Immunothrombosis and COVID-19 ‒ a nested post-hoc analysis from a 3,186 patient cohort in a Latin American public reference hospital

Objective COVID-19 is associated with an elevated risk of thromboembolism and excess mortality. Difficulties with best anticoagulation practices and their implementation motivated the current analysis of COVID-19 patients who developed Venous Thromboembolism (VTE). Method This is a post-hoc analysis of a COVID-19 cohort, described in an economic study already published. The authors analyzed a subset of patients with confirmed VTE. We described the characteristics of the cohort, such as demographics, clinical status, and laboratory results. We tested differences amid two subgroups of patients, those with VTE or not, with the competitive risk Fine and Gray model. Results Out of 3,186 adult patients with COVID-19, 245 (7.7%) were diagnosed with VTE, 174 (5.4%) of them during admission to the hospital. Four (2.3% of these 174) did not receive prophylactic anticoagulation and 19 (11%) discontinued anticoagulation for at least 3 days, resulting in 170 analyzed. During the first week of hospitalization, the laboratory most altered results were C-reactive protein and D-dimer. Patients with VTE were more critical, had a higher mortality rate, worse SOFA score, and, on average, 50% longer hospital stay. Conclusion Proven VTE incidence in this severe COVID-19 cohort was 7.7%, despite 87% of them complying completely with VTE prophylaxis. The clinician must be aware of the diagnosis of VTE in COVID-19, even in patients receiving proper prophylaxis.

Clinical outcomes and lung mechanics characteristics between COVID-19 and non-COVID-19-associated acute respiratory distress syndrome: a propensity score analysis of two major randomized trials. / Desfechos clínicos e características da mecânica pulmonar entre a síndrome do desconforto respiratório agudo associada à COVID-19 e a não associada à COVID-19: uma análise de escore de propensão de dois importantes ensaios randomizados.

OBJECTIVE: To compare the lung mechanics and outcomes between COVID-19-associated acute respiratory distress syndrome and non-COVID-19-associated acute respiratory distress syndrome. METHODS: We combined data from two randomized trials in acute respiratory distress syndrome, one including only COVID-19 patients and the other including only patients without COVID-19, to determine whether COVID-19-associated acute respiratory distress syndrome is associated with higher 28-day mortality than non-COVID-19 acute respiratory distress syndrome and to examine the differences in lung mechanics between these two types of acute respiratory distress syndrome. RESULTS: A total of 299 patients with COVID-19-associated acute respiratory distress syndrome and 1,010 patients with non-COVID-19-associated acute respiratory distress syndrome were included in the main analysis. The results showed that non-COVID-19 patients used higher positive end-expiratory pressure (12.5cmH2O; SD 3.2 versus 11.7cmH2O SD 2.8; p < 0.001), were ventilated with lower tidal volumes (5.8mL/kg; SD 1.0 versus 6.5mL/kg; SD 1.2; p < 0.001) and had lower static respiratory compliance adjusted for ideal body weight (0.5mL/cmH2O/kg; SD 0.3 versus 0.6mL/cmH2O/kg; SD 0.3; p = 0.01). There was no difference between groups in 28-day mortality (52.3% versus 58.9%; p = 0.52) or mechanical ventilation duration in the first 28 days among survivors (13 [IQR 5 - 22] versus 12 [IQR 6 - 26], p = 0.46). CONCLUSION: This analysis showed that patients with non-COVID-19-associated acute respiratory distress syndrome have different lung mechanics but similar outcomes to COVID-19-associated acute respiratory distress syndrome patients. After propensity score matching, there was no difference in lung mechanics or outcomes between groups.

OBJETIVO: Comparar a mecânica pulmonar e os desfechos entre a síndrome do desconforto respiratório agudo associada à COVID-19 e a síndrome do desconforto respiratório agudo não associada à COVID-19. MÉTODOS: Combinamos dados de dois ensaios randomizados sobre a síndrome do desconforto respiratório agudo, um incluindo apenas pacientes com COVID-19 e o outro incluindo apenas pacientes sem COVID-19, para determinar se a síndrome do desconforto respiratório agudo associada à COVID-19 está associada à maior mortalidade aos 28 dias do que a síndrome do desconforto respiratório agudo não associada à COVID-19 e também examinar as diferenças na mecânica pulmonar entre esses dois tipos de síndrome do desconforto respiratório agudo. RESULTADOS: Foram incluídos na análise principal 299 pacientes com síndrome do desconforto respiratório agudo associada à COVID-19 e 1.010 pacientes com síndrome do desconforto respiratório agudo não associada à COVID-19. Os resultados mostraram que os pacientes sem COVID-19 utilizaram pressão positiva expiratória final mais alta (12,5cmH2O; DP 3,2 versus 11,7cmH2O; DP 2,8; p < 0,001), foram ventilados com volumes correntes mais baixos (5,8mL/kg; DP 1,0 versus 6,5mL/kg; DP 1,2; p < 0,001) e apresentaram menor complacência respiratória estática ajustada para o peso ideal (0,5mL/cmH2O/kg; DP 0,3 versus 0,6mL/cmH2O/kg; DP 0,3; p = 0,01). Não houve diferença entre os grupos quanto à mortalidade aos 28 dias (52,3% versus 58,9%; p = 0,52) ou à duração da ventilação mecânica nos primeiros 28 dias entre os sobreviventes (13 [IQ 5 - 22] dias versus 12 [IQ 6 - 26] dias; p = 0,46). CONCLUSÃO: Esta análise mostrou que os pacientes com síndrome do desconforto respiratório agudo não associada à COVID-19 têm mecânica pulmonar diferente, mas desfechos semelhantes aos dos pacientes com síndrome do desconforto respiratório agudo associada à COVID-19. Após pareamento por escore de propensão, não houve diferença na mecânica pulmonar e nem nos desfechos entre os grupos.

Association between obesity and COVID-19 mortality and length of stay in intensive care unit patients in Brazil: a retrospective cohort study.

The present study aimed to evaluate the association between obesity and COVID-19 mortality and length of stay in ICU patients, and how these associations were modified by age groups. We performed a retrospective multicenter cohort study with data obtained from a hospital-based registry. The sample consisted of 8183 ICU hospitalized patients who tested positive for SARS-CoV-2. Cox proportional models were used to evaluate the association between BMI categories and COVID-19 mortality and generalized linear models for the length of stay in the ICU. After adjusting for confounders, those in the younger group with severe obesity had an increased risk of COVID-19 mortality compared to those with normal/overweight (HR 1.27; 95% CI 1.01-1.61). An increased risk of death was also observed for patients with underweight (HR 3.74; 95% CI 1.39-10.07). For patients aged ≥ 60 year, mild/moderate obesity was associated with reduced mortality risk (HR 0.87; 95% CI 0.78-0.97). For the age group < 60 year, the length of stay in ICU for those patients with severe obesity was 35% higher compared to the normal/overweight category (eß 1.35; 95% CI 1.21-1.51). Conversely, for the survivors in the underweight category, the length of stay in ICU was 51% lower compared to the normal/overweight group (eß 0.49; 95% CI 0.31-0.78). In the age group ≥ 60 year, mild/moderate obesity was associated with an increased length of stay in the ICU (eß 1.10; 95% CI 1.01-1.21), adjusting for confounders. These findings could be helpful for health professionals to identify subgroups at higher risk for worse outcomes.

Use and misuse of biomarkers and the role of D-dimer and C-reactive protein in the management of COVID-19: A post-hoc analysis of a prospective cohort study.

OBJECTIVE: Coronavirus disease 2019 (COVID-19) is associated with high mortality among hospitalized patients and incurs high costs. Severe acute respiratory syndrome coronavirus 2 infection can trigger both inflammatory and thrombotic processes, and these complications can lead to a poorer prognosis. This study aimed to evaluate the association and temporal trends of D-dimer and C-reactive protein (CRP) levels with the incidence of venous thromboembolism (VTE), hospital mortality, and costs among inpatients with COVID-19. METHODS: Data were extracted from electronic patient records and laboratory databases. Crude and adjusted associations for age, sex, number of comorbidities, Sequential Organ Failure Assessment score at admission, and D-dimer or CRP logistic regression models were used to evaluate associations. RESULTS: Between March and June 2020, COVID-19 was documented in 3,254 inpatients. The D-dimer level ≥4,000 ng/mL fibrinogen equivalent unit (FEU) mortality odds ratio (OR) was 4.48 (adjusted OR: 1.97). The CRP level ≥220 mg/dL OR for death was 7.73 (adjusted OR: 3.93). The D-dimer level ≥4,000 ng/mL FEU VTE OR was 3.96 (adjusted OR: 3.26). The CRP level ≥220 mg/dL OR for VTE was 2.71 (adjusted OR: 1.92). All these analyses were statistically significant (p<0.001). Stratified hospital costs demonstrated a dose-response pattern. Adjusted D-dimer and CRP levels were associated with higher mortality and doubled hospital costs. In the first week, elevated D-dimer levels predicted VTE occurrence and systemic inflammatory harm, while CRP was a hospital mortality predictor. CONCLUSION: D-dimer and CRP levels were associated with higher hospital mortality and a higher incidence of VTE. D-dimer was more strongly associated with VTE, although its discriminative ability was poor, while CRP was a stronger predictor of hospital mortality. Their use outside the usual indications should not be modified and should be discouraged.

Bedside clinical data subphenotypes of critically ill COVID-19 patients: a cohort study. / Subfenótipos baseados em dados clínicos de beira-leito de pacientes críticos com COVID-19: um estudo de coorte.

OBJECTIVE: To identify more severe COVID-19 presentations. METHODS: Consecutive intensive care unit-admitted patients were subjected to a stepwise clustering method. RESULTS: Data from 147 patients who were on average 56 ± 16 years old with a Simplified Acute Physiological Score 3 of 72 ± 18, of which 103 (70%) needed mechanical ventilation and 46 (31%) died in the intensive care unit, were analyzed. From the clustering algorithm, two well-defined groups were found based on maximal heart rate [Cluster A: 104 (95%CI 99 - 109) beats per minute versus Cluster B: 159 (95%CI 155 - 163) beats per minute], maximal respiratory rate [Cluster A: 33 (95%CI 31 - 35) breaths per minute versus Cluster B: 50 (95%CI 47 - 53) breaths per minute], and maximal body temperature [Cluster A: 37.4 (95%CI 37.1 - 37.7)°C versus Cluster B: 39.3 (95%CI 39.1 - 39.5)°C] during the intensive care unit stay, as well as the oxygen partial pressure in the blood over the oxygen inspiratory fraction at intensive care unit admission [Cluster A: 116 (95%CI 99 - 133) mmHg versus Cluster B: 78 (95%CI 63 - 93) mmHg]. Subphenotypes were distinct in inflammation profiles, organ dysfunction, organ support, intensive care unit length of stay, and intensive care unit mortality (with a ratio of 4.2 between the groups). CONCLUSION: Our findings, based on common clinical data, revealed two distinct subphenotypes with different disease courses. These results could help health professionals allocate resources and select patients for testing novel therapies.

OBJETIVO: Identificar apresentações mais graves de COVID-19. MÉTODOS: Pacientes consecutivamente admitidos à unidade de terapia intensiva foram submetidos à análise de clusters por meio de método de explorações sequenciais. RESULTADOS: Analisamos os dados de 147 pacientes, com média de idade de 56 ± 16 anos e Simplified Acute Physiological Score 3 de 72 ± 18, dos quais 103 (70%) demandaram ventilação mecânica e 46 (31%) morreram na unidade de terapia intensiva. A partir do algoritmo de análise de clusters, identificaram-se dois grupos bem definidos, com base na frequência cardíaca máxima [Grupo A: 104 (IC95% 99 - 109) batimentos por minuto versus Grupo B: 159 (IC95% 155 - 163) batimentos por minuto], frequência respiratória máxima [Grupo A: 33 (IC95% 31 - 35) respirações por minuto versus Grupo B: 50 (IC95% 47 - 53) respirações por minuto] e na temperatura corpórea máxima [Grupo A: 37,4 (IC95% 37,1 - 37,7)ºC versus Grupo B: 39,3 (IC95% 39,1 - 39,5)ºC] durante o tempo de permanência na unidade de terapia intensiva, assim como a proporção entre a pressão parcial de oxigênio no sangue e a fração inspirada de oxigênio quando da admissão à unidade de terapia intensiva [Grupo A: 116 (IC95% 99 - 133) mmHg versus Grupo B: 78 (IC95% 63 - 93) mmHg]. Os subfenótipos foram distintos em termos de perfis inflamatórios, disfunções orgânicas, terapias de suporte, tempo de permanência na unidade de terapia intensiva e mortalidade na unidade de terapia intensiva (com proporção de 4,2 entre os grupos). CONCLUSÃO: Nossos achados, baseados em dados clínicos universalmente disponíveis, revelaram dois subfenótipos distintos, com diferentes evoluções de doença. Estes resultados podem ajudar os profissionais de saúde na alocação de recursos e seleção de pacientes para teste de novas terapias.

Protective ventilation and outcomes of critically ill patients with COVID-19: a cohort study.

BACKGROUND: Approximately 5% of COVID-19 patients develop respiratory failure and need ventilatory support, yet little is known about the impact of mechanical ventilation strategy in COVID-19. Our objective was to describe baseline characteristics, ventilatory parameters, and outcomes of critically ill patients in the largest referral center for COVID-19 in Sao Paulo, Brazil, during the first surge of the pandemic. METHODS: This cohort included COVID-19 patients admitted to the intensive care units (ICUs) of an academic hospital with 94 ICU beds, a number expanded to 300 during the pandemic as part of a state preparedness plan. Data included demographics, advanced life support therapies, and ventilator parameters. The main outcome was 28-day survival. We used a multivariate Cox model to test the association between protective ventilation and survival, adjusting for PF ratio, pH, compliance, and PEEP. RESULTS: We included 1503 patients from March 30 to June 30, 2020. The mean age was 60 ± 15 years, and 59% were male. During 28-day follow-up, 1180 (79%) patients needed invasive ventilation and 666 (44%) died. For the 984 patients who were receiving mechanical ventilation in the first 24 h of ICU stay, mean tidal volume was 6.5 ± 1.3 mL/kg of ideal body weight, plateau pressure was 24 ± 5 cmH2O, respiratory system compliance was 31.9 (24.4-40.9) mL/cmH2O, and 82% of patients were ventilated with protective ventilation. Noninvasive ventilation was used in 21% of patients, and prone, in 36%. Compliance was associated with survival and did not show a bimodal pattern that would support the presence of two phenotypes. In the multivariable model, protective ventilation (aHR 0.73 [95%CI 0.57-0.94]), adjusted for PF ratio, compliance, PEEP, and arterial pH, was independently associated with survival. CONCLUSIONS: During the peak of the epidemic in Sao Paulo, critically ill patients with COVID-19 often required mechanical ventilation and mortality was high. Our findings revealed an association between mechanical ventilation strategy and mortality, highlighting the importance of protective ventilation for patients with COVID-19.

Characteristics and outcomes of patients with COVID-19 admitted to the ICU in a university hospital in São Paulo, Brazil - study protocol

OBJECTIVES: We designed a cohort study to describe characteristics and outcomes of patients with coronavirus disease (COVID-19) admitted to the intensive care unit (ICU) in the largest public hospital in Sao Paulo, Brazil, as Latin America becomes the epicenter of the pandemic. METHODS: This is the protocol for a study being conducted at an academic hospital in Brazil with 300 adult ICU beds dedicated to COVID-19 patients. We will include adult patients admitted to the ICU with suspected or confirmed COVID-19 during the study period. The main outcome is ICU survival at 28 days. Data will be collected prospectively and retrospectively by trained investigators from the hospital's electronic medical records, using an electronic data capture tool. We will collect data on demographics, comorbidities, severity of disease, and laboratorial test results at admission. Information on the need for advanced life support and ventilator parameters will be collected during ICU stay. Patients will be followed up for 28 days in the ICU and 60 days in the hospital. We will plot Kaplan-Meier curves to estimate ICU and hospital survival and perform survival analysis using the Cox proportional hazards model to identify the main risk factors for mortality. ClinicalTrials.gov: NCT04378582. RESULTS: We expect to include a large sample of patients with COVID-19 admitted to the ICU and to be able to provide data on admission characteristics, use of advanced life support, ICU survival at 28 days, and hospital survival at 60 days. CONCLUSIONS: This study will provide epidemiological data about critically ill patients with COVID-19 in Brazil, which could inform health policy and resource allocation in low- and middle-income countries.

Characteristics and outcomes of patients with COVID-19 admitted to the ICU in a university hospital in São Paulo, Brazil - study protocol.

OBJECTIVES: We designed a cohort study to describe characteristics and outcomes of patients with coronavirus disease (COVID-19) admitted to the intensive care unit (ICU) in the largest public hospital in Sao Paulo, Brazil, as Latin America becomes the epicenter of the pandemic. METHODS: This is the protocol for a study being conducted at an academic hospital in Brazil with 300 adult ICU beds dedicated to COVID-19 patients. We will include adult patients admitted to the ICU with suspected or confirmed COVID-19 during the study period. The main outcome is ICU survival at 28 days. Data will be collected prospectively and retrospectively by trained investigators from the hospital's electronic medical records, using an electronic data capture tool. We will collect data on demographics, comorbidities, severity of disease, and laboratorial test results at admission. Information on the need for advanced life support and ventilator parameters will be collected during ICU stay. Patients will be followed up for 28 days in the ICU and 60 days in the hospital. We will plot Kaplan-Meier curves to estimate ICU and hospital survival and perform survival analysis using the Cox proportional hazards model to identify the main risk factors for mortality. ClinicalTrials.gov: NCT04378582. RESULTS: We expect to include a large sample of patients with COVID-19 admitted to the ICU and to be able to provide data on admission characteristics, use of advanced life support, ICU survival at 28 days, and hospital survival at 60 days. CONCLUSIONS: This study will provide epidemiological data about critically ill patients with COVID-19 in Brazil, which could inform health policy and resource allocation in low- and middle-income countries.