o SAPS III é o melhor escore prognóstico, com a maior discriminação e poder de calibração.

CONTEXT AND OBJECTIVE: Prognostic models reflect the population characteristics of the countries from which they originate. Predictive models should be customized to fit the general population where they will be used. The aim here was to perform external validation on two predictive models and compare their performance in a mixed population of critically ill patients in Brazil.DESIGN AND SETTING: Retrospective study in a Brazilian general intensive care unit (ICU).METHODS: This was a retrospective review of all patients admitted to a 41-bed mixed ICU from August 2011 to September 2012. Calibration (assessed using the Hosmer-Lemeshow goodness-of-fit test) and discrimination (assessed using area under the curve) of APACHE II and SAPS III were compared. The standardized mortality ratio (SMR) was calculated by dividing the number of observed deaths by the number of expected deaths.RESULTS: A total of 3,333 ICU patients were enrolled. The Hosmer-Lemeshow goodness-of-fit test showed good calibration for all models in relation to hospital mortality. For in-hospital mortality there was a worse fit for APACHE II in clinical patients. Discrimination was better for SAPS III for in-ICU and in-hospital mortality (P = 0.042). The SMRs for the whole population were 0.27 (confidence interval [CI]: 0.23 - 0.33) for APACHE II and 0.28 (CI: 0.22 - 0.36) for SAPS III.CONCLUSIONS: In this group of critically ill patients, SAPS III was a better prognostic score, with higher discrimination and calibration power.