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BackgroundAlmost two years since the onset of the COVID-19 pandemic no predictive algorithm has been generally adopted, nor new tests identified to improve the prediction and management of SARS-CoV-2 infection. MethodsRetrospective observational analysis of the predictive performance of clinical parameters and laboratory tests in hospitalised patients with COVID-19. Outcomes were 28-day survival and maximal severity in a cohort of 1,579 patients and two validation cohorts of 598 and 434 patients. A pilot study conducted in a patient subgroup measured 17 cytokines and 27 lymphocyte phenotypes to explore additional predictive laboratory tests. Findings1) Despite a strong association of 22 clinical and laboratory variables with the outcomes, their joint prediction power was limited due to redundancy. 2) Eight variables: age, comorbidity index, oxygen saturation to fraction of inspired oxygen ratio, neutrophil-lymphocyte ratio, C-reactive protein, aspartate aminotransferase/alanine aminotransferase ratio, fibrinogen, and glomerular filtration rate captured most of the statistical predictive power. 3) The interpretation of clinical and laboratory variables was improved by grouping them in categories. 4) Age and organ damage-related tests were the best predictors of survival, and inflammatory-related tests were the best predictors of severity. 5) The pilot study identified several immunological tests (including chemokine ligand 10, chemokine ligand 2, and interleukin 1 receptor antagonist), that performed better than currently used tests. ConclusionsCurrently used tests for clinical management of COVID-19 patients are of limited predictive value due to redundancy, as all measure aspects of two major processes: inflammation, and organ damage. There are no independent predictors based on the quality of the nascent adaptive immune response. Understanding the limitations of current tests would improve their interpretation and simplify clinical management protocols. A systematic search for better biomarkers is urgent and feasible. This study was funded by Instituto de Salud Carlos III, Madrid, Spain, grants COV20/00416, Cov20/00654 and COV20/00388 to R.P-B, ATS and JBM respectively and co-financed by the European Regional Development Fund (ERDF). DA-S is recipient of a doctoral fellowship from the Vall dHebron Research Institute, Barcelona, Spain. ASM was supported by a postdoctoral grant "Juan Rodes" (JR18/00022) from Instituto de Salud Carlos III through the Ministry of Economy and Competitiveness, Spain
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ObjectiveTo develop and validate a rapid scoring system at hospital admission for predicting in-hospital mortality in patients hospitalized with coronavirus disease 19 (COVID-19), and to compare this score with other existing ones. DesignCohort study SettingThe Brazilian COVID-19 Registry has been conducted in 36 Brazilian hospitals in 17 cities. Logistic regression analysis was performed to develop a prediction model for in-hospital mortality, based on the 3978 patients that were admitted between March-July, 2020. The model was then validated in the 1054 patients admitted during August-September, as well as in an external cohort of 474 Spanish patients. ParticipantsConsecutive symptomatic patients ([≥]18 years old) with laboratory confirmed COVID-19 admitted to participating hospitals. Patients who were transferred between hospitals and in whom admission data from the first hospital or the last hospital were not available were excluded, as well those who were admitted for other reasons and developed COVID-19 symptoms during their stay. Main outcome measuresIn-hospital mortality ResultsMedian (25th-75th percentile) age of the model-derivation cohort was 60 (48-72) years, 53.8% were men, in-hospital mortality was 20.3%. The validation cohorts had similar age distribution and in-hospital mortality. From 20 potential predictors, seven significant variables were included in the in-hospital mortality risk score: age, blood urea nitrogen, number of comorbidities, C-reactive protein, SpO2/FiO2 ratio, platelet count and heart rate. The model had high discriminatory value (AUROC 0.844, 95% CI 0.829 to 0.859), which was confirmed in the Brazilian (0.859) and Spanish (0.899) validation cohorts. Our ABC2-SPH score showed good calibration in both Brazilian cohorts, but, in the Spanish cohort, mortality was somewhat underestimated in patients with very high (>25%) risk. The ABC2-SPH score is implemented in a freely available online risk calculator (https://abc2sph.com/). ConclusionsWe designed and validated an easy-to-use rapid scoring system based on characteristics of COVID-19 patients commonly available at hospital presentation, for early stratification for in-hospital mortality risk of patients with COVID-19. Summary boxesWhat is already known on this topic? O_LIRapid scoring systems may be very useful for fast and effective assessment of COVID-19 patients in the emergency department. C_LIO_LIThe majority of available scores have high risk of bias and lack benefit to clinical decision making. C_LIO_LIDerivation and validation studies in low- and middle-income countries, including Latin America, are scarce. C_LI What this study adds O_LIABC2-SPH employs seven well defined variables, routinely assessed upon hospital presentation: age, number of comorbidities, blood urea nitrogen, C reactive protein, Spo2/FiO2 ratio, platelets and heart rate. C_LIO_LIThis easy-to-use risk score identified four categories at increasing risk of death with a high level of accuracy, and displayed better discrimination ability than other existing scores. C_LIO_LIA free web-based calculator is available and may help healthcare practitioners to estimate the expected risk of mortality for patients at hospital presentation. C_LI
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BackgroundModulation of the immune system to prevent lung injury is being widely used against the new coronavirus disease (COVID-19) despite the scarcity of evidence. MethodsWe report the preliminary results from the Vall dHebron prospective cohort study at Vall dHebron University Hospital, in Barcelona (Spain), including all consecutive patients who had a confirmed infection with the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and who were treated with tocilizumab until March 25th. The primary endpoint was mortality at 7 days after tocilizumab administration. Secondary endpoints were admission to the intensive care unit, development of ARDS and respiratory insufficiency among others. Results82 patients with COVID-19 received at least one dose of tocilizumab. The mean ({+/-} SD) age was 59.1 (19.8) years, 63% were male, 22% were of non-Spanish ancestry, and the median (IQR) age-adjusted Charlson index at baseline was 3 (1-4) points. Respiratory failure and ARDS developed in 62 (75.6%) and 45 (54.9%) patients, respectively. Median time from symptom onset to ARDS development was 8 (5-11) days. The median time from symptom onset to the first dose of tocilizumab was 9 (7-11) days. Mortality at 7 days was 26.8%. Hazard ratio for mortality was 3.3; 95% CI, 1.3 to 8.5 (age-adjusted hazard ratio for mortality 2.1; 95% CI, 0.8 to 5.8) if tocilizumab was administered after the onset of ARDS. ConclusionTime from lung injury onset to tocilizumab administration may be critical to patient recovery. Our preliminary data could inform bedside decisions until more data from clinical trials becomes available. Summary of the articles main pointIn patient with COVID-19 and lung injury, time from lung injury onset to tocilizumab administration may be critical to patient recovery. Early administration of host-directed therapies may improve patient outcome.
