In this large, prospective, multinational cohort, more than one half of all cases of non-HACEK gram-negative bacillus endocarditis were associated with health care contact. Non-HACEK gram-negative bacillus endocarditis is not primarily a disease of injection drug users.

Background Antiviral drugs are administered in patients with severe COVID‐19 respiratory syndrome, including those treated with direct oral anticoagulants (DOACs). Concomitant administration of antiviral agents has the potential to increase their plasma concentration. A series of patients managed in the Cremona Thrombosis Center were admitted at Cremona Hospital for SARS‐CoV‐2 and started antiviral drugs without stopping DOAC therapy. DOAC plasma levels were measured in hospital and results compared with those recorded before hospitalization. Methods All consecutive patients on DOACs were candidates for administration of antiviral agents (lopinavir, ritonavir, or darunavir). Plasma samples for DOAC measurement were collected 2to 4 days after starting antiviral treatment, at 12 hours from the last dose intake in patients on dabigatran and apixaban, and at 24 hours in those on rivaroxaban and edoxaban. For each patient, C‐trough DOAC level, expressed as ng/mL, was compared with the one measured before hospitalization. Results Of the 1039 patients hospitalized between February 22 and March 15, 2020 with COVID‐19 pneumonia and candidates for antiviral therapy, 32 were on treatment with a DOAC. DOAC was stopped in 20 and continued in the remaining 12. On average, C‐trough levels were 6.14 times higher during hospitalization than in the pre‐hospitalization period. Conclusion DOAC patients treated with antiviral drugs show an alarming increase in DOAC plasma levels. In order to prevent bleeding complications, we believe that physicians should consider withholding DOACs from patients with SARS‐CoV‐2 and replacing them with alternative parenteral antithrombotic strategies for as long as antiviral agents are deemed necessary and until discharge.

Timely identification of COVID-19 patients at high risk of mortality can significantly improve patient management and resource allocation within hospitals. This study seeks to develop and validate a data-driven personalized mortality risk calculator for hospitalized COVID-19 patients. De-identified data was obtained for 3,927 COVID-19 positive patients from six independent centers, comprising 33 different hospitals. Demographic, clinical, and laboratory variables were collected at hospital admission. The COVID-19 Mortality Risk (CMR) tool was developed using the XGBoost algorithm to predict mortality. Its discrimination performance was subsequently evaluated on three validation cohorts. The derivation cohort of 3,062 patients has an observed mortality rate of 26.84%. Increased age, decreased oxygen saturation (≤ 93%), elevated levels of C-reactive protein (≥ 130 mg/L), blood urea nitrogen (≥ 18 mg/dL), and blood creatinine (≥ 1.2 mg/dL) were identified as primary risk factors, validating clinical findings. The model obtains out-of-sample AUCs of 0.90 (95% CI, 0.87–0.94) on the derivation cohort. In the validation cohorts, the model obtains AUCs of 0.92 (95% CI, 0.88–0.95) on Seville patients, 0.87 (95% CI, 0.84–0.91) on Hellenic COVID-19 Study Group patients, and 0.81 (95% CI, 0.76–0.85) on Hartford Hospital patients. The CMR tool is available as an online application at covidanalytics.io/mortality_calculator and is currently in clinical use. The CMR model leverages machine learning to generate accurate mortality predictions using commonly available clinical features. This is the first risk score trained and validated on a cohort of COVID-19 patients from Europe and the United States.

We performed a multicentre retrospective cohort study including 606,649 acute inpatient episodes at 10 European hospitals in 2010 and 2011 to estimate the impact of antimicrobial resistance on hospital mortality, excess length of stay (LOS) and cost. Bloodstream infections (BSI) caused by third-generation cephalosporin-resistant Enterobacteriaceae (3GCRE), meticillin-susceptible (MSSA) and -resistant Staphylococcus aureus (MRSA) increased the daily risk of hospital death (adjusted hazard ratio (HR) = 1.80; 95% confidence interval (CI): 1.34–2.42, HR = 1.81; 95% CI: 1.49–2.20 and HR = 2.42; 95% CI: 1.66–3.51, respectively) and prolonged LOS (9.3 days; 95% CI: 9.2–9.4, 11.5 days; 95% CI: 11.5–11.6 and 13.3 days; 95% CI: 13.2–13.4, respectively). BSI with third-generation cephalosporin-susceptible Enterobacteriaceae (3GCSE) significantly increased LOS (5.9 days; 95% CI: 5.8–5.9) but not hazard of death (1.16; 95% CI: 0.98–1.36). 3GCRE significantly increased the hazard of death (1.63; 95% CI: 1.13–2.35), excess LOS (4.9 days; 95% CI: 1.1–8.7) and cost compared with susceptible strains, whereas meticillin resistance did not. The annual cost of 3GCRE BSI was higher than of MRSA BSI. While BSI with S. aureus had greater impact on mortality, excess LOS and cost than Enterobacteriaceae per infection, the impact of antimicrobial resistance was greater for Enterobacteriaceae.

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