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

Thiago Domingos Corrêa Thais Dias Midega Karina Tavares Timenetsky Ricardo Luiz Cordioli Carmen Silvia Valente Barbas Moacyr Silva Júnior Bruno de Arruda Bravim Bruno Caldin Silva Gustavo Faissol Janot de Matos Ricardo Kenji Nawa Fabrício Rodrigues Torres de Carvalho Verônica Neves Fialho Queiroz Roberto Rabello Filho Felipe Maia de Toledo Piza Adriano José Pereira Marcele Liliane Pesavento Raquel Afonso Caserta Eid Bento Fortunato Cardoso dos Santos Andreia Pardini Vanessa Damázio Teich Claudia Regina Laselva Miguel Cendoroglo Neto Sidney Klajner Leonardo José Rolim Ferraz About the authors

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.

Keywords:
Coronavirus; COVID-19; Coronavirus infections; SARS-CoV-2; Betacoronavirus; Intensive care units; Respiration, artificial; Noninvasive ventilation; Extracorporeal membrane oxygenation; Critical care outcomes; Mortality

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 Simplied 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.

Descritores:
Coronavírus; COVID-19; Infecções por coronavírus; SARS-CoV-2; Betacoronavírus; Unidades de terapia intensiva; Respiração artificial; Ventilação não invasiva; Oxigenação por membrana extracorpórea; Resultados de cuidados críticos; Mortalidade

INTRODUCTION

Coronavirus disease 2019 (COVID-19) is an emerging infectious disease that was first reported in Wuhan, China, and has subsequently spread worldwide.(11 Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395(10223):497-506. Erratum in: Lancet. 2020 Jan 30;:) Although most of the infected patients develop only mild symptoms, approximately 15% of symptomatic patients will require hospitalization,(22 Teich VD, Klajner S, Almeida FA, Dantas AC, Laselva CR, Torritesi MG, et al. Epidemiologic and clinical features of patients with COVID-19 in Brazil. einstein (São Paulo). 2020;18:eAO6022.) and almost 20% of hospitalized patients will require intensive care unit (ICU) admission due to progression to acute respiratory failure (ARF).(33 Petrilli CM, Jones SA, Yang J, Rajagopalan H, O’Donnell L, Chernyak Y, et al. Factors associated with hospital admission and critical illness among 5279 people with coronavirus disease 2019 in New York City: prospective cohort study. BMJ. 2020;369:m1966.,44 Chang R, Elhusseiny KM, Yeh YC, Sun WZ. COVID-19 ICU and mechanical ventilation patient characteristics and outcomes-a systematic review and meta-analysis. PLoS One. 2021;16(2):e0246318.)

Advanced age, male sex, obesity, systemic hypertension, diabetes mellitus, chronic obstructive pulmonary disease (COPD), and cardiovascular disease are major risk factors for severe COVID-19.(55 Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet. 2020;395(10223):507-13.

6 Grasselli G, Zangrillo A, Zanella A, Antonelli M, Cabrini L, Castelli A, Cereda D, Coluccello A, Foti G, Fumagalli R, Iotti G, Latronico N, Lorini L, Merler S, Natalini G, Piatti A, Ranieri MV, Scandroglio AM, Storti E, Cecconi M, Pesenti A; COVID-19 Lombardy ICU Network. Baseline characteristics and outcomes of 1591 patients infected with SARS-CoV-2 admitted to ICUs of the Lombardy Region, Italy. JAMA. 2020;323(16):1574-81. Erratum in: JAMA. 2021;325(20):2120.

7 Jain V, Yuan JM. Predictive symptoms and comorbidities for severe COVID-19 and intensive care unit admission: a systematic review and meta-analysis. Int J Public Health. 2020;65(5):533-46.
-88 Wu C, Chen X, Cai Y, Xia J, Zhou X, Xu S, et al. Risk factors associated with acute respiratory distress syndrome and death in patients with coronavirus disease 2019 pneumonia in Wuhan, China. JAMA Intern Med. 2020;180(7):934-43. Erratum in: JAMA Intern Med. 2020;180(7):1031.) Critically ill patients with COVID-19 require substantial organ support and prolonged ICU stay.(99 Tan E, Song J, Deane AM, Plummer MP. Global impact of coronavirus disease 2019 infection requiring admission to the ICU: a systematic review and meta-analysis. Chest. 2021;159(2):524-36.) For instance, a systematic review including 16,561 critically ill COVID-19 patients demonstrated approximately 76% of COVID-19 patients admitted to the ICU developed acute respiratory distress syndrome (ARDS), two thirds of patients used mechanical ventilation, and 17% of them required renal replacement therapy (RRT).(99 Tan E, Song J, Deane AM, Plummer MP. Global impact of coronavirus disease 2019 infection requiring admission to the ICU: a systematic review and meta-analysis. Chest. 2021;159(2):524-36.)

The first case of COVID-19 in Brazil was confirmed at Hospital Israelita Albert Einstein (HIAE), on February 26, 2020.(22 Teich VD, Klajner S, Almeida FA, Dantas AC, Laselva CR, Torritesi MG, et al. Epidemiologic and clinical features of patients with COVID-19 in Brazil. einstein (São Paulo). 2020;18:eAO6022.) Up to June 2021, more than 16 million cases and 500 thousand deaths due to COVID-19 had been registered in Brazil.(1010 Brasil. Ministério da Saúde. COVID-19. Painel Coronavírus. Brasília (DF): Ministério da Saúde; 2021 [citado 2021 Jun 27]. Disponível em: https://covid.saude.gov.br/
https://covid.saude.gov.br/...
) Nevertheless, few studies reported on epidemiology, clinical characteristics, resource use, and outcomes of ICU patients with COVID-19, in Brazil.(1111 Santos MM, Lucena EE, Lima KC, Brito AA, Bay MB, Bonfada D. Survival and predictors of deaths of patients hospitalised due to COVID-19 from a retrospective and multicentre cohort study in Brazil. Epidemiol Infect. 2020; 148:e198.

12 Socolovithc RL, Fumis RR, Tomazini BM, Pastore L, Galas FR, de Azevedo LC, et al. Epidemiology, outcomes, and the use of intensive care unit resources of critically ill patients diagnosed with COVID-19 in Sao Paulo, Brazil: a cohort study. PLoS One. 2020;15(12):e0243269.

13 Sousa GJ, Garces TS, Cestari VR, Florêncio RS, Moreira TM, Pereira ML. Mortality and survival of COVID-19. Epidemiol Infect. 2020;148:e123.
-1414 Ranzani OT, Bastos LS, Gelli JG, Marchesi JF, Baiao F, Hamacher S, et al. Characterisation of the first 250 000 hospital admissions for COVID-19 in Brazil: a retrospective analysis of nationwide data. Lancet Respir Med. 2021;9:407-18.)

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

Study design

We performed a single center retrospective cohort study. The study was approved by the Local Ethics Committee at HIAE with waiver of Informed Consent (CAAE: 30797520.6.0000.0071, protocol number: 4.562.815). This study is reported in accordance with the effort Strengthening the Reporting of Observational Studies in Epidemiology (STROBE).(1515 von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP; Iniciativa STROBE. [The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies]. Rev Esp Salud Publica. 2008;82(3):251-9. Spanish.)

Setting

This study was conducted in a private quaternary care hospital located in São Paulo, SP, Brazil. The HIAE comprises 634 beds. Out of those, 37 were open medical-surgical adult ICU beds and 81 were adult step-down unit beds. During the first year of the COVID-19 pandemic, the total ICU operational capacity was increased, reaching 81 ICU beds designated to support severe COVID-19 patients requiring intensive care.

Study participants

Consecutive adult (≥18 years) patients admitted to the ICU, from March 4, 2020 to February 28, 2021 and diagnosed with COVID-19 were eligible for inclusion in this study. Laboratory confirmation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection was based on positive reverse transcriptase polymerase chain reaction (RT-PCR) assay (Cobas® SARS-CoV-2 Test, Roche Molecular Systems, Branchburg, NJ, United States).(1616 Corman VM, Landt O, Kaiser M, Molenkamp R, Meijer A, Chu DK, et al. Detection of 2019 novel coronavirus (2019-nCoV) by real-time RT-PCR. Euro Surveill. 2020;25(3):2000045. Erratum in: Euro Surveill. 2020;25(14): Erratum in: Euro Surveill. 2020;25(30): Erratum in: Euro Surveill. 2021;26(5).)

Patient management

Criteria for ICU admission and the institutional protocol for severe SARS-CoV-2 infection management have been published elsewhere.(1717 Corrêa TD, Matos GF, Bravim BA, Cordioli RL, Garrido AG, Assuncao MS, et al. Intensive support recommendations for critically-ill patients with suspected or confirmed COVID-19 infection. einstein (São Paulo). 2020;18:eAE5793.,1818 Corrêa TD, Matos GF, Bravim BA, Cordioli RL, Garrido AG, Assuncao MS, et al. Comment to:Intensive support recommendations for critically-ill patients with suspected or confirmed COVID-19 infection. einstein (São Paulo). 2020; 18:eCE5931.)

Data collection and study variables

All study data were retrieved from Epimed Monitor system (Epimed Solutions, Rio de Janeiro, Brazil), which is an electronic structured case report form, in which patients’ data are prospectively entered by trained ICU case managers.(1919 Soares M, Bozza FA, Angus DC, Japiassú AM, Viana WN, Costa R, et al. Organizational characteristics, outcomes, and resource use in 78 Brazilian intensive care units: the ORCHESTRA study. Intensive Care Med. 2015;41(12):2149-60.) Collected variables included demographics, comorbidities, Simplified Acute Physiology Score (SAPS 3)(2020 Moreno RP, Metnitz PG, Almeida E, Jordan B, Bauer P, Campos RA, Iapichino G, Edbrooke D, Capuzzo M, Le Gall JR; SAPS 3 Investigators. SAPS 3-From evaluation of the patient to evaluation of the intensive care unit. Part 2: Development of a prognostic model for hospital mortality at ICU admission. Intensive Care Med. 2005;31(10):1345-55. Erratum in: Intensive Care Med. 2006;32(5):796.) at ICU admission, Sequential Organ Failure Assessment (SOFA)(2121 Vincent JL, Moreno R, Takala J, Willatts S, De Mendonca A, Bruining H, et al. The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure. On behalf of the Working Group on Sepsis-Related Problems of the European Society of Intensive Care Medicine. Intensive Care Med. 1996;22(7):707-10.) at ICU admission, Charlson Comorbidity Index,(2222 Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373-83.) modified frailty index (MFI),(2323 Velanovich V, Antoine H, Swartz A, Peters D, Rubinfeld I. Accumulating deficits model of frailty and postoperative mortality and morbidity: its application to a national database. J Surg Res. 2013;183(1):104-10.) resource use and organ support (vasopressors, noninvasive ventilation, high flow nasal cannula – HFNC –, mechanical ventilation, and extracorporeal membrane oxygenation – ECMO), during ICU stay, destination at hospital discharge, ICU and hospital length of stay, and ICU and in-hospital mortality.

Statistical analysis

Categorical variables are presented as absolute and relative frequencies. Continuous variables are presented as median with interquartile range (IQR). Normality was assessed by the Kolmogorov-Smirnov test.

Comparisons were made between survivors and non-survivors, based on in-hospital mortality. Categorical variables were compared using the χ2 test or Fisher exact test, when appropriate. Continuous variables were compared using independent t test, or Mann-Whitney U test in case of non-normal distribution. Survival at day 28 of pooled patients, and survival stratified according to the use of mechanical ventilation, RRT and ECMO, were analyzed by means of the Kaplan-Meier method. Patients discharged from hospital before 28 days were considered alive at day 28.

Univariable logistic regression analysis was performed to identify which predictors were associated with in-hospital mortality. Multivariable logistic regression analyses with backward elimination procedure, including all the predictors showing a p-value <0.10 in the univariable analysis, were undertaken to obtain adjusted odds ratio (OR), along with 95% confidence interval (95%CI), and to define which variables were independently associated with in-hospital mortality. We tested the linearity assumption for continuous variables included in logistic regression models by analyzing the interaction between each predictor and its own log (natural log transformation).(2424 Hosmer DW, Lemeshow S, Sturdivant RX. Applied logistic regression. Nova Jersey: Wiley & Sons; 2013. p. 203-22.) Whenever the linearity assumption was violated, continuous variables were categorized. Final multivariable logistic regression model discrimination (area under a Receiver Operating Characteristic Curve – AUC) and calibration (Hosmer-Lemeshow χ2 statistic) were reported.(2525 Ottenbacher KJ, Ottenbacher HR, Tooth L, Ostir GV. A review of two journals found that articles using multivariable logistic regression frequently did not report commonly recommended assumptions. J Clin Epidemiol. 2004;57(11):1147-52. Review.)

Two-tailed tests were used, and considered statistically significant when p<0.05. All analyses were performed using IBM (SPSS) for Macintosh, version 27.0., and GraphPad Prism version 9.0 (GraphPad Software, California, United States) was used for graph plotting.

RESULTS

Cohort included

Between March 4, 2020 and February 28, 2021, 1,296 patients with laboratory confirmed COVID-19 were admitted to the ICU. Out of those, 170 (13.6%) died at hospital (non-survivors) and 1.078 (86.4%) were discharged alive from the hospital (survivors). By the time data were extracted (March 9, 2021), 48 patients were still hospitalized. Baseline characteristics of patients are shown in table 1.

Table 1
Baseline characteristics of studied patients according to in-hospital mortality

The median (IQR) age of pooled patients was 66 (53 to 77) years, 66.5% were male, and the median (IQR) SAPS 3 was 49 (42 to 56) points. The most common comorbidities were hypertension (59.4%), diabetes mellitus (35.8%), and obesity (30.7%). At ICU admission, 20.6% of patients were receiving noninvasive ventilation, 8.6% were under mechanical ventilation, and 6.4% were using vasopressors.

Compared to survivors, non-survivors were older [80 (70-88) versus 63 (50-74) years; p<0.001], had a higher SAPS 3 [59 (54-66) versus 47 (42-53) points; p<0.001] and a higher SOFA [6 (4-9) versus 1 (0-3) points; p<0.001] at ICU admission. Cancer, congestive heart failure, chronic kidney disease requiring and not requiring RRT were more frequent in non-survivors compared to survivors.

Resource use

During the ICU stay, 56.6% of patients received noninvasive ventilation, 32.9% of patients were mechanically ventilated; 31.3% used HFNC, 11.7% received RRT, and 1.5% received ECMO support. The median (IQR) duration of mechanical ventilation in pooled patients was 11 (6 to 24) days (Table 2).

Table 2
Resource use

Mechanical ventilation, HFNC, vasopressors, RRT, and ECMO were more frequently used in non-survivors compared to survivors. The median (IQR) days on mechanical ventilation was higher in non-survivors compared to survivors [17 (10-38) versus 9 (5-15) days; p<0.001].

Clinical outcomes

Pooled patients

Intensive care unit and in-hospital mortality of pooled patients was, respectively, 11.7% (151 of 1,296 patients) and 13.6% (170 of 1,248 patients) (Table 3). Monthly ICU and in-hospital mortality between March 2020 and February 2021 is shown in figure 1. Cumulative survival at day 28 of pooled patients and survival stratified according to the use of mechanical ventilation, RRT, and ECMO are shown in figure 2.

Table 3
Clinical outcomes
Figure 1
Monthly length of intensive care unit and hospital stay, intensive care unit and in-hospital mortality, and simplified acute physiology score 3 from March 2020 to February 2021
Figure 2
Cumulative survival at day 28 of pooled patients and according to the need for organ support

The median IQR length of ICU and hospital stay was, respectively, 7 (4 to 16) days and 13 (8 to 23) days. Compared to survivors, non-survivors exhibited a higher length of ICU [15 (9-29) versus 7 (3-13) days; p<0.001] and hospital stay [19 (12-34) versus 12 (8-21) days; p<0.001] (Table 3).

Mechanically ventilated patients

Mechanically ventilated patients exhibited a higher in-hospital mortality compared to patients who did not receive mechanical ventilation (34.1% versus 4.3%; unadjusted OR: 11.5; 95%CI: 7.8-17.0; p<0.001). The length of ICU [20 (13-32) versus 5 (2-8) days; p<0.001] and hospital stay [27 (17-41) versus 10 (7-15) days; p<0.001] was higher in patients who received mechanical ventilation compared to non-mechanically ventilated patients.

Patients who received renal replacement therapy

Patients submitted to RRT showed a higher in-hospital mortality compared to patients who did not receive RRT (56.3% versus 8.4%; unadjusted OR: 14.0; 95%CI: 9.4-20.8; p<0.001). Mechanical ventilation was used in 143 of 151 (94.7%) patients who received RRT. The length of ICU [27 (15-40) versus 7 (3-13) days; p<0.001] and hospital stay [33 (22-55) versus 12 (8-19) days; p<0.001] was higher in patients who received RRT than in patients who did not receive RRT.

Patients who received extracorporeal membrane oxygenation

Patients who received ECMO exhibited a higher in-hospital mortality compared to patients who did not receive ECMO [64.7% versus 12.9%; unadjusted OR: 12.4; 95%CI: 4.5-33.9; p<0.001) (Table 3). All patients who received ECMO support received mechanical ventilation, and 13 out of 20 (65.0%) patients also used RRT. The length of ICU [32 (24-59) versus 7 (3-15) days; p<0.001] and hospital stay [48 (29-70) versus 12 (8-23) days; p<0.001] was higher in patients who received ECMO than in patients who did not receive ECMO support.

Predictors of in-hospital mortality

Univariable analysis of factors associated with in-hospital death is depicted in table 4. After adjusting for confounders, independent predictors of in-hospital mortality included age (OR: 1.08; 95%CI: 1.06-1.10; p<0.001); SOFA (OR: 1.18; 95%CI: 1.08-1.29; p<0.001); Charlson Comorbidity Index (OR: 1.28; 95%CI: 1.15-1.43; p<0.001); the need for mechanical ventilation (OR: 4.45; 95%CI: 2.43-8.16; p<0.001); the need for HFNC (OR: 1.64; 95%CI: 1.04-2.58; p=0.033); RRT (OR: 3.42; 95%CI: 1.96-5.98; p<0.001) and ECMO support (OR: 8.18; 95%CI: 2.48-27.05; p<0.001) (Table 4). The final multivariable model had an area under the ROC curve (95%CI) of 0.93 (0.91-0.94) and a Hosmer-Lemeshow χ2 of 8.844 (p=0.356).

Table 4
Univariable and multivariable logistic regression analyses addressing risk factors for in-hospital mortality

DISCUSSION

In this retrospective single center cohort study, we found that one in seven patients admitted to the ICU due to severe COVID-19 infection died at the hospital. Non-survivors were older, sicker, in accordance with SAPS 3 and SOFA, presented more comorbidities, such as cancer, congestive heart failure or chronic kidney disease, and had a longer ICU and hospital length of stay compared to survivors. Finally, increased age, higher SOFA score and Charlson Comorbidity Index, need for mechanical ventilation, HFNC, RRT, and ECMO were independent predictors of in-hospital mortality.

The association between advanced age and increased risk of death in patients infected with SARS-CoV-2 has been reported by different authors.(33 Petrilli CM, Jones SA, Yang J, Rajagopalan H, O’Donnell L, Chernyak Y, et al. Factors associated with hospital admission and critical illness among 5279 people with coronavirus disease 2019 in New York City: prospective cohort study. BMJ. 2020;369:m1966.,2626 Cummings MJ, Baldwin MR, Abrams D, Jacobson SD, Meyer BJ, Balough EM, et al. Epidemiology, clinical course, and outcomes of critically ill adults with COVID-19 in New York City: a prospective cohort study. Lancet. 2020;395(10239):1763-70.

27 Chen T, Wu D, Chen H, Yan W, Yang D, Chen G, et al. Clinical characteristics of 113 deceased patients with coronavirus disease 2019: retrospective study. BMJ. 2020;368:m1091. Erratum for: BMJ. 2020;368:m1295.
-2828 Gupta S, Hayek SS, Wang W, Chan L, Mathews KS, Melamed ML, Brenner SK, Leonberg-Yoo A, Schenck EJ, Radbel J, Reiser J, Bansal A, Srivastava A, Zhou Y, Sutherland A, Green A, Shehata AM, Goyal N, Vijayan A, Velez JC, Shaefi S, Parikh CR, Arunthamakun J, Athavale AM, Friedman AN, Short SA, Kibbelaar ZA, Abu Omar S, Admon AJ, Donnelly JP, Gershengorn HB, Hernán MA, Semler MW, Leaf DE; STOP-COVID Investigators. Factors associated with death in critically Ill patients with Coronavirus disease 2019 in the US. JAMA Intern Med. 2020;180(11):1436-47. Erratum in: JAMA Intern Med. 2020;180(11):1555.) Moreover, the association between the presence of comorbidities and the severity of COVID-19 was evidenced in several studies.(99 Tan E, Song J, Deane AM, Plummer MP. Global impact of coronavirus disease 2019 infection requiring admission to the ICU: a systematic review and meta-analysis. Chest. 2021;159(2):524-36.,2626 Cummings MJ, Baldwin MR, Abrams D, Jacobson SD, Meyer BJ, Balough EM, et al. Epidemiology, clinical course, and outcomes of critically ill adults with COVID-19 in New York City: a prospective cohort study. Lancet. 2020;395(10239):1763-70.,2929 Wang B, Li R, Lu Z, Huang Y. Does comorbidity increase the risk of patients with COVID-19: evidence from meta-analysis. Aging (Albany NY). 2020; 12(7):6049-57.,3030 Li B, Yang J, Zhao F, Zhi L, Wang X, Liu L, et al. Prevalence and impact of cardiovascular metabolic diseases on COVID-19 in China. Clin Res Cardiol. 2020;109(5):531-8. Review.) For instance, COVID-19 patients with hypertension, cardiocerebrovascular diseases, and diabetes mellitus were at higher risk of developing severe symptoms, and requiring ICU admission than patients without these comorbidities.(3030 Li B, Yang J, Zhao F, Zhi L, Wang X, Liu L, et al. Prevalence and impact of cardiovascular metabolic diseases on COVID-19 in China. Clin Res Cardiol. 2020;109(5):531-8. Review.) Furthermore, we observed that locoregional cancer diagnosis was more prevalent in deceased patients in comparison with survivors. Indeed, it was demonstrated in a large case-control study that cancer patients with COVID-19 exhibited an increased risk of worse clinical outcomes.(3131 Wang Q, Berger NA, Xu R. Analyses of risk, racial disparity, and outcomes among US patients with cancer and COVID-19 infection. JAMA Oncol. 2021;7(2):220-7.) Although increased mortality has also been reported in patients with hematological cancer,(3232 Passamonti F, Cattaneo C, Arcaini L, Bruna R, Cavo M, Merli F, Angelucci E, Krampera M, Cairoli R, Della Porta MG, Fracchiolla N, Ladetto M, Gambacorti Passerini C, Salvini M, Marchetti M, Lemoli R, Molteni A, Busca A, Cuneo A, Romano A, Giuliani N, Galimberti S, Corso A, Morotti A, Falini B, Billio A, Gherlinzoni F, Visani G, Tisi MC, Tafuri A, Tosi P, Lanza F, Massaia M, Turrini M, Ferrara F, Gurrieri C, Vallisa D, Martelli M, Derenzini E, Guarini A, Conconi A, Cuccaro A, Cudillo L, Russo D, Ciambelli F, Scattolin AM, Luppi M, Selleri C, Ortu La Barbera E, Ferrandina C, Di Renzo N, Olivieri A, Bocchia M, Gentile M, Marchesi F, Musto P, Federici AB, Candoni A, Venditti A, Fava C, Pinto A, Galieni P, Rigacci L, Armiento D, Pane F, Oberti M, Zappasodi P, Visco C, Franchi M, Grossi PA, Bertù L, Corrao G, Pagano L, Corradini P; ITA-HEMA-COV Investigators. Clinical characteristics and risk factors associated with COVID-19 severity in patients with haematological malignancies in Italy: a retrospective, multicentre, cohort study. Lancet Haematol. 2020;7(10):e737-e45.) we did not observe this association in our study.

Interestingly, in our cohort we found lower in-hospital mortality both among patients admitted to the ICU and those requiring mechanical ventilation support, compared to previous studies conducted in Brazil(1414 Ranzani OT, Bastos LS, Gelli JG, Marchesi JF, Baiao F, Hamacher S, et al. Characterisation of the first 250 000 hospital admissions for COVID-19 in Brazil: a retrospective analysis of nationwide data. Lancet Respir Med. 2021;9:407-18.) and in other countries.(66 Grasselli G, Zangrillo A, Zanella A, Antonelli M, Cabrini L, Castelli A, Cereda D, Coluccello A, Foti G, Fumagalli R, Iotti G, Latronico N, Lorini L, Merler S, Natalini G, Piatti A, Ranieri MV, Scandroglio AM, Storti E, Cecconi M, Pesenti A; COVID-19 Lombardy ICU Network. Baseline characteristics and outcomes of 1591 patients infected with SARS-CoV-2 admitted to ICUs of the Lombardy Region, Italy. JAMA. 2020;323(16):1574-81. Erratum in: JAMA. 2021;325(20):2120.,3333 Wang Y, Lu X, Li Y, Chen H, Chen T, Su N, et al. Clinical course and outcomes of 344 intensive care patients with COVID-19. Am J Respir Crit Care Med. 2020;201(11):1430-4.,3434 Richardson S, Hirsch JS, Narasimhan M, Crawford JM, McGinn T, Davidson KW: the Northwell COVID-19 Research Consortium, Barnaby DP, Becker LB, Chelico JD, Cohen SL, Cookingham J, Coppa K, Diefenbach MA, Dominello AJ, Duer-Hefele J, Falzon L, Gitlin J, Hajizadeh N, Harvin TG, Hirschwerk DA, Kim EJ, Kozel ZM, Marrast LM, Mogavero JN, Osorio GA, Qiu M, Zanos TP. Presenting characteristics, comorbidities, and outcomes among 5700 patients hospitalized with COVID-19 in the New York City area. JAMA. 2020;323(20):2052-9. Erratum in: JAMA. 2020;323(20):2098.) In a cohort study involving 254,288 patients hospitalized with COVID-19 in Brazil, Ranzani et al., demonstrated a hospital mortality rate of approximately 60% among patients admitted to the ICU and a rate of roughly 80% among patients who received mechanical ventilation.(1414 Ranzani OT, Bastos LS, Gelli JG, Marchesi JF, Baiao F, Hamacher S, et al. Characterisation of the first 250 000 hospital admissions for COVID-19 in Brazil: a retrospective analysis of nationwide data. Lancet Respir Med. 2021;9:407-18.) In a meta-analysis comprising 28 studies and 12,437 patients admitted to the ICU with COVID-19 worldwide, the reported ICU and mechanically ventilated mortality were, respectively, 28.3% and 43%.(44 Chang R, Elhusseiny KM, Yeh YC, Sun WZ. COVID-19 ICU and mechanical ventilation patient characteristics and outcomes-a systematic review and meta-analysis. PLoS One. 2021;16(2):e0246318.)

The discrepancy between the observed mortality rate in the present study and in other series may be explained by different hospital characteristics (private versus public); adopted thresholds for hospitalization and/or ICU admission; availability of resources, such as ICU beds, and limited offer of advanced respiratory support outside an ICU, or in ICUs but with resource constraints, characteristics of the ICU staff; ventilation strategies, such as the use of noninvasive ventilation and HFNC, and strategies for extra-pulmonary organ support. Furthermore, despite the different moments of COVID-19 pandemic in Brazil, the observed monthly stability on outcomes (length of stay and mortality) of COVID-19 patients reflects the hospital and ICU organization to provide the best quality of care to patients.

Patients with acute kidney injury requiring RRT had a 14-fold increase in the odds for in-hospital death, compared with COVID-19 patients who did not receive RRT. This observation is consistent with other studies, in which a significant association between acute kidney injury and increased risk of death was reported in patients with severe COVID-19.(44 Chang R, Elhusseiny KM, Yeh YC, Sun WZ. COVID-19 ICU and mechanical ventilation patient characteristics and outcomes-a systematic review and meta-analysis. PLoS One. 2021;16(2):e0246318.,3535 Hansrivijit P, Qian C, Boonpheng B, Thongprayoon C, Vallabhajosyula S, Cheungpasitporn W, et al. Incidence of acute kidney injury and its association with mortality in patients with COVID-19: a meta-analysis. J Investig Med. 2020;68(7):1261-70.,3636 Cheng Y, Luo R, Wang K, Zhang M, Wang Z, Dong L, et al. Kidney disease is associated with in-hospital death of patients with COVID-19. Kidney Int. 2020;97(5):829-38.) Additionally, we found that almost half of the deceased patients underwent RRT, which is also similar to other studies.(3434 Richardson S, Hirsch JS, Narasimhan M, Crawford JM, McGinn T, Davidson KW: the Northwell COVID-19 Research Consortium, Barnaby DP, Becker LB, Chelico JD, Cohen SL, Cookingham J, Coppa K, Diefenbach MA, Dominello AJ, Duer-Hefele J, Falzon L, Gitlin J, Hajizadeh N, Harvin TG, Hirschwerk DA, Kim EJ, Kozel ZM, Marrast LM, Mogavero JN, Osorio GA, Qiu M, Zanos TP. Presenting characteristics, comorbidities, and outcomes among 5700 patients hospitalized with COVID-19 in the New York City area. JAMA. 2020;323(20):2052-9. Erratum in: JAMA. 2020;323(20):2098.,3737 Lowe R, Ferrari M, Nasim-Mohi M, Jackson A, Beecham R, Veighey K, Cusack R, Richardson D, Grocott M, Levett D, Dushianthan A; University Hospital Southampton Critical Care Team and the REACT COVID investigators. Clinical characteristics and outcome of critically ill COVID-19 patients with acute kidney injury: a single centre cohort study. BMC Nephrol. 2021;22(1):92.,3838 Yang X, Yu Y, Xu J, Shu H, Xia J, Liu H, et al. Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. Lancet Respir Med. 2020;8(5):475-81. Erratum in: Lancet Respir Med. 2020;8(4):e26.) The assessment of risk factors for the development of acute kidney injury, and use of RRT in the first 207 critically ill COVID-19 patients admitted to our ICU, were reported elsewhere.(3939 Doher MP, Torres de Carvalho FR, Scherer PF, Matsui TN, Ammirati AL, Caldin da Silva B, et al. Acute kidney injury and renal replacement therapy in critically Ill COVID-19 patients: risk factors and outcomes: a single-center experience in Brazil. Blood Purif. 2020:50(4-5):520-30.)

The highest in-hospital mortality rate in our study was observed in the subgroup of patients who received ECMO (approximately 65%). Reported mortality for COVID-19 patients submitted to veno-venous ECMO varied widely.(4040 Huang S, Zhao S, Luo H, Wu Z, Wu J, Xia H, et al. The role of extracorporeal membrane oxygenation in critically ill patients with COVID-19: a narrative review. BMC Pulm Med. 2021;21(1):116. Review.) For instance, the reported in-hospital death at 90 days after ECMO initiation in 1,035 patients from the Extracorporeal Life Support Organization (ELSO) registry was 37%.(4141 Barbaro RP, MacLaren G, Boonstra PS, Iwashyna TJ, Slutsky AS, Fan E, Bartlett RH, Tonna JE, Hyslop R, Fanning JJ, Rycus PT, Hyer S, Anders MM, Agerstrand CL, Hryniewicz K, Diaz R, Lorusso R, Combes A, Brodie D; Extracorporeal Life Support Organization. Extracorporeal membrane oxygenation support in COVID-19: an international cohort study of the Extracorporeal Life Support Organization registry. Lancet. 2020;396(10257):1071-8. Erratum in: Lancet. 2020;396(10257):1070.) Nevertheless, approximately one third of patients included in this study were still hospitalized, or had been discharged to another hospital or to a long-term acute care center at the time of outcome measurement.(4141 Barbaro RP, MacLaren G, Boonstra PS, Iwashyna TJ, Slutsky AS, Fan E, Bartlett RH, Tonna JE, Hyslop R, Fanning JJ, Rycus PT, Hyer S, Anders MM, Agerstrand CL, Hryniewicz K, Diaz R, Lorusso R, Combes A, Brodie D; Extracorporeal Life Support Organization. Extracorporeal membrane oxygenation support in COVID-19: an international cohort study of the Extracorporeal Life Support Organization registry. Lancet. 2020;396(10257):1071-8. Erratum in: Lancet. 2020;396(10257):1070.) Therefore, the crude mortality for COVID-19 patients who receive ECMO may be underestimated.

Our study has limitations. First, it was performed in a single ICU located in a private quaternary care hospital in Brazil. Therefore, our results may not be generalizable to other ICUs in Brazil or in other developing countries, since healthcare systems and patient characteristics may vary substantially from our cohort. Second, we did not collect detailed data on noninvasive or on ventilator management strategies. It is well established that ventilatory support for ARF patients has a major impact on outcomes.(4242 Acute Respiratory Distress Syndrome Network, Brower RG, Matthay MA, Morris A, Schoenfeld D, Thompson BT, Wheeler A. Ventilation with lower tidal volumes as compared with traditional tidal volumes for acute lung injury and the acute respiratory distress syndrome. N Engl J Med. 2000;342(18):1301-8.,4343 Guérin C, Reignier J, Richard JC, Beuret P, Gacouin A, Boulain T, Mercier E, Badet M, Mercat A, Baudin O, Clavel M, Chatellier D, Jaber S, Rosselli S, Mancebo J, Sirodot M, Hilbert G, Bengler C, Richecoeur J, Gainnier M, Bayle F, Bourdin G, Leray V, Girard R, Baboi L, Ayzac L; PROSEVA Study Group. Prone positioning in severe acute respiratory distress syndrome. N Engl J Med. 2013;368(23):2159-68.) Third, we assumed that patients discharged from hospital before 28 days were still alive at day 28. Nevertheless, discharged patients might have been readmitted elsewhere or could have died after discharge. Finally, we did not assess whether the new SARS-CoV-2 variants affected outcomes in our cohort of patients compared to previously circulating variants in Brazil.(4444 Faria NR, Mellan TA, Whittaker C, Claro IM, Candido DS, Mishra S, et al. Genomics and epidemiology of the P.1 SARS-CoV-2 lineage in Manaus, Brazil. Science. 2021;372(6544):815-21.,4545 Resende PC, Gräf T, Paixão AC, Appolinario L, Lopes RS, Mendonça AC, et al. A Potential SARS-CoV-2 Variant of Interest (VOI) Harboring Mutation E484K in the Spike Protein Was Identified within Lineage B.1.1.33 Circulating in Brazil. Viruses. 2021;13(5):724.)

CONCLUSION

Patients with severe COVID-19 admitted to the intensive care unit had considerable morbidity and mortality, requiring substantial organ support, and a prolonged intensive care unit and hospital stay. The volume and severity of COVID-19 patients requiring intensive care unit admission are a great burden for the Brazilian health care system. Therefore, the results of this study may be of interest to be used as benchmark, or to support decisions concerning delivery of healthcare services and prognosis for COVID-19 patients demanding intensive care.

ACKNOWLEDGMENTS

We thank the intensive care unit physicians, nursing staff, physical therapists, and all members of the multidisciplinary team of Hospital Israelita Albert Einstein, who managed patients during the SARS-CoV-2 pandemic. The authors thank Helena Spalic for proofreading this manuscript.

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Publication Dates

  • Publication in this collection
    03 Dec 2021
  • Date of issue
    2021

History

  • Received
    08 May 2021
  • Accepted
    03 Aug 2021
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