Anticoagulant Treatment in Severe ARDS COVID-19 Patients

Patients with COVID-19 may complicate their evolution with thromboembolic events. Incidence of thromboembolic complications are high and also, patients with the critically-ill disease showed evidence of microthrombi and microangiopathy in the lung probably due to endothelial damage by directly and indirectly injured endothelial and epithelial cells. Pulmonary embolism, deep venous thrombosis and arterial embolism were reported in patients with COVID-19, and several analytical abnormal coagulation parameters have been described as well. D-dimer, longer coagulation times and lower platelet counts have been associated with poor outcomes. The use of anticoagulation or high doses of prophylactic heparin is controversial. Despite the use of anticoagulation or high prophylactic dose of heparin have been associated with better outcomes in observational studies, only in patients with non-critically ill disease benefits for anticoagulation was observed. In critically-ill patient, anticoagulation was not associated with better outcomes. Other measures such as antiplatelet therapy, fibrinolytic therapy or nebulized anticoagulants are being studied in ongoing clinical trials

Evaluation of the Kinetics of Pancreatic Stone Protein as a Predictor of Ventilator-Associated Pneumonia

Ventilator-associated pneumonia (VAP) is a severe condition. Early and adequate antibiotic treatment is the most important strategy for improving prognosis. Pancreatic Stone Protein (PSP) has been described as a biomarker that increases values 3-4 days before the clinical diagnosis of nosocomial sepsis in different clinical settings. We hypothesized that serial measures of PSP and its kinetics allow for an early diagnosis of VAP. METHODS: The BioVAP study was a prospective observational study designed to evaluate the role of biomarker dynamics in the diagnosis of VAP. To determine the association between repeatedly measured PSP and the risk of VAP, we used joint models for longitudinal and time-to-event data. RESULTS: Of 209 patients, 43 (20.6%) patients developed VAP, with a median time of 4 days. Multivariate joint models with PSP, CRP, and PCT did not show an association between biomarkers and VAP for the daily absolute value, with a hazard ratio (HR) for PSP of 1.01 (95% credible interval: 0.97 to 1.05), for CRP of 1.00 (0.83 to 1.22), and for PCT of 0.95 (0.82 to 1.08). The daily change of biomarkers provided similar results, with an HR for PSP of 1.15 (0.94 to 1.41), for CRP of 0.76 (0.35 to 1.58), and for PCT of 0.77 (0.40 to 1.45). CONCLUSION: Neither absolute PSP values nor PSP kinetics alone nor in combination with other biomarkers were useful in improving the prediction diagnosis accuracy in patients with VAP. Clinical Trial Registration: Registered retrospectively on August 3rd, 2012. NCT02078999

Evaluation of the Kinetics of Pancreatic Stone Protein as a Predictor of Ventilator-Associated Pneumonia

Funding Information: This study was partially supported by Abionic, CIBERES, and Research and Innovation Institute Parc Tauli (I3PT). A.C. acknowledges receiving financial support from Instituto de Salud Carlos III (ISCIII; Sara Borrell 2021: CD21/00087). The funding sources had no role in the design and conduct of the study; the collection, management, analysis, and interpretation of the data; the preparation, review, or approval of the manuscript; or in the decision to submit the manuscript for publication. Publisher Copyright: © 2023 by the authors.BACKGROUND: Ventilator-associated pneumonia (VAP) is a severe condition. Early and adequate antibiotic treatment is the most important strategy for improving prognosis. Pancreatic Stone Protein (PSP) has been described as a biomarker that increases values 3–4 days before the clinical diagnosis of nosocomial sepsis in different clinical settings. We hypothesized that serial measures of PSP and its kinetics allow for an early diagnosis of VAP. METHODS: The BioVAP study was a prospective observational study designed to evaluate the role of biomarker dynamics in the diagnosis of VAP. To determine the association between repeatedly measured PSP and the risk of VAP, we used joint models for longitudinal and time-to-event data. RESULTS: Of 209 patients, 43 (20.6%) patients developed VAP, with a median time of 4 days. Multivariate joint models with PSP, CRP, and PCT did not show an association between biomarkers and VAP for the daily absolute value, with a hazard ratio (HR) for PSP of 1.01 (95% credible interval: 0.97 to 1.05), for CRP of 1.00 (0.83 to 1.22), and for PCT of 0.95 (0.82 to 1.08). The daily change of biomarkers provided similar results, with an HR for PSP of 1.15 (0.94 to 1.41), for CRP of 0.76 (0.35 to 1.58), and for PCT of 0.77 (0.40 to 1.45). CONCLUSION: Neither absolute PSP values nor PSP kinetics alone nor in combination with other biomarkers were useful in improving the prediction diagnosis accuracy in patients with VAP. Clinical Trial Registration: Registered retrospectively on August 3rd, 2012. NCT02078999.publishersversionpublishe

Clustering COVID-19 ARDS patients through the first days of ICU admission. An analysis of the CIBERESUCICOVID Cohort

Background Acute respiratory distress syndrome (ARDS) can be classified into sub-phenotypes according to different inflammatory/clinical status. Prognostic enrichment was achieved by grouping patients into hypoinflammatory or hyperinflammatory sub-phenotypes, even though the time of analysis may change the classification according to treatment response or disease evolution. We aimed to evaluate when patients can be clustered in more than 1 group, and how they may change the clustering of patients using data of baseline or day 3, and the prognosis of patients according to their evolution by changing or not the cluster.Methods Multicenter, observational prospective, and retrospective study of patients admitted due to ARDS related to COVID-19 infection in Spain. Patients were grouped according to a clustering mixed-type data algorithm (k-prototypes) using continuous and categorical readily available variables at baseline and day 3.Results Of 6205 patients, 3743 (60%) were included in the study. According to silhouette analysis, patients were grouped in two clusters. At baseline, 1402 (37%) patients were included in cluster 1 and 2341(63%) in cluster 2. On day 3, 1557(42%) patients were included in cluster 1 and 2086 (57%) in cluster 2. The patients included in cluster 2 were older and more frequently hypertensive and had a higher prevalence of shock, organ dysfunction, inflammatory biomarkers, and worst respiratory indexes at both time points. The 90-day mortality was higher in cluster 2 at both clustering processes (43.8% [n = 1025] versus 27.3% [n = 383] at baseline, and 49% [n = 1023] versus 20.6% [n = 321] on day 3). Four hundred and fifty-eight (33%) patients clustered in the first group were clustered in the second group on day 3. In contrast, 638 (27%) patients clustered in the second group were clustered in the first group on day 3.Conclusions During the first days, patients can be clustered into two groups and the process of clustering patients may change as they continue to evolve. This means that despite a vast majority of patients remaining in the same cluster, a minority reaching 33% of patients analyzed may be re-categorized into different clusters based on their progress. Such changes can significantly impact their prognosis

Bioengineered extracellular vesicles : future of precision medicine for sepsis

Sepsis is a syndromic response to infection and is frequently a final common pathway to death from many infectious diseases worldwide. The complexity and high heterogeneity of sepsis hinder the possibility to treat all patients with the same protocol, requiring personalized management. The versatility of extracellular vesicles (EVs) and their contribution to sepsis progression bring along promises for one-to-one tailoring sepsis treatment and diagnosis. In this article, we critically review the endogenous role of EVs in sepsis progression and how current advancements have improved EVs-based therapies toward their translational future clinical application, with innovative strategies to enhance EVs effect. More complex approaches, including hybrid and fully synthetic nanocarriers that mimic EVs, are also discussed. Several pre-clinical and clinical studies are examined through the review to offer a general outlook of the current and future perspectives of EV-based sepsis diagnosis and treatment