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BACKGROUND: The use of convalescent plasma (CP) has been considered for its immunological mechanisms that could benefit patients in moderate and severe stages of COVID-19. This study evaluated the safety and efficacy of the use of donor CP for COVID-19. MATERIAL AND METHODS: A double-blind, randomized controlled clinical trial was conducted from May to October 2020. Thirty-nine participants with moderate (II) and severe (III) stages of COVID-19 confirmed by RT-PCR were included. The study randomization rate was set at 3:1. CPs were chosen for application with a neutralizing antibody titer of ≥1:32. RESULTS: We observed a significantly lower 21-day post-transfusion mortality HR: 0.17 (95.0% CI [0.07-0.45, p < 0.001]) in the group receiving CP compared with the control group; protective units (PU) in the group receiving convalescent plasma after seven days were significantly higher (512 (32-16,384) vs. 96 (32-256), p = 0.01); the PAO2/FIO2 index showed a significant improvement in the group receiving CP (251.01 (109.4) vs. 109.2 (62.4), p < 0.001, in the control group). CONCLUSION: CP is safe and effective, as it decreased mortality in the CP group compared with the control group.
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Introduction: The enzyme lactate dehydrogenase (LDH) is a good marker of general hyperinflammation correlated with mortality for COVID-19, and is therefore used in prognosis tools. In a current COVID-19 clinical randomized trial (CRT), the blood level of LDH was selected as an inclusion criterion. However, LDH decreased during the pandemic; hence, the impact of this decrease on the prognostic value of LDH for mortality was evaluated. Methods: Data on LDH levels in 843 patients were obtained and analyzed. Relative risk, standard error and receiver operating characteristic curves were calculated for two cutoff values. Results: Relative risk lost validity and the area under the curve narrowed by trimester during the pandemic. Conclusion: The progressive decrease in LDH impacted the capacity to predict mortality in COVID-19. More studies are needed to validate this finding and its implications.
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Since the report of the first case of COVID-19 in Wuhan, China, on December 31, 2019, several associated thrombotic complications have been reported, mainly venous thromboembolic events, and myocardial infarctions, in addition to peripheral arterial thrombosis and cerebral vascular events, which have been attributed to a hypercoagulable state. We aimed to know the prevalence and prognostic biomarkers in patients with pulmonary thromboembolism (PE) and SARS Cov-2 pneumonia. Hospitalized patients with SARS Cov-2 pneumonia who have had clinical, biomarker, and imaging data (chest angiography) of pulmonary thromboembolism were included. Descriptive statistics and prevalence rates were calculated. For the analysis between the groups, the paired Student's t and the Wilcoxon test were performed. CT angiography was performed on 26 patients at our institution, with a diagnosis of severe pneumonia secondary to SARS-CoV2. 9 of the patients (34.6%) had a venous thromboembolic disease. Type 2 DM was the most frequent comorbidity up to 55.5% of the total; it was followed by obesity and overweight in 55.5%, and in third place, by systemic arterial hypertension in 33.3% of the cases, 1 (11.1%) patient had chronic kidney disease and 1 (11.1%) patient with a history of cancer, only 1 patient met criteria and was treated with thrombolysis. 6 (66.6%) of the patients had segmental PE, 3 (33.3%) patients had subsegmental PE, and 4 (44.4%) patients presented pulmonary infarction.
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AIM: Coronavirus disease (COVID-19) ranges from mild clinical phenotypes to life-threatening conditions like severe acute respiratory syndrome (SARS). It has been suggested that early liver injury in these patients could be a risk factor for poor outcome. We aimed to identify early biochemical predictive factors related to severe disease development with intensive care requirements in patients with COVID-19. METHODS: Data from COVID-19 patients were collected at admission time to our hospital. Differential biochemical factors were identified between seriously ill patients requiring intensive care unit (ICU) admission (ICU patients) versus stable patients without the need for ICU admission (non-ICU patients). Multiple linear regression was applied, then a predictive model of severity called Age-AST-D dimer (AAD) was constructed (n = 166) and validated (n = 170). RESULTS: Derivation cohort: from 166 patients included, there were 27 (16.3%) ICU patients that showed higher levels of liver injury markers (P < 0.01) compared with non-ICU patients: alanine aminotrasnferase (ALT) 225.4 ± 341.2 vs. 41.3 ± 41.1, aspartate aminotransferase (AST) 325.3 ± 382.4 vs. 52.8 ± 47.1, lactic dehydrogenase (LDH) 764.6 ± 401.9 vs. 461.0 ± 185.6, D-dimer (DD) 7765 ± 9109 vs. 1871 ± 4146, and age 58.6 ± 12.7 vs. 49.1 ± 12.8. With these finding, a model called Age-AST-DD (AAD), with a cut-point of <2.75 (sensitivity = 0.797 and specificity = 0.391, c - statistic = 0.74; 95%IC: 0.62-0.86, P < 0.001), to predict the risk of need admission to ICU (OR = 5.8; 95% CI: 2.2-15.4, P = 0.001), was constructed. Validation cohort: in 170 different patients, the AAD model < 2.75 (c - statistic = 0.80 (95% CI: 0.70-0.91, P < 0.001) adequately predicted the risk (OR = 8.8, 95% CI: 3.4-22.6, P < 0.001) to be admitted in the ICU (27 patients, 15.95%). CONCLUSIONS: The elevation of AST (a possible marker of early liver injury) along with DD and age efficiently predict early (at admission time) probability of ICU admission during the clinical course of COVID-19. The AAD model can improve the comprehensive management of COVID-19 patients, and it could be useful as a triage tool to early classify patients with a high risk of developing a severe clinical course of the disease.