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Background and Importance Antimicrobial prescribing prevalence in COVID-19 patients is estimated to be around 75%, whereas bacterial coinfection prevalence is estimated to be less than 10%. This data shows the unnecessary use of antibiotics. Aim and Objectives To compare the evolution of antimicrobial consumption in COVID-19 patients between the beginning of the pandemic and the third COVID-19 wave in our hospital. Material and Methods Observational retrospective study conducted in a tertiary care hospital during March to June 2020 and May to August 2021 in COVID-19 Intensive Care Unit (CICU) and COVID-19 medical ward (CMW) patients. We extracted antimicrobial consumption data from the Pharmacy database (Silicon) and bed-days data from Admission Service. We standardised antimicrobial consumption to defined daily doses (DDD)/100 bed-days. The descriptive analysis was performed with SPSS. We conducted a normality, an independence and a correlation test. Results An 8% decrease in global antimicrobial use was observed. However, we found a 30% decrease in CMW, and a 39% increase in CICU. The antibiotic use in the two periods showed a significance correlation (p<0,001). Conclusion and Relevance * There is a light decrease of antimicrobial prescriptions in all COVID-19 patients. * There is an important decrease in antimicrobial use in CMW and a considerable increase in CICU. * These results suggest the need for more antimicrobial stewardship programmes in CICU. (Table Presented).
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Objective: Describe actions of a nursing entity in the fight against the COVID-19 pandemic in the Brazilian Amazon Methods: Descriptive study of the type of experience report from documentary research through contemporary documents using social media and apprehension of meanings and attitudes, conducted from August to December 2020 and analyzed through the Theory of Activity. Findings: Actions related to the production of four technological products for individual protection, production of artifacts and dissemination of information were identified. Final Considerations: The actions were planned considering the scenario of the region, as well as the needs inherent to geographic access, technological scope and from the political-social training provided for in nursing education and performance using the collaborative interactions resource for the effectiveness of the actions.
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Background: The efficacy of COVID-19 convalescent plasma (CCP) as passive immunotherapy in hospitalized COVID-19 patients remains uncertain. The transfusion of a large volume of high titre CCP in recently hospitalized patients may be beneficial. Aims: To evaluate the ability CCP transfusion to improve early outcome in patients with moderate to severe COVID-19 pneumonia. Methods: The CORIPLASM study was a multicentric, open-label, Bayesian randomized, adaptive, phase 2/3 clinical trial, nested within the CORIMUNO-19 cohort, to test a superiority hypothesis. Patients 18 years or older hospitalized with COVID-19 in 14 French centers, requiring at least 3 L/min of oxygen but without mechanic ventilation assistance and a WHO Clinical progression scale [CPS, 1 to 10] of 4 or 5 were enrolled. Patients were randomly assigned (1:1) via a web-based system, according to a randomization list stratified on center, to receive usual care plus 4 units of CCP (2 units/day over 2 days) (CCP group) or usual care alone (usual care group) on day 1 and 2 post-enrollment. Primary outcomes were the proportion of patients withWHO CPS greater than 5 on the 10-point scale on day 4 and survival without ventilation or additional immunomodulatory treatment by day 14. Results: One hundred and twenty patients were recruited from April 16th 2020 and April 21th 2021 and randomly assigned to the CCP group (n = 60) and to the usual care group (n = 60) and followed up for 28 days. Immunosuppressed patients comprised 43% (26/60) and 50% (30/60) of patients in the CCP and usual care groups, respectively. Median time from symptoms onset to randomization (days) was 7.0 [interquartile range (IQR): 5.0-9.0] in the CCP group and 7.0 [IQR: 4.0- 8.5] in the usual care group. Thirteen (22%) patients in the CCP group had a WHO CPS greater than 5 at day 4 versus 8 (13%) in the usual care group (adjusted odds ratio (OR): 1.88 [95% CI: 0.71 to 5.24]. By day 14, 19 (31.6%) patients in the CCP and 20 (33.3%) patients in the usual care group had needed ventilation, additional immunomodulatory treatment or had died (adjusted HR: 1.04 [95% CI: 0.55 to 1.97]). The cumulative incidence of death was 3 (5%) in the CCP group and 8 (13%) in the usual care group at day 14 (adjusted HR: 0.40 [95% CI: 0.10 to 1.53]), and 7 (12%) in the CCP group and 12 (20%) in the usual care group at day 28 (adjusted HR: 0.51 [95% CI: 0.20 to 1.32]). Frequency of severe adverse events did not differ significantly between both treatment arms. Subgroup analysis revealed that mortality at day 28 was mostly observed in the immunosuppressed patients (15/56 vs. 4/64) and that CCP was associated with less mortality in these patients (4/26 in the CCP group vs. 11/30 in the usual care group)(HR: 0.36 [95% CI: 0.14-0.97]). Summary/Conclusions: CCP treatment did not improve early outcome in patients with moderate-to-severe COVID-19 pneumonia. CCP-associated early respiratory worsening as well as CCP-associated reduced D14 and D28 mortality were observed, while not reaching statistical significance. CCP treatment was associated with reduced D28 mortality in immunosuppressed patients.
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Background. There are few real-world data on the use of remdesivir (RDV) looking at timing of initiation in relation to symptom onset and severity of presenting disease. Methods. We conducted multi-country retrospective study of clinical practice and use of RDV in COVID-19 patients. De-identified medical records data were entered into an e-CRF. Primary endpoints were all-cause mortality at day 28 and hospitalization duration. We assessed time from symptom onset to RDV start and re-admission. We included adults with PCR-confirmed symptomatic COVID-19 who were hospitalized after Aug 31, 2020 and received at least 1 dose of RDV. Descriptive analyses were conducted. Kaplan-Meier methods were used to calculate the mortality rate, LogRank test to compare groups defined by severity of disease. Competing risk regression with discharge and death as competing events was used to estimate duration of hospitalization, and Gray's test to compare the groups. Results. 448 patients in 5 countries (12 sites) were included. Demographics are summarized (table) by 3 disease severity groups at baseline: no supplemental oxygen (NSO), low flow oxygen ≤6 L/min (LFO), and high-flow oxygen > 6L/min (HFO). No demographic differences were found between groups except for the higher percentage of cancer/chemotherapy patients in NSO group. Corticosteroids use was HFO 73.6%, LFO 62.7%, NSO 58.0%. Mortality rate was significantly lower in NSO, and LFO groups compared with HFO (6.2%, 10.2%, 23.6%, respectively;Fig1). Median duration of hospitalization was 9 (95%CI 8-10), 9 (8-9), 13 (10-15) days, respectively (Fig2). Median time from first symptom to RDV start was 7 days in all 3 groups. Patients started RDV on day 1 of hospitalization in HFO and LFO and day 2 on NSO groups. And received a 5 day course (median). Readmission within 28-days of discharge was < 5% and similar across all 3 groups. Conclusion. In this real-world cohort of COVID-19 positive hospitalized patients, RDV use was consistent across countries. RDV was started within a median of 7 days from symptom within 2 days of admission and given for a median of 5 days. Higher mortality rate and duration of hospitalization was seen in the HFO group and similar rates seen in the LFO and NSO groups. Readmission was consistently low across all 3 groups.
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BACKGROUND: We aimed to describe the epidemiology, risk factors, and clinical outcomes of co-infections and superinfections in onco-hematological patients with COVID-19. METHODS: International, multicentre cohort study of cancer patients with COVID-19. All patients were included in the analysis of co-infections at diagnosis, while only patients admitted at least 48 h were included in the analysis of superinfections. RESULTS: 684 patients were included (384 with solid tumors and 300 with hematological malignancies). Co-infections and superinfections were documented in 7.8% (54/684) and 19.1% (113/590) of patients, respectively. Lower respiratory tract infections were the most frequent infectious complications, most often caused by Streptococcus pneumoniae and Pseudomonas aeruginosa. Only seven patients developed opportunistic infections. Compared to patients without infectious complications, those with infections had worse outcomes, with high rates of acute respiratory distress syndrome, intensive care unit (ICU) admission, and case-fatality rates. Neutropenia, ICU admission and high levels of C-reactive protein (CRP) were independent risk factors for infections. CONCLUSIONS: Infectious complications in cancer patients with COVID-19 were lower than expected, affecting mainly neutropenic patients with high levels of CRP and/or ICU admission. The rate of opportunistic infections was unexpectedly low. The use of empiric antimicrobials in cancer patients with COVID-19 needs to be optimized.
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COVID-19 , Coinfection , Neoplasms , Superinfection , Cohort Studies , Coinfection/epidemiology , Humans , Intensive Care Units , Neoplasms/complications , Neoplasms/epidemiology , SARS-CoV-2ABSTRACT
Introduction: Mature T and NK-cell lymphomas represent a heterogeneous group of lymphoid disorders (29 subtypes according to the 2016 WHO classification) arising from mature T cells of post-thymic origin with different morphological characteristics, phenotypes, and clinical presentation. Following the success of the T Cell Project (TCP), which allowed the analysis of more than 1,500 cases of peripheral T-Cell lymphomas (PTCLs) collected prospectively in 18 Countries, in 2018 the TCP 2.0 was launched. Here we report the global distribution of PTCLs, from the cases registered so far based on the locally established histological diagnosis. Methods: The TCP2.0 (ClinicalTrials.gov Identifier: NCT03964480) is a prospective, international, observational study which adapts to changes made in the new WHO classification. Results: Since the beginning of the study (October 2018), 648 patients with newly diagnosed PTCL were registered by 75 active centers across 14 countries. Of these data, 594 patients have been validated by the centralized trial office. Overall, PTCL-NOS, Anaplastic large cell lymphoma (ALCL) ALK-negative, and Angioimmunoblastic T-cell lymphoma (AITL), represent the most frequent subtypes, representing 31.3%, 18,9% and 13,5% of cases, respectively. As reported in Table 1, PTCL-NOS represents the most frequent subtype worldwide, whereas Adult T-cell leukemia/lymphoma was more frequent in Brazil, AITL and ALCL ALK-negative in Australia/ India, and ALCL ALK-positive in North America and Europe. Extranodal NK/T-cell lymphoma, nasal type was relatively frequent in Brazil and quite rare in the other Latin America Countries. Finally, many sub-types represent less than 5% of cases in all geographic areas. Conclusions: The TCP2.0 continues to recruit very well, despite the difficulties linked to the COVID-19 pandemic, and may represent a useful resource for the prospective study of this group of rare lymphomas.
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RATIONALE: Numerous data regarding both clinical presentation and prognosis of COVID-19 have been published. Most studies focused on individual predictors for mortality. Although some prognostic factors were consistently identified across the different studies such as older age or cardiovascular comorbidities, other discrepancies reflect geographical location of the studies, characteristics of study population, admission in wards and/or intensive care units, and variables incorporated in the statistical model. We aimed to a priori identify specific patient profiles, then assessing their association with the outcomes in COVID-19 patients with respiratory symptoms admitted specifically in hospital wards. METHODS: We conducted a retrospective single center study from February, 27, 2020 to April, 27, 2020. A non-supervised cluster analysis was first used to detect patient profiles based on characteristics at admission of 220 consecutive patients admitted at our institution. Then, we assessed its prognostic value, using Cox regression analyses to predict survival. RESULTS: Three clusters were identified, with 47 patients in cluster 1, 87 in cluster 2, and 86 in cluster 3, and whose presentation differed. Cluster 1 mostly included sexagenarian patients with active malignancy who were admitted early after COVID-19 onset. Cluster 2 included the oldest, overweight patients with high blood pressure and renal insufficiency, while cluster 3 included the youngest patients with gastrointestinal symptoms and delayed admission. These subgroups of patients were associated with different outcomes, with 60 days survival of 74.3% (cluster1), 50.6% (cluster2) and 96.5% (cluster3) (figure 1). This was confirmed by the multivariable Cox analyses that exhibited the prognostic value of those patterns. CONCLUSION: The cluster approach seems appropriate and pragmatic to early identify patient profiles that could help physicians to segregate patients according to their prognosis. Figure 1: Survival since hospital admission according to the clusters .