Predictive value of the APACHE II, SAPS II, SOFA and GCS scoring systems in patients with severe purulent bacterial meningitis

  BACKGROUND: Scoring systems in critical care patients are essential for predicting of the patient outcome and evaluating the therapy. In this study, we determined the value of the Acute Physiology and Chronic Health Evaluation II (APACHE II), Simplified Acute Physiology Score II (SAPS II), Sequential Organ Failure Assessment (SOFA) and Glasgow Coma Scale (GCS) scoring systems in the prediction of mortality in adult patients admitted to the intensive care unit (ICU) with severe purulent bacterial meningitis. METHODS: We retrospectively analysed data from 98 adult patients with severe purulent bacterial meningitis who were admitted to the single ICU between March 2006 and September 2015. RESULTS: Univariate logistic regression identified the following risk factors of death in patients with severe purulent bacterial meningitis: APACHE II, SAPS II, SOFA, and GCS scores, and the lengths of ICU stay and hospital stay. The independent risk factors of patient death in multivariate analysis were the SAPS II score, the length of ICU stay and the length of hospital stay. In the prediction of mortality according to the area under the curve, the SAPS II score had the highest accuracy followed by the APACHE II, GCS and SOFA scores. CONCLUSIONS: For the prediction of mortality in a patient with severe purulent bacterial meningitis, SAPS II had the highest accuracy.  BACKGROUND: Scoring systems in critical care patients are essential for predicting of the patient outcome and evaluating the therapy. In this study, we determined the value of the Acute Physiology and Chronic Health Evaluation II (APACHE II), Simplified Acute Physiology Score II (SAPS II), Sequential Organ Failure Assessment (SOFA) and Glasgow Coma Scale (GCS) scoring systems in the prediction of mortality in adult patients admitted to the intensive care unit (ICU) with severe purulent bacterial meningitis. METHODS: We retrospectively analysed data from 98 adult patients with severe purulent bacterial meningitis who were admitted to the single ICU between March 2006 and September 2015. RESULTS: Univariate logistic regression identified the following risk factors of death in patients with severe purulent bacterial meningitis: APACHE II, SAPS II, SOFA, and GCS scores, and the lengths of ICU stay and hospital stay. The independent risk factors of patient death in multivariate analysis were the SAPS II score, the length of ICU stay and the length of hospital stay. In the prediction of mortality according to the area under the curve, the SAPS II score had the highest accuracy followed by the APACHE II, GCS and SOFA scores. CONCLUSIONS: For the prediction of mortality in a patient with severe purulent bacterial meningitis, SAPS II had the highest accuracy

Different epidemiology of bloodstream infections in COVID-19 compared to non-COVID-19 critically ill patients: a descriptive analysis of the Eurobact II study

Funder: European society of Intensive Care MedicineFunder: European Society of Clinical Microbiology and Infectious Diseases (ESCMID)Funder: Norva Dahlia foundation and the Redcliffe Hospital Private Practice Trust FundAbstract Background The study aimed to describe the epidemiology and outcomes of hospital-acquired bloodstream infections (HABSIs) between COVID-19 and non-COVID-19 critically ill patients. Methods We used data from the Eurobact II study, a prospective observational multicontinental cohort study on HABSI treated in ICU. For the current analysis, we selected centers that included both COVID-19 and non-COVID-19 critically ill patients. We performed descriptive statistics between COVID-19 and non-COVID-19 in terms of patients’ characteristics, source of infection and microorganism distribution. We studied the association between COVID-19 status and mortality using multivariable fragility Cox models. Results A total of 53 centers from 19 countries over the 5 continents were eligible. Overall, 829 patients (median age 65 years [IQR 55; 74]; male, n = 538 [64.9%]) were treated for a HABSI. Included patients comprised 252 (30.4%) COVID-19 and 577 (69.6%) non-COVID-19 patients. The time interval between hospital admission and HABSI was similar between both groups. Respiratory sources (40.1 vs. 26.0%, p &lt; 0.0001) and primary HABSI (25.4% vs. 17.2%, p = 0.006) were more frequent in COVID-19 patients. COVID-19 patients had more often enterococcal (20.5% vs. 9%) and Acinetobacter spp. (18.8% vs. 13.6%) HABSIs. Bacteremic COVID-19 patients had an increased mortality hazard ratio (HR) versus non-COVID-19 patients (HR 1.91, 95% CI 1.49–2.45). Conclusions We showed that the epidemiology of HABSI differed between COVID-19 and non-COVID-19 patients. Enterococcal HABSI predominated in COVID-19 patients. COVID-19 patients with HABSI had elevated risk of mortality. Trial registration ClinicalTrials.org number NCT03937245. Registered 3 May 2019. </jats:sec

Epidemiology and outcomes of hospital-acquired bloodstream infections in intensive care unit patients: the EUROBACT-2 international cohort study

Purpose In the critically ill, hospital-acquired bloodstream infections (HA-BSI) are associated with significant mortality. Granular data are required for optimizing management, and developing guidelines and clinical trials. Methods We carried out a prospective international cohort study of adult patients (≥ 18 years of age) with HA-BSI treated in intensive care units (ICUs) between June 2019 and February 2021. Results 2600 patients from 333 ICUs in 52 countries were included. 78% HA-BSI were ICU-acquired. Median Sequential Organ Failure Assessment (SOFA) score was 8 [IQR 5; 11] at HA-BSI diagnosis. Most frequent sources of infection included pneumonia (26.7%) and intravascular catheters (26.4%). Most frequent pathogens were Gram-negative bacteria (59.0%), predominantly Klebsiella spp. (27.9%), Acinetobacter spp. (20.3%), Escherichia coli (15.8%), and Pseudomonas spp. (14.3%). Carbapenem resistance was present in 37.8%, 84.6%, 7.4%, and 33.2%, respectively. Difficult-to-treat resistance (DTR) was present in 23.5% and pan-drug resistance in 1.5%. Antimicrobial therapy was deemed adequate within 24 h for 51.5%. Antimicrobial resistance was associated with longer delays to adequate antimicrobial therapy. Source control was needed in 52.5% but not achieved in 18.2%. Mortality was 37.1%, and only 16.1% had been discharged alive from hospital by day-28. Conclusions HA-BSI was frequently caused by Gram-negative, carbapenem-resistant and DTR pathogens. Antimicrobial resistance led to delays in adequate antimicrobial therapy. Mortality was high, and at day-28 only a minority of the patients were discharged alive from the hospital. Prevention of antimicrobial resistance and focusing on adequate antimicrobial therapy and source control are important to optimize patient management and outcomes