9 research outputs found

    Co-infection and ICU-acquired infection in COIVD-19 ICU patients: a secondary analysis of the UNITE-COVID data set

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    Background: The COVID-19 pandemic presented major challenges for critical care facilities worldwide. Infections which develop alongside or subsequent to viral pneumonitis are a challenge under sporadic and pandemic conditions; however, data have suggested that patterns of these differ between COVID-19 and other viral pneumonitides. This secondary analysis aimed to explore patterns of co-infection and intensive care unit-acquired infections (ICU-AI) and the relationship to use of corticosteroids in a large, international cohort of critically ill COVID-19 patients.Methods: This is a multicenter, international, observational study, including adult patients with PCR-confirmed COVID-19 diagnosis admitted to ICUs at the peak of wave one of COVID-19 (February 15th to May 15th, 2020). Data collected included investigator-assessed co-infection at ICU admission, infection acquired in ICU, infection with multi-drug resistant organisms (MDRO) and antibiotic use. Frequencies were compared by Pearson's Chi-squared and continuous variables by Mann-Whitney U test. Propensity score matching for variables associated with ICU-acquired infection was undertaken using R library MatchIT using the "full" matching method.Results: Data were available from 4994 patients. Bacterial co-infection at admission was detected in 716 patients (14%), whilst 85% of patients received antibiotics at that stage. ICU-AI developed in 2715 (54%). The most common ICU-AI was bacterial pneumonia (44% of infections), whilst 9% of patients developed fungal pneumonia; 25% of infections involved MDRO. Patients developing infections in ICU had greater antimicrobial exposure than those without such infections. Incident density (ICU-AI per 1000 ICU days) was in considerable excess of reports from pre-pandemic surveillance. Corticosteroid use was heterogenous between ICUs. In univariate analysis, 58% of patients receiving corticosteroids and 43% of those not receiving steroids developed ICU-AI. Adjusting for potential confounders in the propensity-matched cohort, 71% of patients receiving corticosteroids developed ICU-AI vs 52% of those not receiving corticosteroids. Duration of corticosteroid therapy was also associated with development of ICU-AI and infection with an MDRO.Conclusions: In patients with severe COVID-19 in the first wave, co-infection at admission to ICU was relatively rare but antibiotic use was in substantial excess to that indication. ICU-AI were common and were significantly associated with use of corticosteroids

    Characteristics of co-infection and secondary infection amongst critically ill COVID-19 patients in the first two waves of the pandemic

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    Clinical and organizational factors associated with mortality during the peak of first COVID-19 wave : the global UNITE-COVID study (vol 48, pg 690, 2022)

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    Clinical and organizational factors associated with mortality during the peak of first COVID-19 wave : the global UNITE-COVID study

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    Purpose To accommodate the unprecedented number of critically ill patients with pneumonia caused by coronavirus disease 2019 (COVID-19) expansion of the capacity of intensive care unit (ICU) to clinical areas not previously used for critical care was necessary. We describe the global burden of COVID-19 admissions and the clinical and organizational characteristics associated with outcomes in critically ill COVID-19 patients. Methods Multicenter, international, point prevalence study, including adult patients with SARS-CoV-2 infection confirmed by polymerase chain reaction (PCR) and a diagnosis of COVID-19 admitted to ICU between February 15th and May 15th, 2020. Results 4994 patients from 280 ICUs in 46 countries were included. Included ICUs increased their total capacity from 4931 to 7630 beds, deploying personnel from other areas. Overall, 1986 (39.8%) patients were admitted to surge capacity beds. Invasive ventilation at admission was present in 2325 (46.5%) patients and was required during ICU stay in 85.8% of patients. 60-day mortality was 33.9% (IQR across units: 20%-50%) and ICU mortality 32.7%. Older age, invasive mechanical ventilation, and acute kidney injury (AKI) were associated with increased mortality. These associations were also confirmed specifically in mechanically ventilated patients. Admission to surge capacity beds was not associated with mortality, even after controlling for other factors. Conclusions ICUs responded to the increase in COVID-19 patients by increasing bed availability and staff, admitting up to 40% of patients in surge capacity beds. Although mortality in this population was high, admission to a surge capacity bed was not associated with increased mortality. Older age, invasive mechanical ventilation, and AKI were identified as the strongest predictors of mortality

    Clinical utility and prognostic implications of the novel 4S-AF scheme to characterize and evaluate patients with atrial fibrillation: a report from ESC-EHRA EORP-AF Long-Term General Registry

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    Aims: The 4S-AF classification scheme comprises of four domains: stroke risk (St), symptoms (Sy), severity of atrial fibrillation (AF) burden (Sb), and substrate (Su). We sought to examine the implementation of the 4S-AF scheme in the EORP-AF General Long-Term Registry and compare outcomes in AF patients according to the 4S-AF-led decision-making process. Methods and results: Atrial fibrillation patients from 250 centres across 27 European countries were included. A 4S-AF score was calculated as the sum of each domain with a maximum score of 9. Of 6321 patients, 8.4% had low (St), 47.5% EHRA I (Sy), 40.5% newly diagnosed or paroxysmal AF (Sb), and 5.1% no cardiovascular risk factors or left atrial enlargement (Su). Median follow-up was 24 months. Using multivariable Cox regression analysis, independent predictors of all-cause mortality were (St) [adjusted hazard ratio (aHR) 8.21, 95% confidence interval (CI): 2.60-25.9], (Sb) (aHR 1.21, 95% CI: 1.08-1.35), and (Su) (aHR 1.27, 95% CI: 1.14-1.41). For CV mortality and any thromboembolic event, only (Su) (aHR 1.73, 95% CI: 1.45-2.06) and (Sy) (aHR 1.29, 95% CI: 1.00-1.66) were statistically significant, respectively. None of the domains were independently linked to ischaemic stroke or major bleeding. Higher 4S-AF score was related to a significant increase in all-cause mortality, CV mortality, any thromboembolic event, and ischaemic stroke but not major bleeding. Treatment of all 4S-AF domains was associated with an independent decrease in all-cause mortality (aHR 0.71, 95% CI: 0.55-0.92). For each 4S-AF domain left untreated, the risk of all-cause mortality increased substantially (aHR 1.35, 95% CI: 1.16-1.56). Conclusion: Implementation of the novel 4S-AF scheme is feasible, and treatment decisions based on this scheme improve mortality rates in AF

    The SAMe-TT2R2 score and quality of anticoagulation in atrial fibrillation: a simple aid to decision-making on who is suitable (or not) for vitamin K antagonists

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    International audienc

    Clinical utility and prognostic implications of the novel 4S-AF scheme to characterize and evaluate patients with atrial fibrillation: a report from ESC-EHRA EORP-AF Long-Term General Registry

    No full text
    International audienceAbstract Aims The 4S-AF classification scheme comprises of four domains: stroke risk (St), symptoms (Sy), severity of atrial fibrillation (AF) burden (Sb), and substrate (Su). We sought to examine the implementation of the 4S-AF scheme in the EORP-AF General Long-Term Registry and compare outcomes in AF patients according to the 4S-AF-led decision-making process. Methods and results Atrial fibrillation patients from 250 centres across 27 European countries were included. A 4S-AF score was calculated as the sum of each domain with a maximum score of 9. Of 6321 patients, 8.4% had low (St), 47.5% EHRA I (Sy), 40.5% newly diagnosed or paroxysmal AF (Sb), and 5.1% no cardiovascular risk factors or left atrial enlargement (Su). Median follow-up was 24 months. Using multivariable Cox regression analysis, independent predictors of all-cause mortality were (St) [adjusted hazard ratio (aHR) 8.21, 95% confidence interval (CI): 2.60–25.9], (Sb) (aHR 1.21, 95% CI: 1.08–1.35), and (Su) (aHR 1.27, 95% CI: 1.14–1.41). For CV mortality and any thromboembolic event, only (Su) (aHR 1.73, 95% CI: 1.45–2.06) and (Sy) (aHR 1.29, 95% CI: 1.00–1.66) were statistically significant, respectively. None of the domains were independently linked to ischaemic stroke or major bleeding. Higher 4S-AF score was related to a significant increase in all-cause mortality, CV mortality, any thromboembolic event, and ischaemic stroke but not major bleeding. Treatment of all 4S-AF domains was associated with an independent decrease in all-cause mortality (aHR 0.71, 95% CI: 0.55–0.92). For each 4S-AF domain left untreated, the risk of all-cause mortality increased substantially (aHR 1.35, 95% CI: 1.16–1.56). Conclusion Implementation of the novel 4S-AF scheme is feasible, and treatment decisions based on this scheme improve mortality rates in AF
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