Recombinant human plasma gelsolin (rhu-pGSN) in a patient hospitalized with critical COVID-19 pneumonia.
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ABSTRACT:
SUBMITTER: Catteeuw JV
PROVIDER: S-EPMC8353968 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundExcessive inflammation contributes to the morbidity and mortality of severe coronavirus disease 2019 (COVID-19) pneumonia. Recombinant human plasma gelsolin (rhu-pGSN) improves disease outcomes in diverse experimental models of infectious and noninfectious inflammation.MethodsIn a blinded, randomized study, 61 subjects with documented COVID-19 pneumonia having a World Health Organization (WHO) Severity Score of 4 to 6 and evidence of a hyperinflammatory state were treated with standard care and either adjunctive rhu-pGSN 12 mg/kg or an equal volume of saline placebo given intravenously at entry, 12 hours, and 36 hours. The prespecified coprimary outcomes were survival without major respiratory, hemodynamic, or renal support on Day 14 and the incidence of serious adverse events (SAEs) during the 90-day study period.ResultsAll subjects receiving ≥1 dose of study drug were analyzed. Fifty-four of 61 subjects (88.5%) were WHO severity level 4 at entry. The proportions of subjects alive without support on Day 14 were 25 of 30 rhu-pGSN recipients (83.3%) and 27 of 31 placebo recipients (87.1%). Over the duration of the study, WHO Severity Scores improved similarly in both treatment groups. No statistically significant differences were observed between treatment groups at any time point examined. Two subjects died in each group. Numerically fewer subjects in the rhu-pGSN group had SAEs (5 subjects; 16.7%) or ≥ Grade 3 adverse events (5 subjects; 16.7%) than in the placebo group (8 subjects [25.8%] and 9 subjects [29.0%], respectively), mostly involving the lungs. Three rhu-pGSN recipients (10.0%) were intubated compared to 6 placebo recipients (19.4%).ConclusionsOverall, subjects in this study did well irrespective of treatment arm. When added to dexamethasone and remdesivir, no definitive benefit was demonstrated for rhu-pGSN relative to placebo. Safety signals were not identified after the administration of 3 doses of 12 mg/kg rhu-pGSN over 36 hours. The frequencies of SAEs and intubation were numerically fewer in the rhu-pGSN group compared with placebo.
| S-EPMC9345409 | biostudies-literature
Project description:Coronavirus disease 2019 (COVID-19) can be asymptomatic or lead to a wide spectrum of symptoms, ranging from mild upper respiratory system involvement to acute respiratory distress syndrome, multi-organ damage and death. In this study, we explored the potential of microRNAs (miRNA) in delineating patient condition and in predicting clinical outcome. Analysis of the circulating miRNA profile of COVID-19 patients, sampled at different hospitalization intervals after admission, allowed to identify miR-144-3p as a dynamically regulated miRNA in response to COVID-19.
2023-01-27 | GSE195898 | GEO
Project description:Risk of severe disease and death due to coronavirus 2019 (COVID-19) is increased in certain patient demographic groups, including those who are of advanced age, male sex, and obese body mass index. Investigations of the biological variations that contribute to this risk have been hampered by heterogeneous severity, with immunologic features of critical disease potentially obscuring differences between risk groups. To examine immune heterogeneity related to demographic risk factors, we enrolled 38 patients hospitalized with clinically homogeneous COVID-19 pneumonia – defined as oxygen saturation <94% on room air without respiratory failure, septic shock, or multiple organ dysfunction – and performed single-cell RNA-sequencing of leukocytes collected at admission. Examination of individual risk factors identified strong shifts within neutrophil and monocyte/dendritic cell compartments, revealing altered immune cell type-specific responses in higher-risk COVID-19 patient subgroups. Specifically, we found transcriptional evidence of altered neutrophil maturation in aged versus young patients and enhanced cytokine responses in monocytes/dendritic cells of male versus female patients. Such innate immune cell alterations may contribute to outcome differences linked to these risk factors. They also highlight the importance of diverse patient cohorts in studies of therapies targeting the immune response in COVID-19.
2023-10-11 | GSE236177 | GEO
Project description:The lack of available biomarkers for diagnosing and predicting different stages of coronavirus disease 2019 (COVID-19) is currently one of the main challenges that clinicians are facing. Recent evidence indicates that the plasma levels of specific miRNAs may be significantly modified in COVID-19 patients. Large-scale deep sequencing analysis of small RNA expression was performed on plasma samples from 40 patients hospitalized for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (between March and May 2020) (median 13.50 [IQR 9–24] days since symptoms initiation) and 21 healthy noninfected individuals. Patients were categorized as hospitalized not requiring oxygen therapy (n = 6), hospitalized requiring low-flow oxygen (n = 23), and hospitalized requiring high-flow oxygen support (n = 11). A total of 1218 different micro(mi)RNAs were identified. When compared with healthy noninfected donors, SARS-CoV-2 infected patients showed significantly (fold change [FC] >1.2 and adjusted p [padj] <0.05) altered expression of 190 miRNAs. The top 10 differentially expressed (DE) miRNAs were miR-122-5p, let-7b-5p, miR-146a-5p, miR-342-3p, miR-146b-5p, miR-629-5p, miR-24-3p, miR-12136, let-7a-5p, and miR-191-5p, which displayed FC and padj values ranging from 153 to 5 and 2.51 × 10-32 to 2.21 × 10-21, respectively, which unequivocally diagnosed SARS-CoV-2 infection. No differences in blood cell counts and biochemical plasma parameters, including interleukin 6, ferritin and D-dimer, were observed between COVID-19 patients on high-flow oxygen therapy, low-flow oxygen therapy, or not requiring oxygen therapy. Notably, 31 significantly deregulated miRNAs were found when patients on high- and low-flow oxygen therapy were compared. Similarly, 6 DE miRNAs were identified between patients on high flow and those not requiring oxygen therapy. SARS-CoV-2 infection generates a specific miRNA signature in hospitalized patients. Furthermore, specific miRNA profiles are associated with COVID-19 prognosis in severe patients.
2024-04-03 | GSE230092 | GEO
Project description:Background:Plasma gelsolin (pGSN) is an abundant circulating protein quickly consumed by extensive tissue damage. Marked depletion is associated with later poor outcomes in diverse clinical circumstances. Repletion with recombinant human (rhu)-pGSN in animal models of inflammation lessens mortality and morbidity. Methods:Neutropenic mice were treated with different meropenem doses ±12 mg of rhu-pGSN commencing 1 day before an intratracheal challenge with multidrug-resistant Pseudomonas aeruginosa. Survival, bacterial counts, and pulmonary pathology were compared between corresponding meropenem groups with and without rhu-pGSN. Results:Overall survival was 35/64 (55%) and 46/64 (72%) in mice given meropenem without and with rhu-pGSN, respectively (??=?17%; 95% CI, 1-34). In control mice receiving meropenem 1250 mg/kg/d where the majority died, the addition of rhu-pGSN increased survival from 5/16 (31%) to 12/16 (75%) (??=?44%; 95% CI, 13-75). Survival with minor lung injury was found in 26/64 (41%) mice receiving only meropenem, vs 38/64 (59%) in mice given meropenem plus rhu-pGSN (??=?19%; 95% CI, 2-36). Conclusions:In a series of dose-ranging experiments, both mortality and lung injury were reduced by the addition of rhu-pGSN to meropenem against carbapenem-resistant P. aeruginosa. Rhu-pGSN offers a novel candidate therapy for antibiotic-resistant pneumonia.
| S-EPMC7397834 | biostudies-literature
Project description:BackgroundAntibody-based strategies for COVID-19 have shown promise in prevention and treatment of early disease. COVID-19 convalescent plasma (CCP) has been widely used but results from randomized trials supporting its benefit in hospitalized patients with pneumonia are limited. Here, we assess the efficacy of CCP in severely ill, hospitalized adults with COVID-19 pneumonia.MethodsWe performed a randomized control trial (PennCCP2), with 80 adults hospitalized with COVID-19 pneumonia, comparing up to 2 units of locally sourced CCP plus standard care versus standard care alone. The primary efficacy endpoint was comparison of a clinical severity score. Key secondary outcomes include 14- and 28-day mortality, 14- and 28-day maximum 8-point WHO ordinal score (WHO8) score, duration of supplemental oxygenation or mechanical ventilation, respiratory SARS-CoV-2 RNA, and anti-SARS-CoV-2 antibodies.ResultsEighty hospitalized adults with confirmed COVID-19 pneumonia were enrolled at median day 6 of symptoms and day 1 of hospitalization; 60% were anti-SARS-CoV-2 antibody seronegative. Participants had a median of 3 comorbidities, including risk factors for severe COVID-19 and immunosuppression. CCP treatment was safe and conferred significant benefit by clinical severity score (median [MED] and interquartile range [IQR] 10 [5.5-30] vs. 7 [2.75-12.25], P = 0.037) and 28-day mortality (n = 10, 26% vs. n = 2, 5%; P = 0.013). All other prespecified outcome measures showed weak evidence toward benefit of CCP.ConclusionTwo units of locally sourced CCP administered early in hospitalization to majority seronegative participants conferred a significant benefit in clinical severity score and 28-day mortality. Results suggest CCP may benefit select populations, especially those with comorbidities who are treated early.Trial RegistrationClinicalTrials.gov NCT04397757.FundingUniversity of Pennsylvania.
| S-EPMC8670841 | biostudies-literature
Project description:Proteomics analysis of exosomes isolated from four temporal phases of COVID-19
2021-05-19 | PXD026091 | Pride
Project description:BackgroundTo develop machine learning classifiers at admission for predicting which patients with coronavirus disease 2019 (COVID-19) who will progress to critical illness.MethodsA total of 158 patients with laboratory-confirmed COVID-19 admitted to three designated hospitals between December 31, 2019 and March 31, 2020 were retrospectively collected. 27 clinical and laboratory variables of COVID-19 patients were collected from the medical records. A total of 201 quantitative CT features of COVID-19 pneumonia were extracted by using an artificial intelligence software. The critically ill cases were defined according to the COVID-19 guidelines. The least absolute shrinkage and selection operator (LASSO) logistic regression was used to select the predictors of critical illness from clinical and radiological features, respectively. Accordingly, we developed clinical and radiological models using the following machine learning classifiers, including naive bayes (NB), linear regression (LR), random forest (RF), extreme gradient boosting (XGBoost), adaptive boosting (AdaBoost), K-nearest neighbor (KNN), kernel support vector machine (k-SVM), and back propagation neural networks (BPNN). The combined model incorporating the selected clinical and radiological factors was also developed using the eight above-mentioned classifiers. The predictive efficiency of the models is validated using a 5-fold cross-validation method. The performance of the models was compared by the area under the receiver operating characteristic curve (AUC).ResultsThe mean age of all patients was 58.9±13.9 years and 89 (56.3%) were males. 35 (22.2%) patients deteriorated to critical illness. After LASSO analysis, four clinical features including lymphocyte percentage, lactic dehydrogenase, neutrophil count, and D-dimer and four quantitative CT features were selected. The XGBoost-based clinical model yielded the highest AUC of 0.960 [95% confidence interval (CI): 0.913-1.000)]. The XGBoost-based radiological model achieved an AUC of 0.890 (95% CI: 0.757-1.000). However, the predictive efficacy of XGBoost-based combined model was very close to that of the XGBoost-based clinical model, with an AUC of 0.955 (95% CI: 0.906-1.000).ConclusionsA XGBoost-based based clinical model on admission might be used as an effective tool to identify patients at high risk of critical illness.
| S-EPMC7947498 | biostudies-literature
Project description:Passive immunotherapy with convalescent plasma may be the only available agent during the early phases of a pandemic. Here, we report safety and efficacy of high-titer convalescent plasma for COVID-19 pneumonia. Double-blinded randomized multicenter placebo-controlled trial of adult patients hospitalized with COVID-19 pneumonia. The intervention was COVID-19 convalescent plasma and placebo was saline allocated 2:1. The primary outcome was clinical status 14 days after the intervention evaluated on a clinical ordinal scale. The trial was registered at ClinicalTrials.Gov, NCT04345289, 14/04/2020. The CCAP-2 trial was terminated prematurely due to futility. Of 147 patients randomized, we included 144 patients in the modified intention-to-treat population. The ordinal clinical status 14 days post-intervention was comparable between treatment groups (odds ratio (OR) 1.41, 95% confidence interval (CI) 0.72-2.09). Results were consistent when evaluating clinical progression on an individual level 14 days after intervention (OR 1.09; 95% CI 0.46-1.73). No significant differences in length of hospital stay, admission to ICU, frequency of severe adverse events or all-cause mortality during follow-up were found between the intervention and the placebo group. Infusion of convalescent plasma did not influence clinical progression, survival or length of hospitalization in patients with COVID-19 pneumonia.
| S-EPMC9523654 | biostudies-literature
Project description:BackgroundCoronavirus disease 2019 (Covid-19) pneumonia is often associated with hyperinflammation. Despite the disproportionate incidence of Covid-19 among underserved and racial and ethnic minority populations, the safety and efficacy of the anti-interleukin-6 receptor antibody tocilizumab in patients from these populations who are hospitalized with Covid-19 pneumonia are unclear.MethodsWe randomly assigned (in a 2:1 ratio) patients hospitalized with Covid-19 pneumonia who were not receiving mechanical ventilation to receive standard care plus one or two doses of either tocilizumab (8 mg per kilogram of body weight intravenously) or placebo. Site selection was focused on the inclusion of sites enrolling high-risk and minority populations. The primary outcome was mechanical ventilation or death by day 28.ResultsA total of 389 patients underwent randomization, and the modified intention-to-treat population included 249 patients in the tocilizumab group and 128 patients in the placebo group; 56.0% were Hispanic or Latino, 14.9% were Black, 12.7% were American Indian or Alaska Native, 12.7% were non-Hispanic White, and 3.7% were of other or unknown race or ethnic group. The cumulative percentage of patients who had received mechanical ventilation or who had died by day 28 was 12.0% (95% confidence interval [CI], 8.5 to 16.9) in the tocilizumab group and 19.3% (95% CI, 13.3 to 27.4) in the placebo group (hazard ratio for mechanical ventilation or death, 0.56; 95% CI, 0.33 to 0.97; P?=?0.04 by the log-rank test). Clinical failure as assessed in a time-to-event analysis favored tocilizumab over placebo (hazard ratio, 0.55; 95% CI, 0.33 to 0.93). Death from any cause by day 28 occurred in 10.4% of the patients in the tocilizumab group and 8.6% of those in the placebo group (weighted difference, 2.0 percentage points; 95% CI, -?5.2 to 7.8). In the safety population, serious adverse events occurred in 38 of 250 patients (15.2%) in the tocilizumab group and 25 of 127 patients (19.7%) in the placebo group.ConclusionsIn hospitalized patients with Covid-19 pneumonia who were not receiving mechanical ventilation, tocilizumab reduced the likelihood of progression to the composite outcome of mechanical ventilation or death, but it did not improve survival. No new safety signals were identified. (Funded by Genentech; EMPACTA ClinicalTrials.gov number, NCT04372186.).
| S-EPMC7781101 | biostudies-literature